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IAPQR Transactions - A UGC-CARE Listed Journal

Published in Association with Indian Association for Productivity, Quality and Reliability

Current Volume: 49 (2024-2025 )

ISSN: 0970-0102

Periodicity: Half-Yearly

Month(s) of Publication: September & March

Subject: Quality Management/Statistics

DOI: 10.32381/IAPQRT

100

Articles in the fields of Quality, Productivity and Reliability are considered for publication in IAPQR Transactions since its initiation in the year 1975. Since then, the journal is being regularly published twice a year. Articles published in this journal are abstracted / reviewed in renowned scientific periodicals like Zentralblatt fur Mathematik, Mathematical Reviews, Statistical Theory and Methods Abstracts, Quality Control and Applied Statistics and some other such publications.The journal has always been a priority to frontline academicians for communicating their research works. To name a few, Jye-Chyi Lu, Benjamin Reiser, David M. Rocke, Unnikrishnan Nair, S. Joseph, Shun-ichi Abe, Barry C. Arnold, J.M.S.E Castillo, Bo Bergman, J. Dahlgaard, W. Kossler and J. H . Sullivan may be cited. The journal also encourages young researchers to publish their research works. University Grants Commission has placed this journal in its approved list of journals.

Articles published in this journal are abstracted / reviewed in renowned scientific periodicals like Zentralblatt fur Mathematik, Mathematical Reviews, Statistical Theory and Methods Abstracts, Quality Control and Applied Statistics and some other such publications.

 

Founder Editor
Prof. S.P. Mukherjee

Former Centenary Professor in Statistics
University of Calcutta, India


Editor
Prof. Bikas K. Sinha

Former Professor,
Indian Statistical Institute, Kolkata, India


Prof. Manisha Pal

Department of Statistics
University of Calcutta, India


Associate Editor
Prof. Asis Kumar Chattopadhyay

Department of Statistics,
University of Calcutta, India


Prof. Debasish Bhattacharya

Department of Agricultural Statistics,
Institute of Agriculture,
Visva Bharati University,
Santiniketan, W.B., India


Prof. P.G. Sankaran

Pro-Vice Chancellor,
Cochin University of Science & Technology, India


Dr. A. Dharmadhikari

Former General Manager,
Tata Motors, Pune, India


Dr. M. Zafar Anis

S.Q.C. & O.R. Unit,

Indian Statistical Institute,

Kolkata, India


Prof. Debasis Kundu

Department of Mathematics and Statistics,
Indian Institute of Technology, Kanpur, India


Prof. Yogendra P. Chaubey

Department of Mathematics and Statistics,

Concordia University,

Canada


Prof. Arnab Laha

Department of Operations Management,
Indian Institute of Management
Ahmedabad, India


Dr. Ashis Kumar Chakraborty

S.Q.C. & O.R. Unit,

Indian Statistical Institute,

Kolkata, India


Dr. Sudipto Pal

R&D, Uber India,
Bangalore, India


Editorial Secretary
Mr. Kuntal Bakuli

Department of Statistics,

Banwarilal Bhalotia College,

Asansol, India


Volume 49 Issue 1 , (Apr- to Sep-2024)

Design of Experiment as a Tool to Improve the Manufacturing Quality: Case Study involving Lubrication Oil Pressure of a Diesel Engine

By: Avinash Dharmadhikari , Prakash Ganesh Mandke

Page No : 1-12

Abstract
This is a story of Y2 K (yr 2000) in Indian industry. An engine manufacturing company faced the problem of low Lubrication Oil Pressure (LOP) of a six-cylinder diesel engine. The engine under study was used for power generation application. In this paper, we describe how planned Design of Experiment (DOE) was used successfully to resolve the issue of low LOP. Planning or designing an experiment is a well-known technique in statistical literature. What is new is a successful application in resolving the low LOP issue. Hence, we thought of reporting the study in the paper. The paper is written in a tutorial format and would be useful in other studies.

Authors :
Avinash Dharmadhikari and Prakash Ganesh Mandke : Pune, Maharashtra, India
 

DOI : https://doi.org/10.32381/IAPQRT.2025.49.01.1

Price: 251

Varentropy Properties of Ranked Set Sample

By: Manoj Chacko , Varghese George

Page No : 13-34

Abstract
It is well known that the amount of information contained in a ranked set sample is larger than that contained in a simple random sample of same size. In this paper, varentropy properties of the ranked set sample are considered. The expression for varentropy of different modifications of ranked set sampling such as median ranked set sampling and moving extreme ranked set sampling are derived. The stochastic comparison of varentropy based on different modifications of ranked set samples are made. The upper bound and recurrence relation for varentropy are also presented. A dispersion index based on Kullback-Leibler divergence using ranked set sample is also discussed.

Authors :
Manoj Chacko : Department of Statistics, University of Kerala, Trivandrum, India 
Varghese George : St. Stephen's College, Pathanapuram, Kerala, India
 

DOI : https://doi.org/10.32381/IAPQRT.2025.49.01.2

Price: 251

Optimum Software Release Time under Cost-Reliability Set-Up using Size-Biased Sampling

By: Ashis Kumar Chakraborty , Anisha Das

Page No : 35-58

Abstract
Prediction of the optimum time for software release has been an exploring research area in recent times. In this article, we propose a new formulation of the software testing problem in discrete set-up using the sizebiased concept and incorporate the Bayesian technique for finding out the optimum testing time through a trade-off between the total cost of testing the software and the attained bug size. We also show how this cost is related with reliability of the software, the reliability so computed being also determined in an easy way of just finding whether a bug is present or not.The model so developed has been tested on a simulated example, as well as verified with an actual commercial software. It is expected that our modeling will work on any software where data have been collected using a discrete framework. We conclude with possible extensions to our work in future.

Authors :
Ashis Kumar Chakraborty : Statistical Quality Control & Operations Research, Indian Statistical Institute, India
Anisha Das : Department of Statistics, Florida State University, USA
 

DOI : https://doi.org/10.32381/IAPQRT.2025.49.01.3

Price: 251

On Analyzing Milkey Way Globular Clusters: Comparing Efficiency of Dimension Reduction Techniques

By: Abisa Sinha Adhikary

Page No : 59-78

Abstract
Astronomical Data specifically those from Globular Clusters and Young Massive Clusters are usually contaminated with outliers and missing data, detection of which might be very tedious in case the data size is considerably large. Moreover, for skewed multivariate data, Principal Component Analysis (PCA) is not an appropriate approach for dimension reduction. The Robust Principal Component Analysis along with the Missing Value Imputation Technique using the MissForest algorithm is applied to a data from the Harris catalogue {Harris 2010} of globular clusters and the results are demonstrated with some striking features of the clusters.
 

Author :
Abisa Sinha Adhikary : Amity University, Kolkata, India
 

DOI : https://doi.org/10.32381/IAPQRT.2025.49.01.4

Price: 251

Improved Synthetic and Improved Group Runs Control Charts to Detect Shifts in the Process Mean

By: M.P. Gadre , S. S. Venegurkar , R.V. Latpate

Page No : 79-99

Abstract
In this article, we have proposed runs rule-based control charts,namely, Improved Synthetic Control Chart’ (ISCC-x̄) and ‘Improved Group Runs Control Chart’(𝐼𝐺𝑅𝐶𝐶 −X̄) to detect shift in the process mean of a univariate production process. In zero state and also in steady state, it is numerically illustrated that 𝐼𝑆𝐶𝐶 −X̄ and 𝐼𝐺𝑅𝐶𝐶 −X̄ perform significantly better as compared to the related charts.

Authors :
M.P. Gadre : Shriram Institute of Information Technology, Paniv
S. S. Venegurkar : Prof. Ramkrishna More Arts Commerce Science College, Akurdi, Dist. Pune
R.V. Latpate : Department of Statistics, SPPU, Pune
 

DOI : https://doi.org/10.32381/IAPQRT.2025.49.01.5

Price: 251

Numerical Simulation of Nonlinear Equations by Modified Secant Method

By: Inderjeet , Rashmi Bhardwaj

Page No : 100-117

Abstract
Nonlinear equations are solved in a wide range of domains, including applied mathematics, computer science, and engineering. Iterative solutions are the only way to solve non-trivial situations of these equations.Thus, the creation of an effective and efficient iterative technique is crucial and can have a good effect on the process of determining the numerical solution of numerous real-world issues. The goal of this study is to create a novel, and effective iterative approach to solving nonlinear equations. The recently designed iterative approach is based on the classical Secant method for resolving nonlinear equations, which are investigated in various scientific and engineering domains. The nonlinear equation root finding approach that has been developed has an order of convergence of 1.84 and requires three beginning points instead of just two. By the use of multiple benchmark problems with varying iterations, the newly created method's convergence was demonstrated and its performance was compared with the traditional Secant method. According to the results, the newly designed method outperformed the conventional Secant method in terms of iterations and order of convergence. This provides support for the recently discovered method's credibility and offers hope for future study that will further perfect it.

Authors :
Inderjeet and Rashmi Bhardwaj : University School of Basic and Applied Sciences, Guru Gobind Singh Indraprastha University, Dwarka, Delhi , India
 

DOI : https://doi.org/10.32381/IAPQRT.2025.49.01.6

Price: 251

Instruction to the Author

Manuscripts should be typewritten in MS WORD using Times New Roman with 1.15 space and 1” margin at the top, sides and bottom. The text and symbols should be in font size 12. Pages should be numbered consecutively, starting with the title page and the matter arranged in the following order: Title, Abstract, Keywords and Phrases, Introduction, and other sections. The headings of the different sections should be written in bold and upper case, using big (font size 14) and small (font size 11) letters. Sections, from Introduction to Acknowledgement, should be serially numbered and centered.

For example, “1. INTRODUCTION”. The References section should be written in the same style, but not numbered. Tables and figures should be serially numbered and given appropriate titles. like, “Table 1: Values of ....”, “Figure 1: Failure rate curve ...”. Subtitles in each section shall be in bold face, sentence case, italics and font size 12, followed by a colon.

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1. Saaty, T.L. (1961): Elements of Queueing Theory and Applications. McGraw-Hill Company, Inc. 2. Mudholkar, G. S., Srivastva, D.K. and Freimer, M. (1995): The exponentiated Weibull family: a reanalysis of the bus- motor-failure data, Technometrics, 37(4), 436-445.

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