IAPQR Transactions

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

Current Volume: 47 (2022-23 )

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 47 Issue 1 -2 , (Apr-2022 to Mar-2023)

Obituary
Prof. Hemshankar Ray by Subrata Ghosh

By: No author

Page No : (i-ii)

Read Now

Whither Statistics?

By: S. P. Mukherjee

Page No : 1-15

Abstract
The present article reflects on a few issues regarding the on-going trend in theory and applications of Statistics. The aspect of applications and the problems with sample surveys in several domains have been emphasized.

Author :
S. P. Mukherjee

Mentor, Indian Association for Productivity, Quality and Reliability.
 

DOI : https://doi.org/10.32381/IAPQRT.2023.47.01-02.1

Price: 251

Use of Ranked Set Sampling in The Estimation of Parameters ?? and ?? of Morgenstern Type Bivariate Exponential Distribution

By: N.K. Sajeev Kumar , Sumi A.R.

Page No : 16-42

Abstract
In this article we have derived the best linear unbiased estimator (BLUE) of the parameters ?2 and ?2 involved in the Morgenstern type bivariate exponential distribution by ranked set sampling (RSS). Also we have evaluated the BLUE's of ?2 and ?2 involved in the Morgenstern type bivariate exponential distribution by concomitants of ranked set sampling for some specific values of the sample size n. The efficiency comparison of the proposed estimators with that of the estimators using concomitants of order statistics and modified ranked set sampling is also made.

Authors : 
N.K. Sajeev Kumar : 
Department of Statistics, University College, Trivandrum, Kerala, India.
Sumi A.R. : Department of Statistics, University College, Trivandrum, Kerala, India.
 

DOI : https://doi.org/10.32381, IAPQRT.2023.47.01-02.2

Price: 251

Weighted Alternated Charting Statistic Control Chart to Monitor the Mean Vector

By: M.P. Gadre

Page No : 43-60

Abstract
In this article, modification of the ‘Alternated Charting Statistic’ (ACS) scheme with the traditional Hotelling c 2 chart to control the mean vector of a bivariate normal process is proposed. With the bivariate ACS scheme in use, the two quality characteristics (X, Y) are controlled in an alternating fashion. The proposed control chart is called as ‘Weighed Alternated Charting Statistic’ (WACS) control chart to monitor the mean vector by using variable inspection. In WACS chart, which one of the two quality characteristic is to be inspected, is explained in detail. While defining the rule of the status of the process, the weights of each of the two quality characteristics are considered. It is numerically illustrated that the WACS chart performs better as compared to the c 2chart and ACS chart.

Author :
M.P. Gadre

Shriram Institute of Information Technology, Solapur, India.
 

DOI : https://doi.org/10.32381/IAPQRT.2023.47.01-02.3

Price: 251

Reliability and Availability Improvement of Raw Material Charging Station in A Steel Industry

By: Subrata Rath , Ashis Kumar Chakraborty , Subhashis Chatterjee

Page No : 61-85

Abstract
Raw Material Charging Station (RMCS) is one of the most important infrastructures in steel industry and is used to load and carry crushed iron ore to furnace. Breakdown behaviour of the RMCS was observed for a certain period, and its future behaviour was predicted using a reliability model. For improvement of availability however, a Six sigma approach was used. Initial focus was to reduce the repair time per month in order to make RMCS more available for use and save the financial loss due to unavailability of the furnaces to produce steel. This study discovers a way to simultaneously improve reliability, reduce repair time and thereby improve availability of the RMCS. The study also generalises an approach for improving reliability and availability for any mechanised repairable system using six sigma methodologies.

Authors :
Subrata Rath
: SQC & OR Unit, Indian Statistical Institute, Pune, India.
Ashis Kumar Chakraborty : SQC & OR Unit, Indian Statistical Institute, Kolkata, India.
Subhashis Chatterjee : Mathematics Department, IIT(ISM) Dhanbad, India.
 

DOI : https://doi.org/10.32381/IAPQRT.2023.47.01-02.4

Price: 251

Inference and Prediction of Order Statistics Based On K-Record Values from A Weibull Distribution

By: Manoj Chacko , Laji Muraleedharan

Page No : 86-102

Abstract
In this paper, the problem of estimation of parameters and prediction of order statistics from a future sample based on upper k-record values arising from a two parameter Weibull distribution is considered. The maximum likelihood estimators and the Bayes estimators are obtained based on observed upper k-record values. Bayesian point predictors of the order statistics from a future sample and its two-sided equi-tailed prediction intervals are also derived. Finally, a numerical illustration is considered for exemplifying the proposed inferential procedures developed in this paper.

Authors :
Laji Muraleedharan and Manoj Chacko

Department of Statistics, University of Kerala, Trivandrum, India.
 

DOI : https://doi.org/10.32381/IAPQRT.2023.47.01-02.5

Price: 251

News Corner : Golden Jubilee Celebration Conference of IAPQR

By: ..

Page No : 103-107

Price: 251

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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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