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STRUCTURAL STRENGTH
AND STABILITY ASSESSMENT, RISKS AND POTENTIAL
HAZARDS IN THE ARCTIC ENVIRONMENT |
31-40 |
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Alena Rotaru |
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The paper deals with
the assessment of the strength and stability of
structures in Arctic soil conditions. The main
attention is paid to the unique properties of
such soils, which affect the reliability of
structures. These include extremely low
temperatures, permafrost, high humidity and the
presence of permafrost. It is noted that the
existing methods for assessing strength and
stability require further development and
adaptation. The specifics of Arctic soils should
be taken into account when choosing research
methods and approaches. The operation of
structures in the Arctic is associated with
risks of deformation and destruction due to
loads associated with soil features. Problems
may also occur due to changes in temperature and
humidity. To reduce risks and improve the
reliability of structures, it is proposed to
develop and implement comprehensive security
measures. They should take into account the
specifics of Arctic soils at all stages-from
design to operation of infrastructure facilities.
This may include the use of special materials,
the adaptation of design solutions, and the
development of new methods for monitoring the
state of structure. The results of the study can
be useful in the design and operation of
facilities in the Arctic, as well as in the
development of regulatory documents and
standards for construction in difficult ground
conditions. This will ensure the safety and
efficiency of structures in extreme climatic
conditions.
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Cite: Alena Rotaru
STRUCTURAL STRENGTH AND STABILITY ASSESSMENT,
RISKS AND POTENTIAL HAZARDS IN THE ARCTIC
ENVIRONMENT. Reliability: Theory & Applications.
2025, June 2(84): 31-40, DOI: https://doi.org/10.24412/1932-2321-2025-284-31-40
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ASSESSING
TRANSFORMATION RATIO OF VOLTAGE TRANSFORMER
UNDER NON-SINUSOIDAL SUPPLY VOLTAGE CONDITIONS |
41-51 |
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Nurali Yusifbayli,
Huseyngulu Guliyev, Naib Hajiyev and Nijat
Huseynov |
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Voltage transformers
are rarely subjected to periodic inspection and
testing while in operation, which is the reason
for the difference between actual transformation
ratios and their rated values. The frequency
characteristics of voltage transformers are
checked neither. Therefore, there can be large
errors in the case of non-sinusoidal supply
voltage. Existing studies on the study of
voltage transformer faults reflect the results
of the study of the equivalent circuit based on
traditional lumped-parameter circuits. However,
it should be noted that for high-frequency
circuits and at the same time from the point of
view of taking into account the structure of the
windings, increasing the accuracy of the
research results is an urgent issue. The case of
non-sinusoidal supply voltage is of great
scientific interest in this regard. Therefore,
considering the voltage transformer as a
distributed-parameter circuit, its fault under
non-sinusoidal supply voltage was investigated
and studied. This work explores errors of
voltage transformers in the presence of
non-sinusoidal voltage. To this end, a
mathematical model of the transformation ratio
is built considering the equivalent circuit of
transformer as a distributed-parameter circuit.
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Cite: Nurali
Yusifbayli, Huseyngulu Guliyev, Naib Hajiyev and
Nijat Huseynov ASSESSING TRANSFORMATION RATIO
OF VOLTAGE TRANSFORMER UNDER NON-SINUSOIDAL
SUPPLY VOLTAGE CONDITIONS . Reliability: Theory
& Applications. 2025, June 2(84): 41-51, DOI: https://doi.org/10.24412/1932-2321-2025-284-41-51
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ENHANCING
SENSITIVITY OF MTTF AND NETWORK RELIABILITY
STABILITY OF K-OUT-OF-N ACYCLIC TRANSMISSION
NETWORK |
52-66 |
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Hemalatha.G,
Vijayalakshmi.G |
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Networks are used in
many areas of engineering, including computers
and communication, transportation and electric
transmission. Component importance measures are
applicable to improve the system design. The
reliability characteristics of k-out-of-n
acyclic transmission network have been evaluated
using universal generating function (UGF). This
paper explores and analyses Mean Time To Failure
(MTTF), Birnbaum importance measurement,
critical component importance, component risk
growth factor, average risk growth factor and
MTTF sensitivity for acyclic transmission
network. Finally, The stability illustrates the
impact of component failure on the reliability
of the network system. The network reliability
stability for acyclic transmission network is
computed. In this work, we have evaluated
reliability characteristics and of the acyclic
transmission network using UGF method. The
network reliability stability for k-out-of-n
acyclic transmission network is computed.
Furthermore, numerical illustrations are
provided.
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Cite: Hemalatha.G,
Vijayalakshmi.G ENHANCING SENSITIVITY OF MTTF
AND NETWORK RELIABILITY STABILITY OF K-OUT-OF-N
ACYCLIC TRANSMISSION NETWORK . Reliability:
Theory & Applications. 2025, June 2(84): 52-66,
DOI: https://doi.org/10.24412/1932-2321-2025-284-52-66
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TWO PARAMETRIC
GENERALIZED FUZZY ENTROPY MEASURE WITH SOURCE
CODING |
67-77 |
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Tabasum Fatima, M.
A. K. Baig |
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In this manuscript,
we introduce a new generalized fuzzy information
measure for a fuzzy set. We establish its
validity as a fuzzy entropy measure. Also, we
define a new generalized fuzzy average code-word
length for a fuzzy set, and explore its
relationship with the fuzzy information measure.
We prove coding theorems for discrete noiseless
channels. The measures outlined in this
communication are not only novel, but also
encompass certain well-established measures from
the existing literature on fuzzy information
theory. We also show the proposed measure
through a dataset and and observe its
monotonicity through tabular and graphical
forms.
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Cite: Tabasum
Fatima, M. A. K. Baig TWO PARAMETRIC
GENERALIZED FUZZY ENTROPY MEASURE WITH SOURCE
CODING . Reliability: Theory & Applications.
2025, June 2(84): 67-77, DOI: https://doi.org/10.24412/1932-2321-2025-284-67-77
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SHREEKANT
DISTRIBUTION WITH PROPERTIES AND APPLICATIONS TO
MODEL STRESS AND STRENGTH DATA FROM ENGINEERING |
78-95 |
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Rama Shanker |
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Modeling and
analyzing real lifetime data that are stochastic
in nature with the existing lifetime
distributions is really a challenging task for
researchers. During the last decade several one
parameter lifetime distributions have been
proposed in statistics but almost each of them
has been found having some problems regarding
their goodness of fit on certain datasets. This
might have been due to their distributional
properties or due to stochastic nature of
datasets. In this paper, a new lifetime
distribution named Shreekant distribution has
been proposed which has been found to give
improved fits to lifetime datasets than those by
other existing ones such as exponential,
Lindley, Shanker, Akash, Sujatha and Uma
distributions. This has been shown by presenting
its fittings to two datasets relating to stress
and strength data from engineering. Its various
structural and other properties and estimation
of parameters by different methods of estimation
have also been studied.
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Cite: Rama Shanker
SHREEKANT DISTRIBUTION WITH PROPERTIES AND
APPLICATIONS TO MODEL STRESS AND STRENGTH DATA
FROM ENGINEERING. Reliability: Theory &
Applications. 2025, June 2(84): 78-95, DOI: https://doi.org/10.24412/1932-2321-2025-284-78-95
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ON THE FAILURE RATE
FUNCTION OF A SYSTEM UNDER THE δ-SHOCK MODEL |
96-100 |
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Reza Farhadian,
Habib Jafari, Hamed Lorvand |
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An interesting type
of shock model in reliability theory is the
delta-shock model, which is defined based on the
length of time between successive shocks.
Whenever this length is less than or equal to a
prefixed threshold called delta, the system will
fail. In this paper, the failure rate function
of a system subjected to random shocks under the
delta-shock model is discussed. To be more
precise, a simple approximate formula for the
failure rate function is established. Numerical
studies are performed under the assumption that
the arrival of shocks follows a Poisson process.
Based on the numerical results, the accuracy of
the approximation is evaluated, and it is also
shown that reducing the mean of inter-arrival
times between successive shocks leads to an
increase in the failure rate of the system.
Conclusions are presented at the end.
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Cite: Reza Farhadian,
Habib Jafari, Hamed Lorvand ON THE FAILURE
RATE FUNCTION OF A SYSTEM UNDER THE δ-SHOCK
MODEL. Reliability: Theory & Applications. 2025,
June 2(84): 96-100, DOI: https://doi.org/10.24412/1932-2321-2025-284-96-100
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COMPARATIVE ANALYSIS
OF BAYESIAN ESTIMATION TECHNIQUES FOR GAMMA
DISTRIBUTIONS |
101-111 |
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Vijay Kumar Lingutla,
Naganani Nadiminti, R. K. Davala |
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This paper explores
the estimation of the common scale parameter for
two Gamma populations using three Bayesian
methods: Approximate Bayesian Computation (ABC),
Hamiltonian Monte Carlo (HMC), and
Metropolis-Hastings (MH). Unlike traditional
methods like Maximum Likelihood Estimation (MLE),
which can be sensitive to model misspecification,
these Bayesian methods are more flexible in
handling parameter uncertainty and complex data.
ABC bypasses explicit likelihood calculations,
HMC improves sampling efficiency through
gradient information, and MH offers simplicity
and adaptability. A simulation study compares
these methods based on bias, mean squared error
(MSE), and computational efficiency.
Additionally, we apply these methods to real
glucose level data from male and female
individuals with diabetes, highlighting their
strengths and limitations. The results offer
practical recommendations for real-world
applications involving Gamma distributions,
contributing to the advancement of Bayesian
estimation techniques in complex parameter
estimation problems.
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Cite: Vijay Kumar
Lingutla, Naganani Nadiminti, R. K. Davala
COMPARATIVE ANALYSIS OF BAYESIAN ESTIMATION
TECHNIQUES FOR GAMMA DISTRIBUTIONS. Reliability:
Theory & Applications. 2025, June 2(84):
101-111, DOI: https://doi.org/10.24412/1932-2321-2025-284-101-111
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STOCHASTIC ANALYSIS
THROUGH MATLAB OF TWO-UNIT PARALLEL SYSTEM |
112-119 |
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Sonia, Shakuntla
Singla |
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This paper presents
a reliability modelling of a two parallel unit
of manufacturing Industry. Original conservation
figures of the manufacturing industry have been
applied for this determination. Four kinds of
failure were observed: developmental, electronic,
motorized and infrastructural failures. Both
units of manufacturing plant work in parallel
and independently. Various reliability
parameters of the plant such as availability,
busy period for repair, expected number of
repairs and profitability for each type of
failure are examined. Graphical Technique of
Regenerative Point, process of Markov and
Genetic Algorithm are applied for analysis.
Profit analysis for the plant is examined with
respect to returns of the plant and repair rate
along with a graphical representation.
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Cite: Sonia,
Shakuntla Singla STOCHASTIC ANALYSIS THROUGH
MATLAB OF TWO-UNIT PARALLEL SYSTEM. Reliability:
Theory & Applications. 2025, June 2(84):
112-119, DOI: https://doi.org/10.24412/1932-2321-2025-284-112-119
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PERFORMANCE ANALYSIS
OF SOFTWARE SYSTEM SUBJECT TO PREVENTIVE
MAINTENANCE AND SOFTWARE UP-GRADATION FACILITY |
120-127 |
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Kavita Thukral, Shiv
Kumar Sharma |
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Every industrialist
as well as scientist try to satisfy the
customers requirement by providing reliable
software systems and a software system is
reliable and profitable if it is easily
manageable. This study analyzes the criteria
under which software performs correctly with
software upgrade and preventive maintenance
facility. It is observed that researcher threw
light on negligible, major, and load faults
cause software to fail, after which load
recovery, major, and negligible upgrades are
carried out, but there are no discussion on
preventive maintenance concept. Sometimes, to
enhance the software reliability and
performance, preventive maintenance is utilized
and it is better to upgrade the software before
completely failure. The webull distributions are
followed by all of these failures and upgrade
rates. The malfunctioning program can always be
fixed by a skilled technician. The software
performance is analyzed by applying the
regenerative point technique and the semi markov
process. Software reliability metrics including
mean time to software system failure, software
availability, and software profit values are
calculated using tables.
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Cite: Kavita Thukral,
Shiv Kumar Sharma PERFORMANCE ANALYSIS OF
SOFTWARE SYSTEM SUBJECT TO PREVENTIVE
MAINTENANCE AND SOFTWARE UP-GRADATION FACILITY.
Reliability: Theory & Applications. 2025, June
2(84): 120-127, DOI: https://doi.org/10.24412/1932-2321-2025-284-120-127
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PERFORMANCE MEASURES
AND PARAMETRIC ESTIMATION OF A PARALLEL-SERIES
SYSTEM MODEL WITH WEIBULL FAILURE AND REPPAIR
TIME DISTRIBUTIONS |
128-140 |
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Shallu Sharma, Pawan
Kumar, Poonam Sharma |
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The present paper
aims at the study of three non-identical unit
parallel-series system model with Weibull
failure and repair time distributions. The main
focus is on the analysis of reliability
characteristics and also estimation of
parameters in Classical and Bayesian paradigms.
The units in the system are named as A, B and C.
In order that system works successfully, unit A
and anyone of the units B or C should work. Upon
failure a unit will immediately be taken up to
repair facility for necessary remedial actions.
A single repair facility is available to deal
with any kind of failure/fault detected with any
unit. First come first served service discipline
is followed. The failure and repair time
distributions for all the units are taken
Weibull with varying parameters. Regenerative
point technique is used to study various measure
of effectiveness. MLE and Bayes estimates of
various failure and repair parameters involved
in the study have been obtained. A simulation
study has also been undertaken to exhibit the
behaviour of obtained characteristics in
Classical and Bayesian setup and a comparison is
made thereupon. Various conclusions have been
drawn from the tables and graphs plotted for
numerous performance measures for varying values
of repair and failure parameters. Having
obtained all the reliability characteristics,
the profit incurred by the system has been
obtained and studied graphically too.
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Cite: Shallu Sharma,
Pawan Kumar, Poonam Sharma PERFORMANCE
MEASURES AND PARAMETRIC ESTIMATION OF A
PARALLEL-SERIES SYSTEM MODEL WITH WEIBULL
FAILURE AND REPPAIR TIME DISTRIBUTIONS.
Reliability: Theory & Applications. 2025, June
2(84): 128-140, DOI: https://doi.org/10.24412/1932-2321-2025-284-128-140
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EXPONENTIAL TYPE
ESTIMATORS OF POPULATION MEAN-A REVIEW |
141-155 |
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Sajad Hussain,
Vilayat Ali Bhat |
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Survey sampling is a
crucial statistical approach for making
inferences about population characteristics
based on the analysis of a representative sample.
This method offers a practical solution for
saving time and resources while ensuring
reliable outcomes. Auxiliary information plays a
pivotal role in enhancing the accuracy of
estimators used in finite population sampling.
Traditional estimators, such as ratio, product,
and regression types, have proven effective in
improving the precision of population parameter
estimation. The introduction of exponential-type
transcendental functions marked a significant
advancement in this field, further increasing
the efficiency of ratio and product estimators.
This study provides an in-depth review of the
literature on exponential-type ratio and product
estimators, emphasizing their relevance in
survey sampling. It examines theoretical
progress and practical implementations,
showcasing their potential to reduce bias and
improve estimation accuracy by leveraging
complex relationships between study variables
and auxiliary information. The insights from
this review contribute to advancing research in
finite population sampling and offer valuable
directions for future studies in the field.
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Cite: Sajad Hussain,
Vilayat Ali Bhat EXPONENTIAL TYPE ESTIMATORS
OF POPULATION MEAN-A REVIEW. Reliability: Theory
& Applications. 2025, June 2(84): 141-155, DOI: https://doi.org/10.24412/1932-2321-2025-284-141-155
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A COMPARATIVE
ANALYSIS OF GAMMA AND WEIBULL DISTRIBUTIONS IN
TAMIL CINEMA DATA |
156-162 |
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A. Vanathu Suresh, R
Subramani, S Vijayan |
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This paper aims to
systematically investigate the utility of the
Gamma and Weibull distributions, focusing on
their application to lifetime datasets and
clarifying their mathematical and statistical
properties. By analyzing lifetime data across
various disciplines, the research emphasizes the
effectiveness and flexibility of these
distributions in capturing the complexities
inherent in such data. It underscores the
importance of parameters such as standard error,
log-likelihood, Akaike Information Criterion (AIC),
Bayesian Information Criterion (BIC), and Hannan–Quinn
Information Criterion (HQIC) in value estimation.
The findings suggest that both distributions
provide valuable insights into the underlying
data, with practical implications for
reliability engineering and failure analysis.
Moreover, the study demonstrates that the
Weibull distribution offers a better fit to the
given data than the Gamma distribution due to
its adaptability, which yields superior results.
A key contribution of this study is the proposal
of a model based on estimating the Conditional
Weibull distribution for feature parameters,
which accurately predicts a finite mixture of
two-parameter Weibull distributions initially
verified on datasets.
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Cite: A. Vanathu
Suresh, R Subramani, S Vijayan A COMPARATIVE
ANALYSIS OF GAMMA AND WEIBULL DISTRIBUTIONS IN
TAMIL CINEMA DATA. Reliability: Theory &
Applications. 2025, June 2(84): 156-162, DOI: https://doi.org/10.24412/1932-2321-2025-284-156-162
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LEAST SQUARES,
MAXIMUM LIKELIHOOD, AND ANDERSON-DARLING TYPES
ESTIMATORS FOR ENTROPY TRANSFORMED EXPONENTIAL
DISTRIBUTION |
163-174 |
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Ikwuoche John DAVID,
Stephen MATHEW, Isah Charles SAIDU |
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Aim: This research
aim is to investigate the performance stability
and determine the best estimator among Least
Squares (LS), Maximum Likelihood (ML), and
Anderson Darling (AD) type (right tail AD, left
tail AD, second order right tail AD, and second
order left tail AD), estimators for estimating
the parameter of the Entropy Transformed
Exponential distribution. Methods: A Monte Carlo
simulation was conducted to evaluate the finite
sample performance stability and efficiency at
sample sizes of 20, 100, 250, 700, 1000, 1500,
2500, and 3000. The evaluation measures used for
assessment are the Absolute Bias (AB) and Root
Mean Square Error (RMSE) as performance metrics.
Real life data analysis was performed using a
field intensity data measured in microvolts
recorded at 5-second intervals. The data is a
positive right skewed data and highly peaked.
Results: The simulation results demonstrated
that the LS method consistently outperformed the
ML and AD type estimators. This is based on the
lowest values of AB and RMSE obtained across all
the eight sample sizes. Additionally, the
findings were validated through real world data,
where the LS estimator exhibited the lowest
standard error and the narrowest confidence
interval length. Based on the results, the LS is
ranked 1st, right tail AD ranked 2nd, second
order right tail AD ranked 3rd, MLE ranked 4th,
left tail AD ranked 5th, and second order left
tail AD ranked 6th. However, results from t-test
in determining the significance of the parameter
estimate from each estimator, shows that MLE and
second order left tail AD estimates are not
significant at 5%. The graphical representation
of the field intensity data by each estimators
fit clearly depict the LS estimator best
describe the data distribution. Conclusion:
Based on these findings, the study concludes
that the LS estimator is the most effective
method for estimating the parameter of the
Entropy Transformed Exponential distribution
followed by the right tail AD, second order
right tail AD, MLE, left tail AD, and second
order left tail AD being the least effective
estimator.
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Cite: Ikwuoche John
DAVID, Stephen MATHEW, Isah Charles SAIDU
LEAST SQUARES, MAXIMUM LIKELIHOOD, AND
ANDERSON-DARLING TYPES ESTIMATORS FOR ENTROPY
TRANSFORMED EXPONENTIAL DISTRIBUTION.
Reliability: Theory & Applications. 2025, June
2(84): 163-174, DOI: https://doi.org/10.24412/1932-2321-2025-284-163-174
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SOME ADDITIONAL
PROPERTIES OF KUMARASWAMY LOG-LOGISTIC
DISTRIBUTION BASED ON ORDER RANDOM VARIATES |
175-187 |
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Bavita Singh, Nazia
Wahid, Mahfooz Alam, Aafaq A. Rather |
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The Exponentialed
Kumaraswamy-Dagum distribution represents a
significant advancement in the family of
probability distributions. This family
encompasses several well-established sub-models,
including a variant of the Kumaraswamy-Fisk or
Kumaraswamy log-logistic distribution, referred
to as the Exponentialed Kumaraswamy-Dagum family
distribution. In this paper, we characterize the
Kumaraswamy log-logistic (KSLL) distribution by
employing the moment features of generalized
order statistics. Explicit expressions and
recurrence relations are derived for both the
single and product moments of generalized order
statistics associated with the KSLL distribution.
These formulations specifically address record
values and moments of order statistics.
Additionally, the distribution is further
analyzed through conditional moments, and a
recurrence relation for single moments of
generalized order statistics is established.
This rigorous investigation seeks to deepen the
understanding of the KSLL distribution and its
statistical properties as obtained by
generalized order statistics.
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Cite: Bavita Singh,
Nazia Wahid, Mahfooz Alam, Aafaq A. Rather
SOME ADDITIONAL PROPERTIES OF KUMARASWAMY
LOG-LOGISTIC DISTRIBUTION BASED ON ORDER RANDOM
VARIATES . Reliability: Theory & Applications.
2025, June 2(84): 175-187, DOI: https://doi.org/10.24412/1932-2321-2025-284-175-187.
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COMPARATIVE ANALYSIS
OF THE RELIABILITY OF VACUUM AND OIL CIRCUIT
BREAKERS |
188-193 |
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Ilham RAHIMLI,
Aliashraf BAKHTIYAROV |
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In modern power
systems, switching equipment plays a crucial
role in ensuring the safe and reliable
connection and disconnection of electrical
circuits. A failure of a circuit breaker can
lead to serious consequences, including
prolonged power outages and damage to expensive
equipment. This paper presents a comparative
analysis of the reliability of vacuum and oil
circuit breakers, considering operational,
technical, and economic factors. It examines the
main causes of failures, methods of reliability
assessment, and provides a comprehensive
evaluation of the effectiveness of each type of
breaker under various conditions. The novelty of
the proposed solution lies in the in-depth
analysis of operational characteristics and a
multifaceted evaluation of the impact of
external factors on equipment reliability.
Modern diagnostic and monitoring methods,
including thermography, ultrasonic diagnostics,
and the integration of IoT systems for real-time
monitoring, are used. These approaches improve
the processes of equipment selection and
operation, ultimately contributing to the
overall reliability of power systems. The paper
aims to support informed decision-making in
equipment selection to enhance the overall
reliability of power systems.
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Cite: Ilham RAHIMLI,
Aliashraf BAKHTIYAROV COMPARATIVE ANALYSIS OF
THE RELIABILITY OF VACUUM AND OIL CIRCUIT
BREAKERS. Reliability: Theory & Applications.
2025, June 2(84): 188-193, DOI: https://doi.org/10.24412/1932-2321-2025-284-188-193.
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RELIABILITY ANALYSIS
OF THE SHAFT SUBJECTED TO FLUCTUATING LOADS
UNDER TORSION AND BENDING MOMENTS WHEN SHEAR
STRESS FOLLOWS EXPONENTIAL DISTRIBUTION |
194-200 |
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Md. Yakoob Pasha, M.
Tirumala Devi, T. Sumathi Uma Maheswari |
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The reliability of
shafts subjected to fluctuating loads is
essential for ensuring the safe and efficient
operation of rotating machinery in various
engineering applications, including automotive,
aerospace, and industrial systems. Accurate
reliability assessments are crucial to
preventing failures and extending the lifespan
of mechanical components. This study examines
the reliability analysis of shafts subjected to
combined torsional and bending moments, which
create complex stress states that significantly
affect shaft performance and failure behaviour.
A statistical model is considered since the
shear stress generated is random in nature.
Analytical expressions for reliability are
derived by changing the parameters twisting
moment, bending moment, and shaft diameter.
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Cite: Md. Yakoob
Pasha, M. Tirumala Devi, T. Sumathi Uma
Maheswari RELIABILITY ANALYSIS OF THE SHAFT
SUBJECTED TO FLUCTUATING LOADS UNDER TORSION AND
BENDING MOMENTS WHEN SHEAR STRESS FOLLOWS
EXPONENTIAL DISTRIBUTION . Reliability: Theory &
Applications. 2025, June 2(84): 194-200, DOI: https://doi.org/10.24412/1932-2321-2025-284-194-200.
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ANALYSIS OF TWO
VACATION POLICIES UNDER RETRIAL ATTEMPTS,
MARKOVIAN ENCOURAGED ARRIVAL QUEUING MODEL |
201-209 |
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E. IsmailKhan, V.
Narmadha, N. Yathavan |
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This paper presents
a comprehensive analysis of a single-server
Markovian queueing system incorporating two
distinct vacation policies under a framework of
encouraged arrivals and retrial attempts. The
novelty of the model lies in its simultaneous
treatment of several realistic operational
dynamics: server vacations with acceleratory
growth, customer impatience, server breakdown
and repair, and encouraged arrivals, where
potential customers are motivated to join the
system depending on its state. To reflect
real-world retrial scenarios, customers who do
not receive immediate service reattempt after
some time, modeled using a retrial queue
mechanism. Two key vacation policies are
compared: one governed by a first-come,
first-served (FCFS) discipline and the other
utilizing bulk service. The paper derives
steady-state probabilities and evaluates system
performance measures, such as mean queue length,
server utilization, and the expected number of
retrials.
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Cite: E. IsmailKhan,
V. Narmadha, N. Yathavan ANALYSIS OF TWO
VACATION POLICIES UNDER RETRIAL ATTEMPTS,
MARKOVIAN ENCOURAGED ARRIVAL QUEUING MODEL.
Reliability: Theory & Applications. 2025, June
2(84): 201-209, DOI: https://doi.org/10.24412/1932-2321-2025-284-201-209.
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CONSTRUCTING A
SEPARATE RESERVE IN A CHAIN OF LOW-RELIABILITY
ELEMENTS |
210-213 |
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Gurami Tsitsiashvili,
Yury Kharchenko |
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In this paper, we
construct upper and lower estimates of the
minimum separate reserve of low-reliability
chain elements of length m, at which the
probability of operability of the entire chain
becomes close to unity. The appeal to a separate
reserve is caused by the properties of this
reserve, established by Barlow and Proschan. It
is shown that the upper and lower estimates of
the minimum separate reserve are quite close. If
the probability of operability of an individual
element of the chain is 1/ln m, then the minimum
reserve volume is of the order ln2 m.
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Cite: Gurami
Tsitsiashvili, Yury Kharchenko CONSTRUCTING A
SEPARATE RESERVE IN A CHAIN OF LOW-RELIABILITY
ELEMENTS . Reliability: Theory & Applications.
2025, June 2(84): 210-213, DOI: https://doi.org/10.24412/1932-2321-2025-284-210-213.
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EVALUATING THE
IMPACT OF PARAMETER SENSITIVITY IN
META-HEURISTICS ON RELIABILITY PERFORMANCE |
214-226 |
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Shakuntla Singla,
Manisha Rani, Shilpa Rani, Umar Muhammad Modibbo |
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The optimizing
reliability of a system is a crucial target for
any industry to have good values and outcomes
with the balanced cost of maintenance. The
assessment of costs and reliability in intricate
systems, such as Distributed Redundancy
Architecture (DRA), is essential for optimal
system design. Achieving this involves
addressing various constraints to enhance the
overall system's reliability. Researchers have
explored system dependability and cost
optimization challenges, emphasizing the
evolution of metaheuristic approaches. Enhancing
system resilience and optimizing costs are
central objectives of this study, aiming to
improve the reliability and cost-efficiency of
DRA systems. The study's framework builds upon
existing metaheuristic methods, including Moth
Flame Optimization (MFO), Whale Optimization
Algorithm (WOA), Dragonfly Algorithm (DA),
Gazelle Optimization Algorithm (GOA), and Coati
Optimization Algorithm (COA). The findings
reveal that COA demonstrates superior
performance compared to other methods. By
employing the Coati Optimization Algorithm, this
study effectively addresses cost and
reliability-optimization challenges, providing
highly efficient solutions. Key metrics such as
reliability and cost were compared across the
five metaheuristic approaches, showcasing COA's
advantages. Notably, the Coati Optimization
Algorithm delivers faster resolutions and
outperforms its counterparts in reducing costs
while enhancing system reliability. The results
underscore COA's ability to optimize intricate
system parameters more effectively than methods
like MFO, WOA, GOA, and DA. This research
highlights the value of using COA for improving
reliability and minimizing expenses in complex
systems. It offers a novel approach to
addressing these challenges, establishing COA as
a powerful tool for optimizing distributed
system architectures. By analyzing comparative
solutions, the study found that COA consistently
achieved better outcomes, affirming its success
in reliability and cost optimization. In
conclusion, this research emphasizes the
importance of advanced metaheuristic techniques,
particularly the Coati Optimization Algorithm,
in enhancing the performance of Distributed
Redundancy Architectures. By presenting a
numerical example, the comparison has been made
and the outcomes are shown graphically and in
the tabular form to have a clear understanding.
The findings contribute significantly to the
field by providing a robust method for achieving
cost-efficient and reliable system designs.
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Cite: Shakuntla
Singla, Manisha Rani, Shilpa Rani, Umar Muhammad
Modibbo EVALUATING THE IMPACT OF PARAMETER
SENSITIVITY IN META-HEURISTICS ON RELIABILITY
PERFORMANCE . Reliability: Theory & Applications.
2025, June 2(84): 214-226, DOI: https://doi.org/10.24412/1932-2321-2025-284-214-226.
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ESTIMATING THE
FRECHET DISTRIBUTION'S SCALE PARAMETER USING
BAYESIAN METHODS FOR SYMMETRIC AND ASYMMETRIC
LOSS FUNCTIONS |
227-233 |
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S. C. Premila, S.
Jayabharathi, D. Kanagajothi, D. Pachiyappan |
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Comparing several
estimators to estimate the scale parameter of
the Frechet distribution based on complete data
when the shape parameter is known is the focus
of this research. Using the power function
distribution as a prior distribution and the
maximum likelihood estimator (MLE), we apply the
Bayes estimators under the squared error loss
function (SELF), linear exponential loss
function (LLF), asymmetric precautionary loss
function (APLF), and composite LINEX loss
function (CLLF). A Monte Carlo simulation study
served as the basis for the comparison. The
performance of these estimators in relation to
the mean square error (MSE) was compared through
the simulation study.
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Cite: S. C. Premila,
S. Jayabharathi, D. Kanagajothi, D. Pachiyappan
ESTIMATING THE FRECHET DISTRIBUTION'S SCALE
PARAMETER USING BAYESIAN METHODS FOR SYMMETRIC
AND ASYMMETRIC LOSS FUNCTIONS . Reliability:
Theory & Applications. 2025, June 2(84):
227-233, DOI: https://doi.org/10.24412/1932-2321-2025-284-227-233.
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MODELING AND
ANALYSIS OF THE WEIGHTED POWER CHRIS JERRY
DISTRIBUTION FOR RELIABILITY ENGINEERING |
234-241 |
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R. Sembiyan, Iyappan.
M, D. Suresh, Kalaivanan. S, R. Saranraj |
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This paper
introduces a new class of probability
distribution, termed the Weighted Power Chris
Jerry (WPCJ) distribution. This distribution is
developed by applying a weighting technique to
the baseline Power Chris Jerry distribution,
resulting in a more flexible and robust
statistical model. The mathematical and
statistical properties of the WPCJ distribution,
including its moments, reliability measures, and
order statistics, are derived and analyzed in
detail. The parameters of the proposed
distribution are estimated using the Maximum
Likelihood Estimation (MLE) method, ensuring
effective application in real-world scenarios.
To demonstrate the practical utility of the WPCJ
distribution, it is applied to a real-life
dataset. This application highlights the
distribution's ability to model lifetime data
effectively, showcasing its superiority over
existing models. The weighted distribution
approach offers significant advancements in
distribution theory, providing enhanced
flexibility for modeling complex data structures
across various domains, including reliability
engineering, biomedicine, and ecological studies.
The introduction of weighted distributions is
grounded in the foundational work of Fisher and
Rao, which demonstrated their importance in
situations where observations are influenced by
ascertainment methods or weight functions. By
extending these principles, the WPCJ
distribution offers a novel tool for addressing
conceptual challenges in data representation and
model development. This study further
contributes to the literature by illustrating
the adaptability and effectiveness of weighted
distributions in tackling diverse analytical
problems.
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Cite: R. Sembiyan,
Iyappan. M, D. Suresh, Kalaivanan. S, R.
Saranraj MODELING AND ANALYSIS OF THE WEIGHTED
POWER CHRIS JERRY DISTRIBUTION FOR RELIABILITY
ENGINEERING . Reliability: Theory & Applications.
2025, June 2(84): 234-241, DOI: https://doi.org/10.24412/1932-2321-2025-284-234-241.
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BAYES ESTIMATES FOR
THE PARAMETERS OF POISSON TYPE ONE PARAMETER
RAYLEIGH CLASS SRGM USING GAMMA AND INVERTED
GAMMA PRIORS |
242-249 |
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Rajesh Singh,
Kailash R. Kale and Pritee Singh |
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Research on the
reliability of both software and hardware
commonly utilizes the Rayleigh distribution as a
model. During software testing, the failure
occurrence behavior can be used to evaluate the
software's reliability. In this paper, the
Poisson pattern of failure occurrence is assumed
to study the parameters of the Rayleigh Class
software reliability growth model. It has been
studied how the Rayleigh Class Model's scale
parameter and the quantity of software's
intrinsic failures behave. Additionally, using
the Gamma and Inverted Gamma Priors,
respectively, Bayes estimates for the number of
intrinsic failures and the scale parameter are
suggested. The comparative analysis of the
proposed Bayes estimators and accompanying MLEs
is done using the relative efficiency that are
acquired via the use of Monte Carlo Simulation.
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Cite: Rajesh Singh,
Kailash R. Kale and Pritee Singh BAYES ESTIMATES
FOR THE PARAMETERS OF POISSON TYPE ONE PARAMETER
RAYLEIGH CLASS SRGM USING GAMMA AND INVERTED
GAMMA PRIORS. Reliability: Theory & Applications.
2025, June 2(84): 242-249, DOI: https://doi.org/10.24412/1932-2321-2025-284-242-249.
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COX'S REGRESSION
MODEL FOR RELIABILITY ANALYSIS AND FAILURE TIME
PREDICTION IN ENGINEERING SYSTEMS |
250-258 |
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Iyappan. M, Balaji.
M, G. Sathya Priyanka, Jesmon Raj. N, P B Deepa |
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Accelerated Failure
Time Models (AFTMs) are utilized to examine
survival patterns, particularly in the context
of diseases such as diabetes, where traditional
models like Cox proportional hazards may not
apply. In this study, we apply AFTMs to identify
significant prognostic factors affecting
survival in male diabetic patients, using
parametric distributions such as Exponential,
Weibull, Log-normal, and Log-logistic. The
primary objective of this study is to gain
deeper insights into how key covariates
influence survival times and enhance risk
stratification, ultimately leading to better
treatment outcomes. We evaluated the fit of
several AFTMs by comparing Log-Likelihood,
Akaike Information Criterion (AIC), and Bayesian
Information Criterion (BIC) values. Among the
models tested, the Weibull AFTM emerged as the
best fit, demonstrating superior Log-Likelihood
and lower AIC and BIC values compared to other
distributions. The study identified several
significant predictors of survival in male
diabetic patients, including age, family history
of diabetes, duration of diabetes, early use of
insulin (within one year of diagnosis),
retinopathy, use of diuretics, proteinuria,
hypertension, and fasting plasma glucose levels.
All of these covariates were found to
significantly influence survival outcomes (P<0.05),
with older age and longer diabetes duration
correlating with poorer survival rates. These
findings underscore the importance of using
AFTMs to model survival patterns in diabetic
patients and the potential for targeted
interventions based on identified risk factors.
While the small sample size limits the
generalizability of the results, this study
provides valuable insights into the survival
characteristics of male diabetic patients and
highlights the need for further research with
larger datasets. Future studies should consider
a wider range of covariates and explore the
application of AFTMs in broader diabetic
populations to refine survival prediction models
and optimize patient care. Additionally,
integrating machine learning techniques with
AFTMs could enhance predictive accuracy and
provide a more comprehensive understanding of
survival trends in diabetic patients.
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Cite: Iyappan. M,
Balaji. M, G. Sathya Priyanka, Jesmon Raj. N, P
B Deepa COX'S REGRESSION MODEL FOR RELIABILITY
ANALYSIS AND FAILURE TIME PREDICTION IN
ENGINEERING SYSTEMS . Reliability: Theory &
Applications. 2025, June 2(84): 250-258, DOI: https://doi.org/10.24412/1932-2321-2025-284-250-258.
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BIPOLAR NEUTROSOPHIC
MINIMUM SPANNING TREE NETWORK USING UPPER
TRIANGULAR WEIGHT/COST ALGORITHM |
259-264 |
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Shayathri
Linganathan, Purusotham Singamsetty |
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A minimum spanning
tree (MST) is a spanning tree in which the total
weights of all of its edges are the lowest of
all conceivable spanning trees for the network.
MST is crucial in discipline of the operation
research. Similarly, for the neutrosophic
minimum spanning tree problem (NMST) the weights
are unpredictable and inconsistent. The next
form of NMST is considered the bipolar
neutrosophic minimum spanning tree problem. Each
edge of the standard NMST is assigned a bipolar
weight based on the bipolar neutrosophic number
(consisting of positive and negative membership
degrees). This paper introduces the upper
triangular weight algorithm for a given network
and the optimal results are executed in MATLAB.
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Cite: Shayathri
Linganathan, Purusotham Singamsetty BIPOLAR
NEUTROSOPHIC MINIMUM SPANNING TREE NETWORK USING
UPPER TRIANGULAR WEIGHT/COST ALGORITHM .
Reliability: Theory & Applications. 2025, June
2(84): 259-264, DOI: https://doi.org/10.24412/1932-2321-2025-284-259-264.
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DESIGNING AN
ECONOMIC REPETITIVE GROUP SAMPLING PLAN FOR LIFE
TESTS BASED ON PERCENTILES OF EXPONENTIATED
RAYLEIGH DISTRIBUTION |
265-270 |
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P. Umanaheswari, S.
Suganya, K. Pradeepa Veerakumari |
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In this study, a
unique Repetitive Group Sampling Plan (RGSP) for
life tests is presented, emphasizing the use of
percentiles obtained from the Exponentialed
Rayleigh Distribution. To enhance the accuracy,
effectiveness, and general reliability of life
testing techniques, the suggested sample plan
provides a strong foundation for assessing the
longevity and reliability of goods in a variety
of industries. By offering a strong framework
for evaluating the robustness and lifespan of
products in diverse industries, the suggested
sample plan seeks to improve the efficiency and
reliability of life testing methods. Through the
incorporation of statistical techniques grounded
in the Exponentiated Rayleigh Distribution, this
research advances the fields of reliability
assessment and quality control in industrial
processes. Table values are calculated by using
Python programming. The implementation of these
statistical techniques not only enhances the
accuracy of life testing but also enables
businesses to make more informed decisions
regarding product development and quality
assurance. As industries increasingly rely on
data-driven approaches, this research provides a
valuable resource for optimizing performance and
minimizing costs.
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Cite: P.
Umanaheswari, S. Suganya, K. Pradeepa
Veerakumari DESIGNING AN ECONOMIC REPETITIVE
GROUP SAMPLING PLAN FOR LIFE TESTS BASED ON
PERCENTILES OF EXPONENTIATED RAYLEIGH
DISTRIBUTION. Reliability: Theory &
Applications. 2025, June 2(84): 265-270, DOI: https://doi.org/10.24412/1932-2321-2025-284-265-270.
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COMMON FIXED POINT
THEOREMS IN COMPLEX VALUED B-METRIC SPACES AND
USING WEAK COMPATIBLE MAPPINGS |
271-281 |
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Shivani Chourasiya,
Harshit Khare, Kavita Shrivastava |
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Complex-valued
metric spaces, where the distance between points
is represented as a complex number, serve as a
generalization of traditional metric spaces and
present a variety of intriguing applications,
particularly in advanced mathematics and
theoretical physics, such as in quantum
mechanics, quantum computing, functional
analysis, operator theory, complex dynamics,
fractal geometry, complex networks, and signal
processing, as well as theoretical physics,
relativity, geometry, topology, mathematical
finance, and economics. Despite the increasing
interest in complex-valued metric spaces, the
current literature on fixed point theorems
within these contexts is constrained in several
ways. The available literature has notable
shortcomings; consequently, this article
investigates the results and implications of
contractive mappings in complex-valued b-metric
spaces by utilizing weak compatible mappings,
and it also employs control functions while
solving a system of Urysohn integral equations
based on our primary result. These findings
contribute to this area of study.
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Cite: Shivani
Chourasiya, Harshit Khare, Kavita Shrivastava
COMMON FIXED POINT THEOREMS IN COMPLEX VALUED
B-METRIC SPACES AND USING WEAK COMPATIBLE
MAPPINGS . Reliability: Theory & Applications.
2025, June 2(84): 271-281, DOI: https://doi.org/10.24412/1932-2321-2025-284-271-281.
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ESTIMATION AND
APPLICATION OF A NEW GENERALIZATION OF
EXPONENTIAL DISTRIBUTION |
282-294 |
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D. Kumar, P. K.
Chaurasia, P. Kumar, A. Sahoo |
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In statistical
literature, several lifetime distributions exist
for real phenomena. And one of the methods to
find new lifetime distribution by existing
baseline distribution such a method is known as
the transformation method. In this article, we
proposed a generalization of the existing
transformation by introducing the additional
shape parameter. Here, we considered baseline
distributions as an exponential distribution.
Various statistical properties of the new
lifetime distribution, such as survival
function, hazard rate function, cumulative
hazard rate function, moments, quantile
function, and order statistics, have been
discussed. Demonstrate the applicability and
suitability of the proposed distribution. Here,
we focus only on the estimation of the
parameters likes MLE, LSE and also to check
long-run behaviour of the estimators.
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Cite: D. Kumar, P.
K. Chaurasia, P. Kumar, A. Sahoo ESTIMATION
AND APPLICATION OF A NEW GENERALIZATION OF
EXPONENTIAL DISTRIBUTION . Reliability: Theory &
Applications. 2025, June 2(84): 282-294, DOI: https://doi.org/10.24412/1932-2321-2025-284-282-294.
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PARABOLIC DENSE
CLOUDY FUZZY MODEL WITH DEMAND DEPENDENT
PRODUCTION RATE IN AN IMPRECISE PRODUCTION
PROCESS |
295-307 |
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Upsana Rana, Tanuj
Kumar |
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In this paper we
develop a classical economic production lot size
model of a manufactured item in a inadequate
production process in which the ordering cost is
fixed and shortage is not allowed. In this model
the valuation of an item is considered as a
parabolic cloudy fuzzy number and production
rate is depends on demand. In the previous
studies, fuzziness of parameters of the model is
presented in the form of fuzzy numbers using the
membership function only. Parabolic dense cloudy
intuitionistic fuzzy numbers are found to be
more generalized than fuzzy numbers and have the
capability to express the fuzziness of
parameters of the model in a more generalized
way using both membership and non-membership
functions. The presented model is solved in
crisp, fuzzy and Intuitionistic fuzzy setup
using proposed generalize and defuzzification
method with minimum loss of data. The present
model is solved by DBPSO algorithm to determine
optimal values. The validity of the proposed
model and parameter sensitivity analysis is
presented to justify the idea by the numerical
analysis.
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Cite: Upsana Rana,
Tanuj Kumar PARABOLIC DENSE CLOUDY FUZZY MODEL
WITH DEMAND DEPENDENT PRODUCTION RATE IN AN
IMPRECISE PRODUCTION PROCESS. Reliability:
Theory & Applications. 2025, June 2(84):
295-307, DOI: https://doi.org/10.24412/1932-2321-2025-284-295-307.
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RELIABILITY
AVAILABILITY MAINTAINABILITY DEPENDABILITY (RAMD)
OPTIMIZATION: A CASE STUDY OF MANUFACTURING
PLANT |
308-323 |
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Deepika Garg, Dipesh
Popli, Pradeep Kamboj, Nakul Vashishth |
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In the context of
modern Industry practices, optimizing the
performance of complex systems necessitates a
thorough understanding of Reliability,
Availability, Maintainability, and Dependability
(RAMD). This paper dives into the application of
two powerful optimization techniques, Genetic
Algorithm (GA) and Particle Swarm Optimization (PSO),
in RAMD optimization. GA, a simulation of
natural evolution, employs selection, crossover,
and mutation operations to search for optimal
solutions iteratively. In contrast, PSO
replicates the collective behavior of a swarm,
iteratively updating particle positions based on
their best position and the swarm’s best
position. The research specifically focuses on
RAMD optimization in terms of maintenance
schedules, resource allocation, and system
configurations. The results from both techniques
are compared, with PSO demonstrating superior
performance. The paper concludes by underscoring
the need for further research and practical
implementation of PSO and GA to fully exploit
their potential in optimizing RAMD parameters
across diverse domains.
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Cite: Deepika Garg,
Dipesh Popli, Pradeep Kamboj, Nakul Vashishth
RELIABILITY AVAILABILITY MAINTAINABILITY
DEPENDABILITY (RAMD) OPTIMIZATION: A CASE STUDY
OF MANUFACTURING PLANT. Reliability: Theory &
Applications. 2025, June 2(84): 308-323, DOI: https://doi.org/10.24412/1932-2321-2025-284-308-323.
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ON THE PROTECTION
AGAINST NOISE FOR MEASUREMENT-BASED QUANTUM
COMPUTATION |
324-331 |
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Valentin Vankov
Iliev |
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In this paper we
establish conditions for some pairs of quantum
logic gates which operate on one qubit to be
protected against crosstalk. We represent these
logic gates by self-adjoint operators acting on
an unitary plane, consider the resembling
bipartite quantum systems, and extend the
operators naturally to a commuting pair. Thus
the corresponding two measurements can be
considered as simultaneous and we can define
them as events in a classical probability space.
In particular, we are able to study their
dependence, the information noise thus produced,
and to find necessary and sufficient conditions
for being informationally independent events.
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Cite: Valentin
Vankov Iliev ON THE PROTECTION AGAINST NOISE
FOR MEASUREMENT-BASED QUANTUM COMPUTATION.
Reliability: Theory & Applications. 2025, June
2(84): 324-331, DOI: https://doi.org/10.24412/1932-2321-2025-284-324-331.
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HIDDEN MARKOV MODELS
FOR ESTIMATING IMPORT DYNAMICS WITH PROBABILITY
DISTRIBUTION ANALYSIS |
332-346 |
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Vyshnavi. M,
Muthukumar. M |
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This article
examines the use of Hidden Markov Models and
probability distributions to study agricultural
import dynamics, with a focus on revealing
hidden patterns in the data. The idea behind the
study is to enhance our understanding of how
transitions between different agricultural
import states occur and to explore the most
suitable probability distributions for modeling
these hidden states. The purpose of the study is
to identify the optimal distributional fit for
hidden states by evaluating the Transition
Probability Matrix, Emission Probability Matrix,
and Initial Probability Vector (π) for each
state. The research implements the Akaike
Information Criterion and the Bayesian
Information Criterion to select the best-fitting
distribution for each scenario. Furthermore, the
paper focuses on the practical implications of
these discoveries, such as determining the most
likely state sequence using the Viterbi path,
which can help influence decision-making and
forecasting. The analysis is carried out using R
software, which provides information about the
associations between probability distributions,
stationarity tests, and the role of model
selection criteria such as AIC and BIC.
Graphical representations of AIC and BIC values
over several probability distributions, and
additionally a correlation matrix between
selected distributions, help to highlight the
findings. Overall, the paper enhances our
understanding of probability distributions
through HMM frameworks for agricultural import
dynamics, providing recommendations for optimal
model selection in various applications.
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Cite: Vyshnavi. M,
Muthukumar. M HIDDEN MARKOV MODELS FOR
ESTIMATING IMPORT DYNAMICS WITH PROBABILITY
DISTRIBUTION ANALYSIS. Reliability: Theory &
Applications. 2025, June 2(84): 332-346, DOI: https://doi.org/10.24412/1932-2321-2025-284-332-346.
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OPTIMIZED SCHEDULING
FOR THREE-STAGE FLOW SHOP WITH PARALLEL MACHINES:
APPLICATION IN WASTE MANAGEMENT AND RECYCLING
FACILITIES |
347-357 |
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Sonia, Pooja kaushik,
Deepak Gupta, Sonia Goel |
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Scheduling is one of
the most important aspects of manufacturing
sectors. Various factors in terms of performance
evaluation, make business more competitive.
Scheduling is the process of allocating scarce
resources to tasks throughout time in order to
accomplish one or more optimization goals. In
fact, the methodical process of organizing,
managing and maximizing work while ensuring the
greatest possible use of both time and resources
is the main aim of scheduling. This paper
indicates the desirable and necessary steps to
discover the optimum solution by efficient
scheduling in waste recycling facilities which
is essential for optimizing resources
utilization and reducing operational delay. In
this study, we have taken three stage flow shop
scheduling with multiple machines at first two
stages and single machine at last stage. This
type of model has a number of applications not
only in several industries but also in saving
natural resources like water, electricity and
reducing waste, idle time and unnecessary energy
consumption. As, this research specially focused
on the scenario of waste management and
recycling facility where incoming waste
undergoes three primary stages sorting, cleaning,
and recycling. Here the scheduling evaluation is
done by comparing the Branch and Bound method
with Palmer’s and Dannenbring method to
determine an optimal job sequence that minimize
the total processing time. The processing time
is represented as a trapezoidal fuzzy number
making an impact. The goal of this activity is
to determine the optimal job plan in order to
reduce the total amount of time that has
processed and allocate the lead in the best
feasible way to reduce the machine idle time,
minimizes the water usage and energy consumption.
This comparison demonstrated how well our
suggested approach handled this challenging
scheduling issue the findings contribute to the
efficient management of recycling facilities,
ensuring improved throughput. Because better
scheduling strategies must be implemented in
order to the growing demand for waste processing
and recycling. So, the proposed approach aids in
streamlining waste management processes,
ultimately supporting environmental conservation
efforts. Here, Branch and Bound is the best
approach as compared to Palmer and Dannenbring
approach. Future work can be extending this
methodology to the three-phase flow shop
scheduling with parallel machines at all the
stages.
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Cite: Sonia, Pooja
kaushik, Deepak Gupta, Sonia Goel OPTIMIZED
SCHEDULING FOR THREE-STAGE FLOW SHOP WITH
PARALLEL MACHINES: APPLICATION IN WASTE
MANAGEMENT AND RECYCLING FACILITIES. Reliability:
Theory & Applications. 2025, June 2(84):
347-357, DOI: https://doi.org/10.24412/1932-2321-2025-284-347-357.
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RELIABILITY MEASURES
AND CLASSICAL AND BAYESIAN PARAMETRIZATION OF
TWO NON-IDENTICAL UNITS SYSTEM MODEL WITH
ON-LINE/OFF-LINE REPAIRS OF REPAIR MACHINE |
358-371 |
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Poonam Sharma, Pawan
Kumar, Shallu Sharma |
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The present paper
deals with the reliability analysis of a system
model which consists of two non identical units
and a repair machine. One of the units
initially, is in operative mode and other is
kept in standby mode. Repair machine is
initially in good condition, it may fails while
repairing the failed units. In case of failure
of repair machine, firstly it undergoes on-line
repair and then to off-line repair if not
repaired online. The failure time distributions
of both the units and repair machine are assumed
to be exponential while the repair time
distributions are taken as general. By using
regenerative point techniques, various measures
of system effectiveness such as transition
probabilities, MTSE, reliability, availability,
busy period etc. have been obtained. Also, some
of them have been studied graphically. A
simulation study is also carried out to analyse
the considered system model both in Classical
and Bayesian setups. From the graphs and tables,
various important conclusions are drawn.
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Cite: Poonam Sharma,
Pawan Kumar, Shallu Sharma RELIABILITY MEASURES
AND CLASSICAL AND BAYESIAN PARAMETRIZATION OF
TWO NON-IDENTICAL UNITS SYSTEM MODEL WITH
ON-LINE/OFF-LINE REPAIRS OF REPAIR MACHINE.
Reliability: Theory & Applications. 2025, June
2(84): 358-371, DOI: https://doi.org/10.24412/1932-2321-2025-284-358-371.
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DEVELOPMENT OF AN
ATTRIBUTE CONTROL CHART BASED ON THE INVERSE
KUMARASWAMY DISTRIBUTION |
372-381 |
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Nagaraju, R.,
Palanivel, M., Sriramachandran, G. V. |
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This article
presents the development of an attribute control
chart designed for products with lifespans
following the inverse Kumaraswamy distribution,
using the distribution’s mean as the quality
metric. The study assumes one distribution
parameter is known while varying the other to
design the control chart. The chart’s
performance is evaluated using Average Run
Length (ARL), with adjustments to parameter
values determining ARL in out-of-control
conditions. The proposed control chart is
assessed through simulations. A comparative
analysis with other similar charts is conducted
based on ARL values, and the findings are
discussed in detail.
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Cite: Nagaraju, R.,
Palanivel, M., Sriramachandran, G. V.
DEVELOPMENT OF AN ATTRIBUTE CONTROL CHART BASED
ON THE INVERSE KUMARASWAMY DISTRIBUTION.
Reliability: Theory & Applications. 2025, June
2(84): 372-381, DOI: https://doi.org/10.24412/1932-2321-2025-284-372-381.
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ASSESSMENT OF
POSSIBLE SEISMIC HAZARD AND RISK USING THE
EXAMPLE OF ALMATY |
382-393 |
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Gennadii Nigmetov,
Andrey Savinov, Temir Nigmetov, Syrym Gabbasov |
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In January 2024,
residents of Almaty felt the seismic impact of
an earthquake that occurred on the border of
China and Kyrgyzstan. The city was not prepared
for such an event. How could the city residents
prepare for this devastating earthquake? In
order to properly prepare the population for a
destructive earthquake, it is necessary to have
a system for assessing the individual seismic
risk of the city, which uses data for risk
assessment: on predicted possible earthquake
sources (PES) dangerous for the city for the
next 10 years, on the seismic resistance of
buildings and the city’s population. Based on
these data, the possible individual risk for the
city population is assessed. In order to assess
the individual risk as accurately as possible,
in addition to data on the PES and seismic
resistance of buildings, data on the
macroseismic field from the PES forecast are
needed. At present, there are all the necessary
scientific and technical capabilities for
creating monitoring systems for seismic
protection of cities.
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Cite: Gennadii
Nigmetov, Andrey Savinov, Temir Nigmetov, Syrym
Gabbasov ASSESSMENT OF POSSIBLE SEISMIC HAZARD
AND RISK USING THE EXAMPLE OF ALMATY.
Reliability: Theory & Applications. 2025, June
2(84): 382-393, DOI: https://doi.org/10.24412/1932-2321-2025-284-382-393.
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AN
APPLICATIONS-BASED STOCHASTIC MODELING OF
MIXTURE DISTRIBUTION FOR CANCER DATA |
394-407 |
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Pooyitha R and
Pandiyan P |
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This study proposed
a new stochastic model by the mixture of Gamma
and Zeghdoudi distribution (MGZ Distribution).
The Reliability Analysis and statistical
features such as moments, Moment generating
function, order statistics, stochastic ordering,
entropy, and the Maximum Likelihood Estimation
of the model parameters were derived. Two
real-time datasets of cancer patients' survival
times were used to demonstrate the model's
goodness-of-fit using the AIC, BIC, and AICC
model selection methods. The new MGZ model has
been compared with the other classical models
like Exponential, Lindley and Shanker. The
result shows that the proposed model is more
flexible than the other models with the lowest
values of AIC, BIC and AICC.
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Cite: Pooyitha R and
Pandiyan P AN APPLICATIONS-BASED STOCHASTIC
MODELING OF MIXTURE DISTRIBUTION FOR CANCER
DATA. Reliability: Theory & Applications. 2025,
June 2(84): 394-407, DOI: https://doi.org/10.24412/1932-2321-2025-284-394-407.
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HIGH-TEMPERATURE
HEAT-INSULATING MATERIALS: A COMPROMISE BETWEEN
THERMAL CONDUCTIVITY AND RELIABILITY |
408-413 |
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N.M. Piriyeva, R.K.
Karimova, G.K. Abdullayeva |
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This article
examines heat transfer mechanisms in
high-temperature thermal insulation materials,
addressing key operational challenges such as
thermal degradation, mechanical stability, and
chemical resistance. The novelty of the study
lies in an integrated approach that includes
optimizing the micro- and nanostructure to
minimize radiative and conductive heat transfer,
developing advanced multilayer and composite
systems, applying predictive computational
modeling for property assessment, and exploring
self-healing coatings and intelligent materials.
These innovations ensure reduced thermal
conductivity without compromising mechanical
strength, enhance resistance to thermal cycling
and aggressive chemical exposure, and
significantly extend the service life of
insulation systems, making them highly promising
for aerospace, energy, metallurgy, and other
industries requiring reliable thermal
protection. Additionally, the proposed solutions
contribute to increased energy efficiency,
reduced material consumption, and improved
environmental sustainability, paving the way for
next-generation thermal insulation technologies
with broader industrial applicability.
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Cite: N.M. Piriyeva,
R.K. Karimova, G.K. Abdullayeva HIGH-TEMPERATURE
HEAT-INSULATING MATERIALS: A COMPROMISE BETWEEN
THERMAL CONDUCTIVITY AND RELIABILITY .
Reliability: Theory & Applications. 2025, June
2(84): 408-413, DOI: https://doi.org/10.24412/1932-2321-2025-284-408-413.
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EVALUATING MULTI
SERVER QUEUING SYSTEM EFFICIENCY: A COMPARATIVE
STUDY BETWEEN FUZZY QUEUING MODEL AND
INTUITIONISTIC FUZZY QUEUING MODEL WITH INFINITE
CAPACITY CONSTRAINTS |
414-428 |
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S. Aarthi |
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In this study, we
suggest an innovative analytical approach
employing triangular fuzzy and triangular
intuitionistic fuzzy numbers to ascertain the
membership functions governing significant
service-execution proportions within multiserver
queuing models. Departing from conventional
methodologies, both the inter-entry and
completion rates are characterized by fuzzy
natures, introducing a novel dimension to the
analysis. Through numerical validation, our
model demonstrates viability in the multiserver
queuing context, bolstering its credibility.
Furthermore, we conduct a contextual
investigation, juxtaposing individual fuzzy
metrics, thereby revealing the superior
categorization potential of intuitionistic fuzzy
queuing models over their fuzzy counterparts.
Expanding the horizons of traditional fuzzy
queuing theory, our integration of
intuitionistic fuzzy environments promises
enhanced queuing model implementation efficacy.
Our primary objective lies in evaluating the
productivity of a multi-server queuing model
with limitless capacity, leveraging both fuzzy
queuing and intuitionistic fuzzy queuing
theories. Embracing a framework where arrival
and service rates are characterized by
triangular and intuitionistic triangular fuzzy
numbers, we undertake a thorough assessment to
establish evaluation criteria, adhering to a
design protocol that preserves fuzzy values
without converting them into crisp values.
Additionally, we address two statistical
challenges to ascertain the method's validity.
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Cite: S. Aarthi
EVALUATING MULTI SERVER QUEUING SYSTEM
EFFICIENCY: A COMPARATIVE STUDY BETWEEN FUZZY
QUEUING MODEL AND INTUITIONISTIC FUZZY QUEUING
MODEL WITH INFINITE CAPACITY CONSTRAINTS.
Reliability: Theory & Applications. 2025, June
2(84): 414-428, DOI: https://doi.org/10.24412/1932-2321-2025-284-414-428.
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FORECASTING
VOLATILITY IN INDIAN NATIONAL STOCK EXCHANGE
USING A MARKOV SWITCHING GARCH MODEL |
429-446 |
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D. Pachiyappan, S.
Jayabharathi, Y. Geeyha Evanjalin, S. Kavitha |
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This paper analyzes
various GARCH models in terms of their
effectiveness in predicting volatility in the
national Stock Exchange (NSE). This paper
examines GARCH models that feature both Gaussian
and fat-tailed residual conditional
distributions, and evaluates their ability to
characterize and predict volatility over time
horizons ranging from 1 to 22 days. The
AR(2)-MR-SGARCH-GED model demonstrates superior
performance compared to other models at a
one-day horizon. The AR(2)-MR-SGARCH-GED and
AR(2)-MRSGARCH+ models surpass other models at
the 5-day horizon. Within a ten-day timeframe,
three AR(2)-MR-SGARCH models surpass the
performance of alternative models. Regarding the
22-day forecast horizon, the results demonstrate
no distinctions between MR-SGARCH models and
standard GARCH models. When looking at risk
management outside of samples (95% VaR), a
number of models seem to give accurate and
reasonable VaR estimates for a one-day period,
with a coverage rate close to the nominal level.
According to the risk management loss functions,
no model is universally the most accurate. This
variability suggests that model performance is
context-dependent, influenced by the specific
characteristics of the data and the underlying
assumptions of each approach. Therefore,
practitioners should consider employing a
combination of models to enhance robustness in
their risk assessments and decision-making
processes.
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Cite: D. Pachiyappan,
S. Jayabharathi, Y. Geeyha Evanjalin, S. Kavitha
FORECASTING VOLATILITY IN INDIAN NATIONAL STOCK
EXCHANGE USING A MARKOV SWITCHING GARCH MODEL.
Reliability: Theory & Applications. 2025, June
2(84): 429-446, DOI: https://doi.org/10.24412/1932-2321-2025-284-429-446.
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MULTI REFERENCE
SKIP-LOT SAMPLING PLAN: A NOVEL APPROACH FOR
QUALITY CONTROL |
447-455 |
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Meby Joseph Manoj,
Azarudheen S |
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Skip-lot sampling
plans have become significant in modern quality
control due to rising production volumes and the
demand for cost-effective inspection methods
that will yield high-quality outputs. When
inspecting a submitted lot, a skip-lot plan is
economically favourable and guarantees high
quality. Thus, this approach benefits both
producers and consumers. The skip-lot sampling
plan generally utilizes the same sampling plan
as the reference plans for both skipping and
normal inspection. However, using the same plan
in both phase favours either the producer or the
consumer in the most essential situations. This
article introduces a novel approach, the Multi
Reference Skip-Lot Sampling Plan with the
provision of having two different reference
plans in the normal and skipping phases of the
skip-lot plan. The paper explores the efficacy
of this approach by deriving performance
measures using a power series approach. To
evaluate the proposed plan, a comparison is made
with existing skip-lot sampling plans that use
single sampling plans or double sampling plans
as reference plans. This comparison is based on
operational characteristics and average sample
number values, accompanied by graphical
representations. The comparative analysis
demonstrates that the new plan effectively
balances the satisfaction of both producers and
consumers. Additionally, the study offers a
strategy for selecting the plan parameters using
the unity value approach, supported by a table
providing unity values.
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Cite: Meby Joseph
Manoj, Azarudheen S MULTI REFERENCE SKIP-LOT
SAMPLING PLAN: A NOVEL APPROACH FOR QUALITY
CONTROL. Reliability: Theory & Applications.
2025, June 2(84): 447-455, DOI: https://doi.org/10.24412/1932-2321-2025-284-447-455.
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MARSHALL - OLKIN TWO
PARAMETER SUJATHA DISTRIBUTION AND ITS
APPLICATIONS |
456-465 |
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V. Sreejith, Ajitha
Sasi, B. Vineshkumar |
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Sujatha
distribution, often discussed in the context of
reliability engineering and survival analysis,
is a probability distribution that is useful for
modeling lifetimes of objects and systems. In
this paper, we introduce a three parameter
distribution called the Marshall - Olkin two
parameter Sujatha distribution. Marshall - Olkin
generalization is a novel method of enlarging a
known family of distributions. It leads to a
rich class of distributions that can capture
different shapes and behaviours and thus allows
for better fitting to empirical data, thereby
establishing its importance in reliability
engineering. We derive many useful statistical
properties such as the hazard rate function,
reverse hazard rate function, order statistics,
moments, measure of skewness and measure of
kurtosis of the Marshall - Olkin two parameter
Sujatha distribution. The stress - strength
reliability of this distribution has also been
derived. The application of this new
distribution is established using real life data
sets. We also compare the performance of this
distribution with that of some existing
distributions.
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Cite: V. Sreejith,
Ajitha Sasi, B. Vineshkumar MARSHALL - OLKIN TWO
PARAMETER SUJATHA DISTRIBUTION AND ITS
APPLICATIONS. Reliability: Theory &
Applications. 2025, June 2(84): 456-465, DOI: https://doi.org/10.24412/1932-2321-2025-284-456-465.
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A NEW GENERALIZATION
OF PARETO DISTRIBUTION: PROPERTIES AND
APPLICATIONS |
466-478 |
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Tabasum Ahad, S.P.
Ahmad |
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This manuscript
introduces a new extension of the Pareto
distribution using the SMP transformation
technique, known as SMP Pareto distribution (SMPP).
The SMP technique is named after (Shamshad,
Murtiza, Parvaiz) who pioneered this approach to
enhance the flexibility and applicability of
statistical models. This new distribution
provides a better fit for data than many
existing models. The shapes of the density
function exhibit great flexibility. It can
support different hazard shapes, such as
increasing, decreasing and constant shapes.
Various statistical properties of the proposed
distribution such as moments, quantile function,
entropy and order statistics were presented. The
maximum likelihood technique is used to estimate
the model parameters. An extensive simulation
study is carried out to illustrate the behavior
of MLEs. In addition, two real-world datasets
are analyzed to showcase the applicability of
the proposed approach. The results indicate that
the SMP Pareto distribution (SMPP) is more
flexible and offers a superior fit for
describing data compared to several existing
forms of the Pareto distribution.
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Cite: Tabasum Ahad,
S.P. Ahmad A NEW GENERALIZATION OF PARETO
DISTRIBUTION: PROPERTIES AND APPLICATIONS .
Reliability: Theory & Applications. 2025, June
2(84): 466-478, DOI: https://doi.org/10.24412/1932-2321-2025-284-466-478.
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FUZZY DATA-DRIVEN
ESTIMATION FOR DUAL WEIBULL POPULATIONS: EM AND
BAYESIAN METHODS WITH GIBBS SAMPLING |
479-492 |
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Abbarapu Ashok and
Nadiminti Nagamani |
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In statistical
analysis, accurately estimating parameters in
the presence of uncertain and imprecise data is
critical, particularly when dealing with
complex, dual population models. Fuzzy data,
which effectively represents real-world
ambiguity, provides a framework for handling
such uncertainties. While parameter estimation
for single-population models with fuzzy data has
been explored extensively, extending these
methods to dual populations remains challenging.
This study addresses this gap by developing
estimation techniques for two Weibull
populations that share a common shape parameter
but differ in scale parameters, under fuzzy data
conditions. We employ the
Expectation-Maximization (EM) algorithm for
Maximum Likelihood estimation and a Bayesian
framework with TK approximation for parameter
estimation. To refine our Bayesian estimates, we
use Gibbs sampling to compute posterior
densities. Through Monte Carlo simulations, for
generated data as well as for a real dataset, we
evaluate the accuracy and robustness of the
proposed estimators, demonstrating their
practical utility in applications where data
imprecision is a significant factor. This
research highlights the importance of robust
methodologies for dual-population Weibull
models, contributing to enhanced reliability in
statistical analysis across diverse fields.
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Cite: Abbarapu Ashok
and Nadiminti Nagamani FUZZY DATA-DRIVEN
ESTIMATION FOR DUAL WEIBULL POPULATIONS: EM AND
BAYESIAN METHODS WITH GIBBS SAMPLING .
Reliability: Theory & Applications. 2025, June
2(84): 479-492, DOI: https://doi.org/10.24412/1932-2321-2025-284-479-492.
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ACCELERATED FAILURE
TIME MODELING FOR PROGNOSTIC FACTORS IN MALE
DIABETES PATIENTS: A COMPARATIVE ANALYSIS OF
SURVIVAL MODELS |
493-502 |
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Jeslin J, Radhika A,
Haripriya M |
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Accelerated Failure
Time Models (AFTMs) are utilized to examine
survival patterns, particularly in the context
of diseases such as diabetes, where traditional
models like Cox proportional hazards may not
apply. In this study, we apply AFTMs to identify
significant prognostic factors affecting
survival in male diabetic patients, using
parametric distributions such as Exponential,
Weibull, Log-normal, and Log-logistic. The
primary objective of this study is to gain
deeper insights into how key covariates
influence survival times and enhance risk
stratification, ultimately leading to better
treatment outcomes. We evaluated the fit of
several AFTMs by comparing Log-Likelihood,
Akaike Information Criterion (AIC), and Bayesian
Information Criterion (BIC) values. Among the
models tested, the Weibull AFTM emerged as the
best fit, demonstrating superior Log-Likelihood
and lower AIC and BIC values compared to other
distributions. The study identified several
significant predictors of survival in male
diabetic patients, including age, family history
of diabetes, duration of diabetes, early use of
insulin (within one year of diagnosis),
retinopathy, use of diuretics, proteinuria,
hypertension, and fasting plasma glucose levels.
All of these covariates were found to
significantly influence survival outcomes
(\(P<0.05\)), with older age and longer diabetes
duration correlating with poorer survival rates.
These findings underscore the importance of
using AFTMs to model survival patterns in
diabetic patients and the potential for targeted
interventions based on identified risk factors.
While the small sample size limits the
generalizability of the results, this study
provides valuable insights into the survival
characteristics of male diabetic patients and
highlights the need for further research with
larger datasets. Future studies should consider
a wider range of covariates and explore the
application of AFTMs in broader diabetic
populations to refine survival prediction models
and optimize patient care. Additionally,
integrating machine learning techniques with
AFTMs could enhance predictive accuracy and
provide a more comprehensive understanding of
survival trends in diabetic patients.
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Cite: Jeslin J,
Radhika A, Haripriya M ACCELERATED FAILURE
TIME MODELING FOR PROGNOSTIC FACTORS IN MALE
DIABETES PATIENTS: A COMPARATIVE ANALYSIS OF
SURVIVAL MODELS . Reliability: Theory &
Applications. 2025, June 2(84): 493-502, DOI: https://doi.org/10.24412/1932-2321-2025-284-493-502.
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PERFORMANCE
EVALUATION AND OPTIMIZATION OF CRYSTALLIZATION
AND SUGAR HANDLING SUBSYSTEMS IN SUGAR MILL
PLANT USING PSO |
503-517 |
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Sandeep Kumar, Vikas
Modgil |
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An appropriate
maintenance strategy is necessary for sugar mill
plants and particularly focuses on the core
processing system. This research creates an
availability-based simulation model for a sugar
mill with 25,500 tons sugarcane crushing
capacity. A Markov performance evaluation
approach is used, and differential equations
generated from a transition diagram covering
fully operational, partially operational, and
failure modes are included. Among the major
processing units, the Evaporator is identified
as a core processing component, being directly
involved in sugar concentration. In contrast,
the Rotary Dryer and the Centrifugal Machine
(Batch or Continuous Centrifuge) are classified
as auxiliary units. These support the production
process by reducing moisture content and
separating sugar from molasses, respectively,
without altering the sugar chemically. The
Crystallizer (e.g., A-Pan Crystallizer) is also
a core processing component, directly
responsible for crystal formation. PSO is used
to improve performance by optimizing the failure
and repair rates and enhancing the performance
metrics. Experimental results showed the system
achieved 88.84% availability. These results
allow maintenance strategies that focus on the
most critical subsystems to be processing
developed. A case for focused maintenance is
made based on the evidence provided for more
effective scheduling, ultimately improving
system performance.
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Cite: Sandeep Kumar,
Vikas Modgil PERFORMANCE
EVALUATION AND OPTIMIZATION OF CRYSTALLIZATION
AND SUGAR HANDLING SUBSYSTEMS IN SUGAR MILL
PLANT USING PSO. Reliability: Theory &
Applications. 2025, June 2(84): 503-517, DOI: https://doi.org/10.24412/1932-2321-2025-284-503-517.
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ASSESSING THE
PREDICTIVE RESILIENCE OF COMPOSITE EXPERIMENTAL
DESIGNS UNDER MISSING OBSERVATIONS: THE
INFLUENCE OF A ALPHA VALUE VARIATIONS |
518-534 |
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A.R. Gokul and M.
Pachamuthu |
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Withdrawal |
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FIXED POINT THEOREMS
FOR SEQUENCE OF MAPPINGS IN TRICOMPLEX VALUED
METRIC SPACE |
535-546 |
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Shivani Chourasiya,
Kavita Shrivastava |
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|
Fixed point theory
plays a crucial role in mathematical analysis,
with profound applications in differential
equations, optimization, and dynamic systems.
Over the years, researchers have extended
classical fixed point results to more complex
structures, such as tricomplex valued metric
spaces, to address problems in multidimensional
and hypercomplex settings. Despite the growing
interest in tricomplex variable spaces, existing
literature on fixed point theorems within these
frameworks remains limited by various
constraints. The existing literature exhibits
several limitations; therefore, in this article,
we utilize the concepts of continuity and weak
compatibility to establish fixed point results
for a novel class of contraction mappings by
employing a sequence of mappings within a
tricomplex valued metric space. If two mappings
commute at their point of coincidence, they are
said to be weakly compatible. These results not
only deepen the comprehension of fixed point
theory but also open up new possibilities for
its application in more intricate and varied
mathematical contexts. As a result, our research
progresses in the field, providing a solid
foundation for future investigations and
potential uses across multiple scientific and
engineering domains.
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Cite: Shivani
Chourasiya, Kavita Shrivastava FIXED POINT
THEOREMS FOR SEQUENCE OF MAPPINGS IN TRICOMPLEX
VALUED METRIC SPACE. Reliability: Theory &
Applications. 2025, June 2(84): 535-546, DOI: https://doi.org/10.24412/1932-2321-2025-284-535-546.
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DISCOUNT PRICING
POLICY WITH STOCHASTIC DEMAND AND PRESERVATION
TECHNOLOGY FOR DETERIORATING ITEMS |
547-561 |
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|
Ramkrishna Tiwari,
Ram Kumar Tiwari, Lalji Kumar, Pooran Lal
Prajapati, Utram Kumar Khedlekar |
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Managing inventory
for deteriorating items presents significant
challenges, especially in environments where
demand is stochastic and price-sensitive.
Retailers face the dual pressure of minimizing
losses from product deterioration while ensuring
sufficient stock availability to meet customer
demand. Additionally, backlogged shortages, if
not managed strategically, can erode customer
satisfaction and profitability. These
complexities are further compounded by the need
to strike a balance between promotional efforts,
preservation investments, and pricing strategies
to remain competitive in dynamic markets. To
address these challenges, this study develops a
comprehensive mathematical model aimed at
optimizing replenishment strategies for
deteriorating items. The model integrates
preservation technologies and strategic price
discounts to enhance product demand while
accounting for the intricate relationship
between market potential, stock levels,
promotional efforts, and selling prices. The
objective is to determine optimal pricing
policies, order quantities, promotional
expenditures, preservation costs, and schedules
for shortages and replenishment, ultimately
maximizing total profit per unit time. The
findings reveal that total profit per unit time
is concave concerning price, shortage duration,
and inventory holding period. Numerical analyses
demonstrate the efficacy of preservation
technologies in mitigating deterioration rates,
enabling retailers to adopt competitive pricing
and stimulate sales. Additionally, the demand
pattern index is shown to significantly
influence inventory policies, while promotional
campaigns play a critical role in augmenting
product sales. Quantity discounts, tied to
demand and order volumes, are identified as
effective tools for reducing procurement costs
and enhancing retailer profitability. These
insights highlight the strategic importance of
investing in preservation technologies, adopting
dynamic pricing strategies, and implementing
targeted promotional campaigns. Together, these
approaches provide a robust framework for
optimizing inventory management, increasing
sales, and maximizing profitability in highly
competitive markets.
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Cite: Ramkrishna
Tiwari, Ram Kumar Tiwari, Lalji Kumar, Pooran
Lal Prajapati, Utram Kumar Khedlekar DISCOUNT
PRICING POLICY WITH STOCHASTIC DEMAND AND
PRESERVATION TECHNOLOGY FOR DETERIORATING ITEMS.
Reliability: Theory & Applications. 2025, June
2(84): 547-561, DOI: https://doi.org/10.24412/1932-2321-2025-284-547-561.
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CAUSES OF
ELECTROMECHANICAL RESONANCE IN WIND TURBINES AND
METHODS FOR ITS ELIMINATION |
562-569 |
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N.S. Mammadov |
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Electromechanical
resonance in wind turbines is a complex and
multifaceted phenomenon that significantly
affects the performance, service life, and
reliability of wind turbines. This problem is
especially relevant for modern high-power wind
turbines operating under variable loads and high
air turbulence. The article provides a detailed
analysis of the mechanisms of electromechanical
resonance, including the influence of design
parameters, aerodynamic loads, electromagnetic
interactions, and operating conditions. The
physical foundations of resonance phenomena and
their impact on the dynamic behavior of wind
turbines are considered, which allows for a
deeper understanding of the mechanisms of their
occurrence and the development of methods for
their prevention. Particular attention is paid
to modern methods of diagnostics and prediction
of resonance effects. The existing technologies
for suppressing resonance oscillations are
analyzed, such as the use of damping elements,
active vibration dampers, adaptive control
systems, and digital twins, which allow for
real-time prediction and correction of generator
behavior. In addition, the article proposes
innovative engineering solutions aimed at
increasing the stability of wind turbines to
resonance phenomena. These solutions include
optimizing design parameters, selecting new
high-strength and damping materials, and
improving automated control systems. Research
into this problem and developing effective
measures to eliminate it are key aspects of
further development of wind energy, allowing for
an increase in the service life of equipment,
its reliability, and a reduction in operating
costs.
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Cite: N.S. Mammadov
CAUSES OF ELECTROMECHANICAL RESONANCE IN WIND
TURBINES AND METHODS FOR ITS ELIMINATION.
Reliability: Theory & Applications. 2025, June
2(84): 562-569, DOI: https://doi.org/10.24412/1932-2321-2025-284-562-569.
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MINIMIZATION OF
ACTIVE POWER LOSSES IN ALTERNATING CURRENT
MAGNETIC SYSTEMS |
570-576 |
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G.V. Mamedova |
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In magnetic systems
of electromagnetic alternating current devices,
active power losses occur in steel and copper,
reducing which is an urgent task. In order to
minimize the loss of active power, a method
based on the geometric optimization of the
magnetic system has been developed. The
optimization criteria are the coefficients of
the proportionality principle. The last
requirement is necessary for the proper
coordination of the designed device with other
mechanisms and for improving the technical and
economic performance of the devices. One of the
proportionality principles for electromagnetic
devices is the construction of designs with a
given coefficient \( n_0 = h\omega_{co} \),
where \( h\omega_{co} \) and are the height and
thickness of the winding, respectively, as the
overall dimensions of the device are mainly
determined by these parameters. As a rule, the
value of the coefficient \( n_0 \) can be
ensured after the preliminary calculation of the
magnetic circuit. On the other hand, there are
complex interrelations between the coefficient
\( n_0 \) and the temperature rise of the
winding. Excessive increase or decrease of the
coefficient \( n_0 \) disrupts this principle,
reduces the current density in the winding,
increases the cross-section of the material and
the winding capacity, and fails to achieve the
specified temperature rise of the winding, etc.
In this case, the main task of optimizing the
winding dimensions is to ensure the maximum
current density in the winding while maintaining
the given coefficient \( n_0 \), temperature
rise, and the ampere-turn values obtained from
the preliminary calculation. In this study, for
the most common electromagnetic design,
considering the given ratios of winding height
to its thickness, temperature rise, and
ampere-turns, the optimal parameters and
dimensions of the magnetic system have been
determined. Loss minimization has been carried
out for electromagnetic devices with voltage
winding and current winding.
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Cite: G.V. Mamedova
MINIMIZATION OF ACTIVE POWER LOSSES IN
ALTERNATING CURRENT MAGNETIC SYSTEMS .
Reliability: Theory & Applications. 2025, June
2(84): 570-576, DOI: https://doi.org/10.24412/1932-2321-2025-284-570-576.
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STEADY STATE
ANALYSIS OF BULK ARRIVAL, FIXED BATCH SERVICE
QUEUE WITH INSPECTION, REWORK AND MULTIPLE
VACATIONS |
577-589 |
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S. Karpagam, R.
Lokesh |
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A non-Markovian bulk
queueing system receives bulk arrivals through a
single server that handles fixed-size batch
services. The server conducts quality checks
after each service to identify defective items,
which are then sent to rework for quality
control purposes. The server takes random-length
vacations until new arrivals reach the threshold
"K" before returning to service. Through the
supplementary variable technique, the key
performance metrics are computed together with
steady-state governing equations. Using
graphical representations and numerical tables,
the model demonstration shows essential
information about system performance through
calculated data.
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Cite: S. Karpagam,
R. Lokesh STEADY STATE ANALYSIS OF BULK
ARRIVAL, FIXED BATCH SERVICE QUEUE WITH
INSPECTION, REWORK AND MULTIPLE VACATIONS.
Reliability: Theory & Applications. 2025, June
2(84): 577-589, DOI: https://doi.org/10.24412/1932-2321-2025-284-577-589.
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ANALYSIS OF THE
PERFORMANCE ON SINGLE SERVER BATCH SERVICE
MULTIPLE WORKING VACATION QUEUING MODEL WITH
COMPULSORY AND EXTENDED REPAIR |
590-604 |
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Lidiya P, K Julia
Rose Mary |
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In this paper, the
concept of single-server multiple-working
vacations queuing model with compulsory and
extended repair is analyzed. In this model,
customers arrive at a service facility and form
a queue to be served by a single server. The
arrival follows the Poisson distribution, and
the service follows the exponential
distribution. Batches of customers are served
under the General Bulk Service Rule. In GBSR,
rather than the individual customer arriving in
a queue one by one, the customers arrive in
groups or batches. Thus, each batch of services
contains a minimum of 'a' units and a maximum of
'b' units of customers. In this study, two types
of repairs, that is, compulsory and extended
repair, are considered. The steady-state
equation, the performance of measures for the
system, and particular cases of described model
are derived. Finally, in the form of tables and
graphs, numerical results have been analyzed.
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Cite: Lidiya P, K
Julia Rose Mary ANALYSIS OF THE PERFORMANCE ON
SINGLE SERVER BATCH SERVICE MULTIPLE WORKING
VACATION QUEUING MODEL WITH COMPULSORY AND
EXTENDED REPAIR. Reliability: Theory &
Applications. 2025, June 2(84): 590-604, DOI: https://doi.org/10.24412/1932-2321-2025-284-590-604.
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A NEW EXTENSION OF
TWO PARAMETER ARADHANA DISTRIBUTION WITH
COMPREHENSIVE STATISTICAL PROPERTIES AND
APPLICATIONS |
605-616 |
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Rashid A. Ganaie,
Manzoor A. Khanday, Prem Lata Gautam, R.
Shenbagaraja, T. Vivekanandan |
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In this study, we
introduce a modified extension of standard two
parameter Aradhana distribution called as the
length biased two parameter Aradhana
distribution. The length-biased distributions
are a subclass of weighted distributions that
adjust the probabilities based on lengths or
sizes of observed phenomena, making them
suitable for modelling certain practical
scenarios. The length biased version is
identified as a specific instance of a broader
category of weighted distributions, which are
widely used in statistical modelling when data
collection mechanisms introduce some inherent
bias. The distribution is thoroughly examined
and analyzed with new structural properties and
parameter estimation is performed using a robust
and widely used technique of maximum likelihood
estimation. The distribution's superiority and
effectiveness are evaluated through a
comparative analysis involving two real-world
datasets. These datasets are used to highlight
the practical applicability of the new
distribution, demonstrate its flexibility and
ability to fit real-world data better than
existing models. This comprehensive approach
highlights both theoretical advancements and
real-world relevance, emphasizing the
distribution's versatility and utility.
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Cite: Rashid A.
Ganaie, Manzoor A. Khanday, Prem Lata Gautam, R.
Shenbagaraja, T. Vivekanandan A NEW EXTENSION OF
TWO PARAMETER ARADHANA DISTRIBUTION WITH
COMPREHENSIVE STATISTICAL PROPERTIES AND
APPLICATIONS. Reliability: Theory &
Applications. 2025, June 2(84): 605-616, DOI: https://doi.org/10.24412/1932-2321-2025-284-605-616.
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LAKIBUL - G FAMILY
OF DISTRIBUTIONS: SPECIAL MODELS, PROPERTIES AND
APPLICATIONS |
617-631 |
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Iozhar A. Lakibul |
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In this study, a new
generated family of distributions is introduced,
called the Lakhul - G Family of Distributions.
The T-X family of distributions is used in the
derivation of the proposed class. Three special
models of the proposed family are derived, such
as the Lakhul - Uniform, Lakhul-Kumaraswamy, and
Lakhul-Rayleigh distributions. Some properties
of the proposed special models such as moments,
mean, variance, moment generating function,
survival, and hazard functions are studied. The
Maximum likelihood approach is used to estimate
the parameters of proposed models. Results show
the following: (i) for Lakhul-Uniform
distribution, it is found that this proposed
probability distribution produces better
estimate for electronic dataset as compared with
the Cubic Transmuted Uniform distribution; (ii)
for Lakhul - Kumaraswamy distribution is found
to give a good fit for the COVID-19 dataset
compared with the Marshall-Olkin reduce Kies and
the Transmuted Kumaraswamy distributions; and
(iii) for the Lakhul - Rayleigh distribution, it
is observed that this distribution provides a
better fit for precipitation dataset as compared
with the Exponentialed Transform Inverse
Rayleigh and the Exponentialed Inverse Rayleigh
distributions.
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Cite: Iozhar A.
Lakibul LAKIBUL - G FAMILY OF DISTRIBUTIONS:
SPECIAL MODELS, PROPERTIES AND APPLICATIONS.
Reliability: Theory & Applications. 2025, June
2(84): 617-631, DOI: https://doi.org/10.24412/1932-2321-2025-284-617-631.
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MULTIVARIATE
IMPUTATION BY MAHALANOBIS DISTANCE OPTIMIZATION
(MIMDO) |
632-641 |
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Geoverr John D.
Labita, Altea S. Labita, Bernadette F. Tubo |
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This paper
introduces a new method for missing data
imputation based on an optimization approach and
is now available as an R package called "mimdo".
This method deals with imputing the missing
values by computing the values that minimize the
Mahalanobis distance between an observation and
the overall mean. The effectivity of mimdo was
demonstrated in both classification and
regression tasks using popular benchmark
datasets. From all experiments, it was found out
that using mimdo for imputing the missing values
in the dataset, on the average, the
classification rate is more than 80% and an
R-squared of more than 50%. Furthermore, the
consistency of the results were validated
through simulation studies.
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Cite: Geoverr John
D. Labita, Altea S. Labita, Bernadette F. Tubo
MULTIVARIATE IMPUTATION BY MAHALANOBIS DISTANCE
OPTIMIZATION (MIMDO). Reliability: Theory &
Applications. 2025, June 2(84): 632-641, DOI: https://doi.org/10.24412/1932-2321-2025-284-632-641.
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ENHANCING PREDICTIVE
ACCURACY WITH ROBUST LIU AND RANDOM FOREST
REGRESSION |
642-647 |
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Muthukrishnan.R and
Karthika Ramakrishnan |
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Robust and Random
Forest regression procedures are powerful
machine learning algorithms that enhance
predictive accuracy and handle complex datasets
with diverse characteristics. The Robust Liu
regression algorithm is designed to address the
limitations of conventional regression methods.
The robust Liu regression method is considered
more reliable in the presence of outliers and
multicollinearity. On the other hand, Random
Forest is an ensemble learning method that
constructs multiple decision trees to improve
classification and regression tasks by
aggregating predictions from individual trees,
thereby mitigating overfitting and increasing
robustness to noise. Its ability to capture
nonlinear relationships and handle
high-dimensional data makes it suitable for many
real-world applications. This study compares the
performance of Least Squares, Liu, Robust Liu,
and Random Forest regression methods using
prediction error measures in real and simulated
environments. This synergy offers new
possibilities for researchers to improve
prediction accuracy in the presence of
heterogeneous non-normal, multicollinear data
and outliers.
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Cite:
Muthukrishnan.R and Karthika Ramakrishnan
ENHANCING PREDICTIVE ACCURACY WITH ROBUST LIU
AND RANDOM FOREST REGRESSION . Reliability:
Theory & Applications. 2025, June 2(84):
642-647, DOI: https://doi.org/10.24412/1932-2321-2025-284-642-647.
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ELECTROMECHANICAL
DEVICES WITH LEVITATION ELEMENTS FOR CONTROL OF
NON-ELECTRICAL PARAMETERS |
648-654 |
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G.S. Kerimzade |
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The paper presents a
mathematical model of electromechanical devices
with levitation elements for automatic control
of non-electrical parameters, as well as
calculation stages for any devices. The
mathematical model is based on the equations of
levitation, currents, magnetomotive forces,
overheating temperature of the windings, and
magnetic induction. Numerical values of
dimensionless quantities are determined, which
can be used as reference data in the development
of electromechanical devices with levitation
elements. The functional dependences of
electromagnetic parameters on the control
voltage and stroke of the levitation element are
established, and expressions for calculating the
force of gravity of the levitation element,
lifting force, magnetomotive force and winding
overheating temperature are obtained.
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Cite: G.S. Kerimzade
ELECTROMECHANICAL DEVICES WITH LEVITATION
ELEMENTS FOR CONTROL OF NON-ELECTRICAL
PARAMETERS. Reliability: Theory & Applications.
2025, June 2(84): 648-654, DOI: https://doi.org/10.24412/1932-2321-2025-284-648-654.
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GEOMETRIC
HAZARD-BASED PREVENTIVE MAINTENANCE AND
REPLACEMENT (GHBPMAR) MODEL FOR AGING
MECHANICALLY REPAIRABLE MACHINES |
655-662 |
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Nse Udoh, Iniobong
Uko, Fredrick Ohaegbunem |
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This work aims to
develop a geometric hazard-based preventive
maintenance model to improve the sustainability
of aging mechanically repairable machines
particularly in developing countries. The goal
is to optimize maintenance and replacement
schedules to meet user needs effectively. The
model utilizes a geometric process as a hazard
rate adjustment factor to account for increasing
deterioration rates of machines due to aging and
prolong usage and applies same model to a
cassava grinding machine across three phases of
lifespan: average lifespan, beyond average
lifespan, and beyond initial replacement age.
The Weibull failure distribution is used to
characterize the machine’s increasing failure
rate. The result reveals that the machine’s
operational time decreases following preventive
maintenance, and maintenance costs increase as
the machine progresses through many phases of
its lifespan. This highlights the model’s
effectiveness in managing the cost and timing of
maintenance activities. The model’s
implementation can significantly impact
communities in developing countries by improving
the reliability and lifespan of essential
machinery like cassava grinding machines and
other industrial machines which can lead to
stable local economies. This approach helps in
managing costs and improving the sustainability
of machines, especially in resource-constrained
environments over extended lifespan.
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Cite: Nse Udoh,
Iniobong Uko, Fredrick Ohaegbunem GEOMETRIC
HAZARD-BASED PREVENTIVE MAINTENANCE AND
REPLACEMENT (GHBPMAR) MODEL FOR AGING
MECHANICALLY REPAIRABLE MACHINES . Reliability:
Theory & Applications. 2025, June 2(84):
655-662, DOI: https://doi.org/10.24412/1932-2321-2025-284-655-662.
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MOMENTS OF
GENERALIZED ORDER STATISTICS FROM DOUBLY
TRUNCATED MODIFIED MAKEHAM DISTRIBUTION AND ITS
CHARACTERIZATION |
663-676 |
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Abu Bakar, Zuber
Akhter and Mohd Amir |
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The Makeham
distribution has been extensively used in
modeling actuarial data and helps as a
fundamental life distribution. It describes a
mortality failure law in which the hazard rate
is composed of two components: a non-aging
failure distribution and an aging failure
distribution, the latter characterized by an
exponentially increasing failure rate. The
concept of generalized order statistics (gos),
introduced by Kamps in 1995, provides a unified
model for combining several models of ordered
random variables, including order statistics,
record values, progressive type II
right-censored order statistics and more. The
development of recurrence relations for the
moments of gos is an important field of research
due to the model’s accessibility and
flexibility. These recurrence relations simplify
the computation of higher-order moments and
establish the associations between moments of
different orders. In this article, we have
derived the recurrence relations of gos for
single and product moments from the doubly
truncated modified Makeham distribution and have
also reduced these relations for specific
ordered random schemes, such as order
statistics, k-th record values and sequential
order statistics for selected different values
of parameters. In the final section, we have
presented a characterization theorem based on
the recurrence relations of the moments. This
theorem has identified the doubly truncated
modified Makeham distribution through its moment
structure within the gos framework. This shows
how important these relationships are for
setting this distribution apart from other
probability models.
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Cite: Abu Bakar,
Zuber Akhter and Mohd Amir MOMENTS OF
GENERALIZED ORDER STATISTICS FROM DOUBLY
TRUNCATED MODIFIED MAKEHAM DISTRIBUTION AND ITS
CHARACTERIZATION . Reliability: Theory &
Applications. 2025, June 2(84): 663-676, DOI: https://doi.org/10.24412/1932-2321-2025-284-663-676.
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A COMPREHENSIVE
STUDY OF LIFETIME DISTRIBUTION MODELS FOR AIR
CONDITIONING SYSTEMS USING FAILURE TIME DATA |
677-684 |
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S. Mythily, S.C.
Premila, P. Manigandan, K. Geetha, D.
Pachiyappan and A. Radhika |
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The purpose of this
paper was to fit the model for the air
conditioning system with failure time for the
normal, gamma, and generalized gamma
distributions and to identify the optimal
distribution model for estimating the air
conditioning system failure time. The
performance of the normal, gamma, and
generalized gamma distributions on air
conditioning system failure data was
investigated. To determine the optimal model for
calculating the air conditioning system failure
time, the secondary data was fitted to the
normal, gamma, and generalized gamma
distribution models. To evaluate the models
performance, the Kolmogorov-Smirnov, and Akaike
Information Criterion, were used. The outcomes
of the research indicated that the gamma model
had the lowest AIC and KS values, measuring
359.108 and 0.47624; the generalized gamma model
came in second with AIC and KS values are
359.6058 and 0.32988; and the normal model had
the highest AIC and KS values, measuring
3203.729 and 0.4298, respectively. Results show
that the gamma model has better flexibility in
handling real data over the conventional normal
and generalized gamma distribution.
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Cite: S. Mythily,
S.C. Premila, P. Manigandan, K. Geetha, D.
Pachiyappan and A. Radhika A COMPREHENSIVE STUDY
OF LIFETIME DISTRIBUTION MODELS FOR AIR
CONDITIONING SYSTEMS USING FAILURE TIME DATA.
Reliability: Theory & Applications. 2025, June
2(84): 677-684, DOI: https://doi.org/10.24412/1932-2321-2025-284-677-684.
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RELIABILITY ANALYSIS
OF AAC BLOCK PLANT USING BOOLEAN FUNCTION AND
PATH TRACING METHOD |
685-693 |
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Balram, S.C. Malik,
A.D. Yadav and S. Malik |
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This study offers a
comprehensive reliability analysis of Autoclaved
Aerated Concrete (AAC) block plants, employing
Boolean function technique and path tracing
method. The analysis addresses a non-repairable
system comprising five interconnected subsystems
arranged in series. Utilizing these mathematical
approaches, we derive expressions for
reliability and mean time to system failure (MTSF).
The study meticulously evaluates system
reliability, with a focus on the Weibull
distribution, especially the exponential
distribution case.
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Cite: Balram, S.C.
Malik, A.D. Yadav and S. Malik RELIABILITY
ANALYSIS OF AAC BLOCK PLANT USING BOOLEAN
FUNCTION AND PATH TRACING METHOD . Reliability:
Theory & Applications. 2025, June 2(84):
685-693, DOI: https://doi.org/10.24412/1932-2321-2025-284-685-693.
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RELIABILITY-
AVAILABILITY - MAINTAINABILITY OF A REPAIRABLE
SYSTEM USING MARKOV APPROACH |
694-704 |
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A. D. Yadav, S.C.
Malik, S. Malik and N. Nandal |
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This study presents
a reliability-availability-maintainability (RAM)
analysis of a repairable system consisting of
two non-identical units, where one unit operates
as the main unit while another unit is in cold
standby mode. A Markov approach is applied to
develop the system model and transition
probability equations are derived using the
Chapman-Kolmogorov technique. The system is
deemed to have failed only when both units are
inoperative.
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Cite: A. D. Yadav,
S.C. Malik, S. Malik and N. Nandal
RELIABILITY- AVAILABILITY - MAINTAINABILITY OF A
REPAIRABLE SYSTEM USING MARKOV APPROACH .
Reliability: Theory & Applications. 2025, June
2(84): 694-704, DOI: https://doi.org/10.24412/1932-2321-2025-284-694-704.
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GARCH-MIDAS ANALYSIS
OF INFLATIONS IMPACT ON ASIAN STOCK RETURN
VOLATILITY |
705-714 |
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S. C. Premila, R.
Jeena, D. Pachiyappan, B. Ramesh Kumar and S.
Kavitha |
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This study examines
the impact of inflation on stock return
volatility in five Asian countries using a GARCH-MIDAS
approach with mixed-frequency data (daily stock
returns and monthly inflation). Results reveal
that higher inflation significantly increases
volatility and depresses returns, underscoring
inflation's critical role in shaping market
dynamics.
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Cite: S. C. Premila,
R. Jeena, D. Pachiyappan, B. Ramesh Kumar and S.
Kavitha GARCH-MIDAS ANALYSIS OF INFLATIONS
IMPACT ON ASIAN STOCK RETURN VOLATILITY.
Reliability: Theory & Applications. 2025, June
2(84): 705-714, DOI: https://doi.org/10.24412/1932-2321-2025-284-705-714.
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MATHEMATIC
SIMLUATION OF SR. CONF. SYSTEM UNDER P. AND C.
MAINTENANCE USING PSO |
715-726 |
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Shakuntla Singla,
Diksha Mangla, Shilpa Rani |
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This paper addressed
the performance of a well-maintained two-unit
system by calculating reliability metrics like
the average duration of system failure and the
available time to perform it by counting the
effect of the collapse rate and its separation
facilities. The goal of this paper is to
maximize the overall profit using a nature
inspired optimization tool, particle swarm
optimization by counting the reliability metrics
for the performance of a series framework
subjected to the influence of routine upkeep and
changing of components.
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Cite: Shakuntla
Singla, Diksha Mangla, Shilpa Rani MATHEMATIC
SIMLUATION OF SR. CONF. SYSTEM UNDER P. AND C.
MAINTENANCE USING PSO. Reliability: Theory &
Applications. 2025, June 2(84): 715-726, DOI: https://doi.org/10.24412/1932-2321-2025-284-715-726.
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ATTRIBUTE CONTROL
CHART APPROACH FOR LIFE TESTING USING
EXPONENTIAL-POISSON DISTRIBUTION |
727-735 |
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Gokila B and Sheik
Abdullah A |
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This article
introduces a novel attribute np control chart
for monitoring the median lifetime of products
under a hybrid censoring plan, assuming an
Exponential-Poisson lifetime distribution.
Optimal control chart parameters are derived to
minimize deviations from a target Average Run
Length (ARL) for an in-control process.
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Cite: Gokila B and
Sheik Abdullah A ATTRIBUTE CONTROL CHART
APPROACH FOR LIFE TESTING USING
EXPONENTIAL-POISSON DISTRIBUTION . Reliability:
Theory & Applications. 2025, June 2(84):
727-735, DOI: https://doi.org/10.24412/1932-2321-2025-284-727-735.
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ESTIMATE MISSING
VALUE OF RANDOMIZED BLOCK DESIGN USING VARIABLE
CONTROL CHARTS THROUGH RESPONSE SURFACE
METHODOLOGY |
736-749 |
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Kokkilambigai S and
Pachamuthu M |
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In this paper, we
are introducing the new methods to estimate the
missing value using variable control charts such
as 3-Sigma and 6-Sigma control charts through
Response Surface Methodology (RSM) with the
numerical example. RSM can be used to find
factor systems that produce a desired maximum,
minimum, or optimal response.
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Cite: Kokkilambigai
S and Pachamuthu M ESTIMATE MISSING VALUE OF
RANDOMIZED BLOCK DESIGN USING VARIABLE CONTROL
CHARTS THROUGH RESPONSE SURFACE METHODOLOGY .
Reliability: Theory & Applications. 2025, June
2(84): 736-749, DOI: https://doi.org/10.24412/1932-2321-2025-284-736-749.
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RELIABILITY AND
PROFIT ANALYSIS OF REPAIRABLE EDIBLE OIL PLANT |
750-757 |
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Ashish Kumar, and
Geetanjali Sharma |
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This paper described
the reliability, availability and profit values
of the edible oil plant by using regenerative
point graphical technique. Generally, it
contains four units such that bleacher (B),
deodorizer (D), thermo fluid boiler (C) and
pressured filter (A). The whole refinery plant
work properly when all units work properly.
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Cite: Ashish Kumar,
and Geetanjali Sharma RELIABILITY AND PROFIT
ANALYSIS OF REPAIRABLE EDIBLE OIL PLANT .
Reliability: Theory & Applications. 2025, June
2(84): 750-757, DOI: https://doi.org/10.24412/1932-2321-2025-284-750-757.
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TOUCH AND STEP
VOLTAGE HAZARD ANALYSIS |
758-768 |
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E.S. Safiyev, S.Y.
Shikhaliyeva |
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This article
analyzes the risks associated with electric
shock, specifically focusing on the effects of
touch and step voltage, which can lead to severe
injury or death. The study highlights key
factors influencing shock severity, including
current magnitude, duration, body resistance,
and current path.
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Cite: E.S. Safiyev,
S.Y. Shikhaliyeva TOUCH AND STEP VOLTAGE
HAZARD ANALYSIS . Reliability: Theory &
Applications. 2025, June 2(84): 758-768, DOI: https://doi.org/10.24412/1932-2321-2025-284-758-768.
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RELIABILITY
ESTIMATION AND PARAMETERS FOR THE LIFESPAN
DISTRIBUTION BASED ON FAILURE TIME DATA FOR
ELECTRICAL COMPONENTS |
769-775 |
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K. Geetha, S.N.
Manoharan, A. Radhika, S. Mythily, and P.
Manigandan |
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The objective of the
present study is to analyse the failure times of
electrical components in order to identify the
optimal distribution model for their longevity.
Fifteen components failure data were analysed
using the Weibull, Lognormal, and Exponential
lifespan distribution algorithms.
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Cite: K. Geetha, S.N.
Manoharan, A. Radhika, S. Mythily, and P.
Manigandan RELIABILITY ESTIMATION AND
PARAMETERS FOR THE LIFESPAN DISTRIBUTION BASED
ON FAILURE TIME DATA FOR ELECTRICAL COMPONENTS .
Reliability: Theory & Applications. 2025, June
2(84): 769-775, DOI: https://doi.org/10.24412/1932-2321-2025-284-769-775.
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COMPARATIVE STUDY OF
REPAIRABLE JUICE PLANTS USING RPGT |
776-783 |
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Mohit Yadav, Vandana
Swami, Naveen Kumar, Puneet Garg |
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In this paper,
comparative study of repairable juice plants is
analyzed by using regenerative point graphical
technique. Generally, juice contains calcium,
vitamin, iron, etc. to give the refresh tests.
There are multiple steps to store the juice at
large levels such as storing, grinding,
pasteurization, etc.
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Cite: Mohit Yadav,
Vandana Swami, Naveen Kumar, Puneet Garg
COMPARATIVE STUDY OF REPAIRABLE JUICE PLANTS
USING RPGT . Reliability: Theory & Applications.
2025, June 2(84): 776-783, DOI: https://doi.org/10.24412/1932-2321-2025-284-776-783.
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CLUSTERING ELECTRIC
POWER SYSTEMS INTO ADEQUACY ASSESSMENT AREAS |
784-791 |
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Dmitry Krupenev,
Denis Boyarkin, Nikolay Belyaev |
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The article
discusses the issue of clustering electric power
systems (EPS) into adequacy assessment areas to
form equivalent models (EM) of power systems,
with such models designed to calculate adequacy
metrics. The level of detail of equivalent
models is backed by the consideration of two
properties of power systems being reliability
and economic feasibility.
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Cite: Dmitry
Krupenev, Denis Boyarkin, Nikolay Belyaev
CLUSTERING ELECTRIC POWER SYSTEMS INTO ADEQUACY
ASSESSMENT AREAS. Reliability: Theory &
Applications. 2025, June 2(84): 784-791, DOI: https://doi.org/10.24412/1932-2321-2025-284-784-791.
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ON CHARACTERIZATION
OF 2KTH ORDER WEIGHTED MAXWELL BOLTZMANN
DISTRIBUTION |
792-802 |
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Nuzhat Ahad, S.P.
Ahmad, J.A. Reshi |
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This paper presents
the characterization results of the 2Kth order
weighted Maxwell Boltzmann distribution (KWMBD).
The characterization results are based on the
coefficient of variance, a straightforward
relationship between two truncated moments, the
conditional expectation of a specific function
of the random variable, the hazard function, and
the reverse hazard function.
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Cite: Nuzhat Ahad,
S.P. Ahmad, J.A. Reshi ON CHARACTERIZATION OF
2KTH ORDER WEIGHTED MAXWELL BOLTZMANN
DISTRIBUTION. Reliability: Theory & Applications.
2025, June 2(84): 792-802, DOI: https://doi.org/10.24412/1932-2321-2025-284-792-802.
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CERTAIN STATIONARY
POINT OUTCOMES FOR ASYMPTOTICALLY REGULAR MAPS
IN INTERVAL- VALUED N-FUZZY METRIC SPACE |
803-812 |
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Heera Ahirwar,
Kavita Shrivastava, Harshit Khare |
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In this study, we
introduce interval valued N-fuzzy metric space (IVNFM)
and we verify certain popular fixed point
results on the structure of interval valued
N-fuzzy metric space through asymptotically
regular mappings.
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Cite: Heera Ahirwar,
Kavita Shrivastava, Harshit Khare CERTAIN
STATIONARY POINT OUTCOMES FOR ASYMPTOTICALLY
REGULAR MAPS IN INTERVAL- VALUED N-FUZZY METRIC
SPACE . Reliability: Theory & Applications.
2025, June 2(84): 803-812, DOI: https://doi.org/10.24412/1932-2321-2025-284-803-812.
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OPTIMIZATION OF
PERISHABLE INVENTORY IN TWO-WAREHOUSE SYSTEM
USING GENETIC ALGORITHMS WITH LOG-GAMMA DECAY
AND NONLINEAR DEMAND |
813-823 |
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Garima Sethi, Ajay
Singh Yadav, Chaman Singh |
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This study presents
a detailed inventory framework for managing
perishable products distributed across two
storage facilities: a capacity-constrained,
company-owned primary warehouse and an auxiliary
rented warehouse. The model accounts for
inventory shortages with partial backlogging,
where both the demand rate and backlogging rate
are modeled as generalized exponentially
decreasing functions of time and selling
price.
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Cite: Garima Sethi,
Ajay Singh Yadav, Chaman Singh OPTIMIZATION OF
PERISHABLE INVENTORY IN TWO-WAREHOUSE SYSTEM
USING GENETIC ALGORITHMS WITH LOG-GAMMA DECAY
AND NONLINEAR DEMAND. Reliability: Theory &
Applications. 2025, June 2(84): 813-823, DOI: https://doi.org/10.24412/1932-2321-2025-284-813-823.
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DESIGNING AN
ATTRIBUTE CONTROL CHART BASED ON
EXPONENTIAL-RAYLEIGH DISTRIBUTION UNDER HYBRID
CENSORING |
824-833 |
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T. Kavitha & M.
Gunasekaran |
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In this paper, we
present a new attribute up control chart aimed
at monitoring the median lifetime of products
within a hybrid censoring scheme, based on the
premise that the lifetimes of these products
follow an Exponential-Rayleigh distribution.
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Cite: T. Kavitha &
M. Gunasekaran DESIGNING AN ATTRIBUTE CONTROL
CHART BASED ON EXPONENTIAL-RAYLEIGH DISTRIBUTION
UNDER HYBRID CENSORING. Reliability: Theory &
Applications. 2025, June 2(84): 824-833, DOI: https://doi.org/10.24412/1932-2321-2025-284-824-833.
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A NEW LENGTH BIASED
EXPONENTIAL- EXPONENTIAL DISTRIBUTION AND ITS
APPLICATIONS TO CANCER DATA |
834-843 |
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Latha J, M
Vijayakumar, Shibu D S |
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In this paper we
propose a new length biased form of the
Exponential-Exponential distribution called
Length Biased Exponential-Exponential
distribution (LBEED) and derive its statistical
properties. The statistical properties including
the moments, moment generating function,
characteristic function, reliability functions
and entropy measures are discussed.
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Cite: Latha J, M
Vijayakumar, Shibu D S A NEW LENGTH BIASED
EXPONENTIAL- EXPONENTIAL DISTRIBUTION AND ITS
APPLICATIONS TO CANCER DATA. Reliability: Theory
& Applications. 2025, June 2(84): 834-843, DOI: https://doi.org/10.24412/1932-2321-2025-284-834-843.
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A NEW GENERALIZATION
OF AREA-BIASED XGAMMA DISTRIBUTION WITH
PROPERTIES AND ITS APPLICATION TO CANCER DATA |
844-856 |
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Athira D V, P.
Pandiyan, and D.S. Shibu |
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In this paper, we
proposed a new model, "Area Biased Xgamma
Distribution", a generalization of the Xgamma
distribution. The various distributional
properties survival function, hazard function,
mean residual life, statistical properties,
moments, moment generating function and
characteristic function, Bonferroni and Lorenz
curve, entropy of the new model were studied.
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Cite: Athira D V, P.
Pandiyan, and D.S. Shibu A NEW GENERALIZATION
OF AREA-BIASED XGAMMA DISTRIBUTION WITH
PROPERTIES AND ITS APPLICATION TO CANCER DATA.
Reliability: Theory & Applications. 2025, June
2(84): 844-856, DOI: https://doi.org/10.24412/1932-2321-2025-284-844-856.
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APPLICATION OF
TYPE-2 FUZZY TOPSIS METHOD FOR ESTIMATING
RENEWABLE ENERGY SOURCES |
857-867 |
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Kamala Aliyeva |
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This paper offers
the integration of spectrum selection
optimization algorithms based on the evaluation
of the characteristics of various renewable
energy options using the TOPSIS fuzzy method.
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Cite: Kamala Aliyeva
APPLICATION OF TYPE-2 FUZZY TOPSIS METHOD FOR
ESTIMATING RENEWABLE ENERGY SOURCES.
Reliability: Theory & Applications. 2025, June
2(84): 857-867, DOI: https://doi.org/10.24412/1932-2321-2025-284-857-867.
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A STATISTICAL
ANALYSIS OF VARIANCE FOR ONE- WAY CLASSIFICATION
USING TRAPEZOIDAL FUZZY TECHNIQUES AND RANKING
METHODS |
868-881 |
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Vanitha. R,
Pachamuthu. M, Kirthik Väiramariappan. A,
Kokkilambigai. S and Sona. S |
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This paper presents
a statistical analysis of variance for one-way
classification using trapezoidal fuzzy
techniques and the ranking method, demonstrated
through a numerical example.
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Cite: Vanitha. R,
Pachamuthu. M, Kirthik Väiramariappan. A,
Kokkilambigai. S and Sona. S A STATISTICAL
ANALYSIS OF VARIANCE FOR ONE- WAY CLASSIFICATION
USING TRAPEZOIDAL FUZZY TECHNIQUES AND RANKING
METHODS. Reliability: Theory & Applications.
2025, June 2(84): 868-881, DOI: https://doi.org/10.24412/1932-2321-2025-284-868-881.
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ON A CLASS OF
INDEFINITE KENMOTSU MANIFOLDS ADMITTING
QUARTER-SYMMETRIC METRIC CONNECTION |
882-889 |
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K. L. Sai Prasad, S.
Sunitha Devi |
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In this present
paper, a class of almost contact metric
manifolds equipped with an indefinite metric,
termed indefinite Kenmotsu manifolds (known as,
$\epsilon$-Kenmotsu), is considered that accepts
a connection of quarter-symmetric.
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Cite: K. L. Sai
Prasad, S. Sunitha Devi ON A CLASS OF
INDEFINITE KENMOTSU MANIFOLDS ADMITTING
QUARTER-SYMMETRIC METRIC CONNECTION .
Reliability: Theory & Applications. 2025, June
2(84): 882-889, DOI: https://doi.org/10.24412/1932-2321-2025-284-882-889.
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PROPERTIES AND
APPLICATION OF ALPHA LOGARITHM TRANSFORMED SINE
WEIBULL DISTRIBUTION |
890-902 |
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A.A. Osi, O.O. Ishaq,
B.A. Abdulsalam, Usman Abubakar |
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In this research, we
introduced a new submodel of the alpha logarithm
transform sine-X family of distributions, called
the alpha logarithm transform sine-Weibull. We
derived its statistical properties, including
survival function, hazard function, moments,
moment-generating function, and order
statistics.
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Cite: A.A. Osi, O.O.
Ishaq, B.A. Abdulsalam, Usman Abubakar
PROPERTIES AND APPLICATION OF ALPHA LOGARITHM
TRANSFORMED SINE WEIBULL DISTRIBUTION .
Reliability: Theory & Applications. 2025, June
2(84): 890-902, DOI: https://doi.org/10.24412/1932-2321-2025-284-890-902.
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A BATHTUB ADDITIVE
FAILURE RATE MODEL FOR ACTUARIAL RELIABILITY |
903-917 |
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M. A. Alhassan, A.
Yahaya, O. O. Ishaq, B. Abba, Y. Hussaini, A.
Bello |
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This paper
introduces a lifetime model named Hybrid
Weibull-Exponential Power model, based on the
later phenomenon vis-a-vis the former approach.
The failure rate (FR) of the proposed model
displayed suitable compound trends such as
increasing-decreasing and various complex forms
of bathtub-curve, with and without the lingering
useful life period.
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Cite: M. A. Alhassan,
A. Yahaya, O. O. Ishaq, B. Abba, Y. Hussaini, A.
Bello A BATHTUB ADDITIVE FAILURE RATE MODEL
FOR ACTUARIAL RELIABILITY. Reliability: Theory &
Applications. 2025, June 2(84): 903-917, DOI: https://doi.org/10.24412/1932-2321-2025-284-903-917.
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RESEARCH ON
SIGNATURE RECOGNITION METHOD BASED ON DEEP
LEARNING TECHNIQUE IN PYTHON LANGUAGE |
918-928 |
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Phuc Hau Nguyen |
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This paper presents
a comprehensive study on the construction of a
signature recognition system using deep learning
with Python. We focus on the preprocessing of
signature images, the construction of a CNN
model architecture combined with RNN to exploit
image features and stroke sequences, and the
performance comparison between models.
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Cite: Phuc Hau
Nguyen RESEARCH ON SIGNATURE RECOGNITION
METHOD BASED ON DEEP LEARNING TECHNIQUE IN
PYTHON LANGUAGE . Reliability: Theory &
Applications. 2025, June 2(84): 918-928, DOI: https://doi.org/10.24412/1932-2321-2025-284-918-928.
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BI STAGE FSSP WITH
TRIANGULAR INTUITIONISTIC FUZZY NUMBER AND
COMPARISON BETWEEN HEURISTICS |
929-943 |
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Pooja Kaushik, Sonia,
Deepak Gupta, Sonia Goel |
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This study explores
a two-stage FSSP, where parallel machines
execute jobs in the both stages. The processing
times in the flow shop scheduling are
represented by fuzzy numbers in this work. This
paper gives comparative study to address the
FSSP under an uncertain environment based on
triangular intuitionistic fuzzy numbers (T+IFNs).
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Cite: Pooja Kaushik,
Sonia, Deepak Gupta, Sonia Goel BI STAGE FSSP
WITH TRIANGULAR INTUITIONISTIC FUZZY NUMBER AND
COMPARISON BETWEEN HEURISTICS. Reliability:
Theory & Applications. 2025, June 2(84):
929-943, DOI: https://doi.org/10.24412/1932-2321-2025-284-929-943.
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A NEW DISCRETE
ENTROPIC MODEL AND ITS APPLICATION TO
CONTINGENCY TABLE INFERENCE |
944-956 |
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Poonam Kumari, Nishi
Kumari |
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This paper
introduces a novel discrete information entropic
model and explores its applications in
statistical analysis. We have demonstrated the
efficacy of this new model by applying it to the
inference of contingency tables, a cornerstone
of statistical analysis.
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Cite: Poonam Kumari,
Nishi Kumari A NEW DISCRETE ENTROPIC MODEL AND
ITS APPLICATION TO CONTINGENCY TABLE INFERENCE.
Reliability: Theory & Applications. 2025, June
2(84): 944-956, DOI: https://doi.org/10.24412/1932-2321-2025-284-944-956.
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