Apr- to Mar-2023

Obituary
Prof. Hemshankar Ray by Subrata Ghosh

By: No author

Page No : (i-ii)

Price: 251

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

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Use of Ranked Set Sampling in The Estimation of Parameters µ₂ and ó₂ 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

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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

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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

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

By: Laji Muraleedharan , Manoj Chacko

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

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News Corner : Golden Jubilee Celebration Conference of IAPQR

By: ..

Page No : 103-107

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Apr- to Mar-2022

Modeling Time-to-First Peritonitis Episode Using Semiparametric Cox and Parametric AFT Survival Models

By: Yehenew G Kifle , Tshepo F. Maja , Ramon A. Tamayo

Page No : 1-16

Abstract
Peritoneal Dialysis (PD) is a process of replacing kidney function that cleans waste product from the blood and removes extra fluid from the body. In most cases, PD process is slowed down by a peritoneal membrane infection called peritonitis, which is the leading cause of morbidity and dialysis failure among PD patients in developing countries. Early prevention of this infection is very crucial for the success of PD in resource-poor countries. Using a prospective study from Pietersburg provincial hospital in South Africa, we have investigated potential social, demographic, and biological risk factors that contribute to the first episode of peritonitis. Both semiparametric Cox proportional hazards and two parametric Accelerated Failure Time (AFT) survival models were fitted to the data and compared for their performance. Weibull AFT model fits better to the peritonitis longitudinal dataset followed by exponential AFT and Cox PH models. Among PD cohort of patients, 60.38% of peritonitis infections were recorded over the follow-up period with the majority of peritonitis infections are recorded among females (65.4%) and rural dwellers (65.7%) with (62.6%) of black Africans which shows a higher risk of developing peritonitis. Patients with no running water and electricity in the house who are living in rural areas with a low level of hemoglobin and shorter duration on PD are associated with a higher risk (hazard) of developing the first episode of peritonitis infections in the study area.

Authors :
Yehenew G Kifle
Department of Mathematics and Statistics, University of Maryland Baltimore County, USA

Tshepo F. Maja
Department of Statistics and Operations Research, University of Limpopo, South Africa

Ramon A. Tamayo
Pietersburg Limpopo Provincial Hospital, South Africa
 

DOI : DOI-https://doi.org/10.32381/IAPQRT.2022.46.01-02.1

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Towards Understanding Enhancement of Quality and Productivity Aspects of Pregnancy/Birth of Children under Suprajanan Scheme 

By: Avinash Dharmadhikari , Bikas K Sinha

Page No : 17-29

Abstract
The first author was involved in a study with the goal of enhancing the quality and productivity of pregnancy/birth of children under “Suprajanan Scheme”, developed and initiated by Manashakti Research Centre (MRC) at Lonavla, near Mumbai, India in 2010. After implementation of the said scheme and collection of relevant data, the author had access to the data and accordingly, he analysed the same for statistical analysis. In order to derive and apply exact inference theory for meaningful elaborate analysis and valid conclusions, he collaborated with the second author and together, they developed the necessary results. It amounted to the formulation of inference problems involving four parameters p, a, b, c; 0 < p < 1 involved in four independent Bernoulli/Binomial experiments having P(H) = (p, ap, bp, cp); 0 < p, ap, bp, cp < 1 respectively. The applications and conclusions are explained with reference to the contexts.

Authors :
Avinash Dharmadhikari
Pune. India.
 

Bikas K Sinha
Koltata, India

DOI : DOI-https://doi.org/10.32381/IAPQRT.2022.46.01-02.2

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Proportional Cause-Specific Hazards Model for Recurrent Events 

By: P. G. Sankaran , Sisuma M.S.

Page No : 30-52

Abstract
The present paper discusses the modelling and analysis of recurrent event data with competing risks in the presence of covariates. We propose an extension of the proportional cause-specific hazards model based on averaged counting process and averaged at-risk set process of recurrent events. The regression parameters are estimated using a partial likelihood approach. Asymptotic properties of the proposed estimators are established. Simulation procedures are carried out to assess the finite sample properties of the proposed estimators. The proposed method is applied to reallife data.

Authors :
P. G. Sankaran
Department of Statistics, Cochin University of Science and Technology Kerala

Sisuma M.S.
Department of Statistics, Cochin University of Science and Technology Kerala
 

DOI : DOI-https://doi.org/10.32381/IAPQRT.2022.46.01-02.3

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Modified Control Charts with Warning Limits to Detect Shifts in the Process Mean and for Increase in Fraction Nonconforming 

By: R. N. Rattihalli , M. P. Gadre , R. A. Patel

Page No : 53-74

Abstract:
In this article, for univariate processes, we propose improved control charts useful to detect shift in the process mean and to identify increases in the fraction nonconforming. These modified control charts are intended to reduce the out-of-control ‘Average Time to Signal’ (ATS). When the charting statistic is inside the control limits, but close to control limits (between the warning and the control limits), the process may not be operating properly. In such situations, to have substantial/additional information about quality of the process, in this article, we propose ‘Modified Control Chart with Warning Limits’ (MCCWL) to detect shifts in the process mean, increases in fraction nonconforming and to monitor shifts in the mean vector. It is modified in the sense that a rule is defined to stop the sampling and to declare the process as out of control. The corresponding expression for Average Run Length (ARL) is obtained. The design parameters are obtained under ‘Average Time to Signal’ (ATS) criterion. The proposed charts namely, ????? ? ??, ????? ? ??,????? ? ??? are shown to perform better than their competitors considered. Abstract: In this article, for univariate processes, we propose improved control charts useful to detect shift in the process mean and to identify increases in the fraction nonconforming. These modified control charts are intended to reduce the out-of-control ‘Average Time to Signal’ (ATS). When the charting statistic is inside the control limits, but close to control limits (between the warning and the control limits), the process may not be operating properly. In such situations, to have substantial/additional information about quality of the process, in this article, we propose ‘Modified Control Chart with Warning Limits’ (MCCWL) to detect shifts in the process mean, increases in fraction nonconforming and to monitor shifts in the mean vector. It is modified in the sense that a rule is defined to stop the sampling and to declare the process as out of control. The corresponding expression for Average Run Length (ARL) is obtained. The design parameters are obtained under ‘Average Time to Signal’ (ATS) criterion. The proposed charts namely, ????? ? ??, ????? ? ??,????? ? ??? are shown to perform better than their competitors considered.

Authors :
R. N. Rattihalli
Retd. Professor, Shivaji University, Kolhapur

M. P. Gadre
Shriram Institute of Information Technology, Paniv, District Solapur

R. A. Patel
Karnatak University, Dharwad
 

DOI : DOI-https://doi.org/10.32381/IAPQRT.2022.46.01-02.4

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Mining and Matching of Profiles in a Social Network – A Static Measure of Friendship

By: Puspendu Biswas , Aditya Bagchi

Page No : 75-98

Abstract
In the process of preventing possible cyber-crimes through social media, a new research paradigm named Proactive Forensics has evolved. As a part of such research effort, this paper attempts to match profiles of two members in a social network as a measure of compatibility between two persons. Profile matching efforts made so far include; matching job profile with candidate profile to choose “right man for the right job”, matching profiles of same person from two different social nets like Facebook and LinkedIn and to ascertain that they belong to the same person and even matching of two different Genome profiles. However, this paper tries to identify whether a friendship request on a social net can be accepted on the basis of a matching value generated by comparing the features of two profiles. For the purpose of matching, this paper provides two measures of closeness between two profiles; first a measure of the degree of exact match of feature values and secondly a composite distance measure of different feature wise distances. This composite measure has been termed as a static measure of friendship. A modified Jacardian similarity and standard Cosine similarity have been used for final measure of closeness between two profiles. In addition, it has been found that many features, used for matching, give rise to different types of hierarchies. New distance measures have been developed for matching such hierarchic structures. It has also been proved that such new measures are valid distance measures.

Authors :
Puspendu Biswas
Software Development Department, IGT Solutions Pvt. Ltd., Gurgaon

Aditya Bagchi
Computer Science Department, Ramakrishna Mission Vivekananda Educational & Research Institute, Belur Math, Howrah
 

DOI : DOI-https://doi.org/10.32381/IAPQRT.2022.46.01-02.5

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A Hidden Projection Property of the 24-Run Plackett-Burman Design

By: Renu Kaul , Sanjoy Roy Chowdhury

Page No : 99-121

Abstract
In the class of two-level non-regular designs, Plackett-Burman ([14], 1946) designs have a special place. These designs have been widely used as screening designs because of their relative simplicity of use. Wang and Wu ([16],1995) observed that these designs possess certain hidden projection properties which are bestowed by the complexity of their partial aliasing relationships. They attributed the  success of Hamada and Wu’s ([9],1992) strategy for entertaining and estimating twofactor interactions from Plackett-Burman (PB) type designs to the hidden projection property.
In this paper, we have used the hidden projection property of the 24-run PB design to propose an alternative to the design suggested by Mclean and Anderson ([13],1984). The proposed design performs better in terms of increased degrees of freedom efficiency and reduced run size. We have also drawn non-isomorphic interaction graphs making D and Ds efficiency as the underlying criterion.

Authors :
Renu Kaul
Department of Statistics, Lady Shri Ram College for Women (University of Delhi), New Delhi

Sanjoy Roy Chowdhury
Department of Statistics, Lady Shri Ram College for Women (University of Delhi), New Delhi
 

DOI : DOI-https://doi.org/10.32381/IAPQRT.2022.46.01-02.6

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News Corner

Page No : 125-126

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Apr-2020 to Mar-2021

Multivariate Process Capability Indices for Non-Normal Processes

By: Kailas Govinda Khadse , Ramkrishna Lahu Shinde

Page No : 1-24

Abstract
In this paper by using fraction conforming probabilities p1 and p2, we introduce Multivariate Process Capability Indices (MPCIs) ( 1) ( 2 ) and p p pk p MC MC which measures potential capability and actual capability respectively for multivariate non-normal processes. Computing aspects of p( p1) MC and  pk ( p2 ) MC are discussed in detail considering hyper rectangular specification region. Two cases of multivariate non-normal processes are considered. While constructing MPCIs, in the first case it is assumed that process variables are independent and in the second case it is assumed that process variables are linearly related. In the second case Principal Component Analysis is used to compute point estimate and interval estimate of proposed MPCIs. Real life problems are given for illustration of proposed MPCIs with their interpretations.

Authors :
Kailas Govinda Khadse
School of Mathematical Sciences, M. J. College (Autonomous), Jalgaon

Ramkrishna Lahu Shinde
School of Mathematical Sciences, Kavayitri Bahinabai Chaudhari North Maharashtra University, Jalgaon

DOI : DOI-https://doi.org/10.32381/IAPQRT.2021.45.01-02.1

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Combined Array Approach for the 12 Run Plackett-Burman Design 

By: Renu Kaul , Sanjoy Roy Chowdhury

Page No : 25-35

Abstract
Taguchi’s ([8], 1987) robust parameter design, is a very useful technique for reducing variation and improving product’s quality. However, in some applications, his approach leads to unnecessary expensive experiments. Alternatively, one can use combined arrays by modelling the response itself rather than the expected loss for Orthogonal Fractional Factorial Designs.
In this paper, we have exploited the non-orthogonal column structure of the 12 run Plackett-Burman (PB) design to generate non-orthogonal combined arrays.

Authors :
Renu Kaul
Department of Statistics, Lady Shri Ram College for Women (University of Delhi), New Delhi

Sanjoy Roy Chowdhury
Department of Statistics, Lady Shri Ram College for Women (University of Delhi), New Delhi
 

DOI : DOI-https://doi.org/10.32381/IAPQRT.2021.45.01-02.2

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Estimation of Parameters for Distribution of Timber Pole Failures Due to in-Ground Decay

By: Anisur Rahman , Gopinath Chattapadhyay

Page No : 36-48

Abstract
Timber components are very popular due to its flexibility in use and therefore, widely used in bridges and building constructions, rail tracks and supply electricity throughout the world and in Australia. The main reason of this choice is for their high strength per unit weight, low cost and excellent durability. Reliability of these components is extremely important because a failure of these components may cause loss of money, loss of properties, injuries or even loss of lives. Reliability depends on various factors such as species of the timber, structural dimensions in design, environmental condition, human factors in installation, operations and maintenance. In general, the timber structure failures are due to the loss of load bearing capacity from the decrease in peripheral dimensions at or below ground level and loss of strength of timber fibre affecting bending resistance. Soil factors and related decays reduce the diameter and the strength of timber component affecting the safety in operation and service. Rotting of fibre can be from centre to outward or outward to centre by accelerating fungal and insect (termite) attack affecting reliability, availability, maintainability and safety of infrastructure assets. This paper is on investigating soil factors for modelling in ground decay and estimating parameters for failure distribution of timber poles. Real life data from electricity supply company in Australia have been used for modelling and validation. Results from this investigation can be used in optimal decision in maintenance and replacements for reducing the life cycle costs and risks of in-service failure of timber poles and infrastructure assets in similar environment.

Authors :
Anisur Rahman
Griffith University, Gold Coast campus, Southport, Australia

Gopinath Chattapadhyay
Federation University, Victoria, Australia
 

DOI : DOI-https://doi.org/10.32381/IAPQRT.2021.45.01-02.3

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On the Nature of Saturated 2-Factor Quadratic Response Designs for Unbiased Estimation of Quadratic Effects Parameters

By: Sobita Sapam , Nripes Kumar Mandal , Bikas K Sinha

Page No : 49-62

Abstract
We contemplate an experimental situation which deals with a 2-factor quadratic response involving, in its model expectation, the mean term, both the linear  effects parameters, and both the quadratic effects parameters as well as the product term parameter. We assume the errors to be homoscedastic and uncorrelated. Our intention is to conduct a saturated design [SD] - using a subset of six distinct but suitably chosen design points in an appropriately defined factor space. Further to this, we wish to achieve maximum precision in joint estimation of the last three [quadratic effects] parameters. It is known beforehand that these three effect(s)/interaction(s) are likely to be non-negligible. We examine the flexibility to the extent that an experimenter can make a choice of an SD, retaining information on the three remaining effects/interactions as well. We use the D-optimality criterion and deal with a continuous design set-up. At the end, we also discuss about A-optimality criterion.

Authors :
Bikas K Sinha
Indian Statistical Institute, Kolkata.

Sobita Sapam
Manipur University, Canchipur [Imphal], Manipur.

Nripes Kumar Mandal
Calcutta University, Kolkata.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2021.45.01-02.4

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Regional Variation in Female Employment Within the Tertiary Sector – A State wise Analysis 

By: Dyuti Chatterjee

Page No : 63-75

Abstract
The growth of the tertiary sector helped India to move on a higher growth pedestal. The present paper tries to explore the regional variation in female employment in the tertiary sector post liberalization. For the sake of the analysis, the states were classified under six zones. The percentage of female main and female marginal workers in the tertiary sector across the states were first analyzed to understand the level of interregional and intraregional variation in female employment in the tertiary sector across the states. The Modified Lilien Index was then used to understand the pace of change in female employment post liberalization across the zones. Lastly a multivariate regression was run to identify the factors behind such regional variation in female employment in the tertiary sector. The paper  concluded that the regional variation in female employment could not be captured properly through some macroeconomic aggregates. Introduction of vocational training for women along with a change in state policies are required for the reduction of such regional variation.

Author :
Dyuti Chatterjee
The Bhawanipur Education Society College, Kolkata
 

DOI : DOI-https://doi.org/10.32381/IAPQRT.2021.45.01-02.5

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Bayesian Optimal Designs for Testing Interaction Effects in a Quadratic Mixture Model with Three Components

By: Manisha Pal , N. K. Mandal

Page No : 76-92

Abstract
Scheffé ([12],1958) introduced models of different degrees to represent the response function in a mixture experiment. He also introduced designs for the estimation of the model parameters. Later, several authors discussed the problem of finding optimum designs, especially for quadratic and cubic models. In this paper, we consider the problem of designing an optimal experiment for the purpose of performing one or more hypothesis tests in a quadratic mixture model with three components. We use the Bayesian decision theoretic approach for the purpose.

Authors :
N. K. Mandal
Former Professor, Department of Statistics, University of Calcutta

Manisha Pal
Department of Statistics, University of Calcutta
 

DOI : DOI-https://doi.org/10.32381/IAPQRT.2021.45.01-02.6

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Development of a Model to Integrate Six Sigma Approaches 

By: Subrata Rath , Ashis Kumar Chakraborty , Subhashis Chatterjee

Page No : 93-115

Abstract
Six Sigma was born with a disciplined problem-solving approach called D M A I C (Define, Measure, Analyse, Improve and Control) way back in 1979. The approach is data-intensive requiring statistical orientation and is used for defect reduction. Effect of such defect reduction is visible in the increased profit margin. This approach was a little silent on the waste accumulation in as-is complicated processes. Accumulated waste has direct impact on the cash flow of an organization and usually lean approach is adopted to optimise process flow to reduce, if not eliminate waste in any process. Hence, a new approach was initiated to adapt lean methodology to create better flow in the processes while continuing delivering Six Sigma results. Such approach is known as Lean Six Sigma (LSS). LSS is process flow intensive, requiring more of Industrial Engineering, Operations Research and lean orientation. Results derived from Six Sigma and Lean Six Sigma are well appreciated worldwide across the type and scale of the organizations. However, question started brewing on why the defects and waste are available in any organization in the first instance. This question designated both the Six Sigma and Lean Six Sigma approaches as reactive problem solving initiatives and gave birth of another very important initiative, named Design for Six Sigma (DFSS), to prevent defects and waste in any product and process, in its launch itself. This process is more domain discipline intensive, requiring discovery, invention and innovation. All these approaches together make more sense in business and unfortunately literature is little silent where these approaches are synchronised to leverage the business results for an organization. This paper is an attempt to create a model to integrate all these three approaches with adequate flexibility of interconnectivity within the approach elements for the overall sustainable, predictable and desirable business results. A case is also used to demonstrate the implementation of the mode.

Authors :
Subrata Pal
Shriram Institute for Industrial Research, 19, University Road, Delhi-110007, India

Ashis Kumar Chakraborty
Statistical Quality Control and Operations Research unit, Indian Statistical Institute

Subhashis Chatterjee
Department of Mathematics and Computing, IIT (ISM), Dhanbad
 

DOI : DOI-https://doi.org/10.32381/IAPQRT.2021.45.01-02.7

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On Model Robustness in Discrete Design(s) Set Up: A Teacher’s Manual 

By: Madhura Mandal

Page No : 116-123

Abstract
The problem studied here involves choice of optimum designs for estimation of a full set of treatment effects contrasts in a block design (BD) setup, when positional effects may also be present, besides treatment and block effects. The experimenter is not sure about which of the two models, viz. a block design model or a row-column design model is appropriate. Using weights on the optimality criteria in the two set-ups based on prior knowledge, robust designs are investigated.

Author :
Madhura Mandal
Vivekananda Mahavidyalaya, Burdwan, West Bengal
 

DOI : DOI-https://doi.org/10.32381/IAPQRT.2021.45.01-02.8

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News Corner

By: Shruti Kanga

Page No : 127-129

 

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Apr-2019 to Sep-2019

An Investigation into Data Quality Aspects of Annual Survey of Industries and of Index of Industrial Production 

By: G. C. Manna

Page No : 1-19

Abstract
This article analyzes the level of precision of estimates of gross value added as per Annual Survey of Industries by examining the relative standard errors associated with the estimates. Annual trend in the estimates of gross value added at the level of state and industrial category is also studied to see if there exist any apparent fluctuations. Further, the article cross-validates the annual growth rates of production of manufacturing sector as assessed by the Index of Industrial Production by comparing the same with the growth rates based on Annual Survey of Industries.

Author :
G. C. Manna
Former Director General Central Statistics Office and National Sample Survey Office, Government of India Currently, Professor, Institute for Human Development & Senior Adviser, NCAER.

 

DOI : DOI-https://doi.org/10.32381/IAPQRT.2019.44.01.1

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Harris Extended Log-Kumaraswamy Distribution and its Applications

By: K. K. Jose , Jisha Virghese

Page No : 20-37

Abstract
Harris Extended Log-Kumaraswamy Distribution and its specialized form namely, the Marshall-Olkin Log-Kumaraswamy Distribution (MOLKw) is introduced and studied in this paper. We have given explicit form for the probability density function and the hazard rate function is derived and its shape properties are studied. Expressions for cumulative distribution function, quantiles and survival function are obtained. Method of maximum likelihood estimation is used for estimation of unknown parameters of the new distribution. The new model is applied on two real data sets on survival times of cancer patients and another data set on carbon fibre strength in the context of reliability studies. The stress strength analysis is carried out with respect to the new model and a simulation study is conducted to estimate the average bias, mean square error, coverage probability etc. for different parameter values.

Authors :
K. K. Jose
Department of Statistics, St.Thomas College, Palai, Arunapuram.

Jisha Varghese
Mahatma Gandhi University, Kottayam, Kerala, India.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2019.44.01.2

Price: 251

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Multivariate Unit and Group Runs Control Chart to Detect Shifts in the Mean Vector

By: M. P. Gadre , V. C. Kakade

Page No : 38-51

Abstract
In some production processes, observations related to the quality characteristics of the process are independent. Under this set up, we propose the ‘Multivariate Unit and Group Runs control chart for mean vector’ (MV-UGR-M). It is verified that, the MV-UGR-M gives a significant reduction in the out-of-control ‘Average Time to Signal’ (ATS) in the zero state, as well in the steady state as compared to the ‘Multivariate Synthetic control chart for Mean vector’ (MV-Syn-M) chart, the ‘Multivariate Group Runs control chart for Mean vector’ (MV-GR-M) and the ‘Multivariate Modified Group Runs control chart for Mean vector’ (MV-MGR-M) charts.

Authors :
M.P. Gadre
Department of Statistics, Savitribai Phule Pune University, Pune.

V.C. Kakade
Department of Statistics, Tuljaram Chaturchand College, Baramati.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2019.44.01.3

Price: 251

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A Model for Impact of Financial Developments and Industries Level Total Factor Productivity on Indian Manufacturing

By: Manoj Kumar

Page No : 52-84

Abstract
In this paper we use firms’ data to study the effects of financial development on total factor productivity of India’s manufacturing sector between 1990 and 2018. We find evidence that financial development has significantly enhanced firm-level TFP in the sector. The evidence is stronger when micro indicators of financial development are used. The firms in Indian private sector need better access to the banking system, while the firms in the government sector and the foreign sector reveal the need for accessing the capital market. We find a significant relationship between financial development and industry-level TFP growth when controlling for time, and industry-time fixed effects. Our results are both statistically and economically significant. Our results are robust to different samples and specifications. Our results suggest that policies favoring financial development in India should be pursued further in order for the largest democracy in the world to advance its economic growth.

Author :
Manoj Kumar
SP Jain School of Global Management, Singapore.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2019.44.01.4

Price: 251

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Literature Review on Methods of Classification in Pattern Recognition

By: Khimya S. Tinani , Deepa H. Kandpal

Page No : 85-102

Abstract
 The objective of this review paper is to summarize some of the well-known methods used in various stages of a pattern recognition system. Pattern recognition has become more and more popular and important to us and it induces attractive attention coming from wider areas. The general processing steps of pattern recognition are discussed, starting with the pre-processing, then the feature extraction, and classification. In this paper we have reviewed methods used in pattern recognition. This review paper introduces the basic concepts of pattern recognition, different methods used for pattern recognition like statistical and structural techniques, template matching, neural network and provides the understanding of various methods and related algorithms for classification.

Authors :
Khimys S. Tinani
Department of Statistics, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, India.

Deepa H. Kandpal
Department of Statistics, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, India.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2019.44.01.5

Price: 251

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News Corner

By: Sucheta Mukherjee

Page No : 103-105

 

Price: 251

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Oct-2019 to Mar-2020

Balancing Cost, Performance and risk in Maintenance and Capital Expenditure

By: Gopinath Chattapadhyay

Page No : 107-126

Abstract
Asset Management is focused on realisation of value from assets through managing risk and opportunity. ISO standard for asset management ISO55000, 2014 stipulates effective control and governance of assets for desired balancing act of cost, performance and risk. This paper aims to study the maintenance and capital expenditure problems. It proposes how to balance cost, performance and risk for asset management. Decisions need to be based on performance and risk in addition to costs based on whole of life are supported by international standards for asset management. Option analysis and informed decision-making are proposed considering life cycle costs. Recent trend with industries is to align with latest international standards for asset management. Asset management in heavy haul rail network focuses on this by realisation of value from assets through managing risk and opportunity. Model for total cost of maintenance was developed covering risk costs associated with undetected surface/ subsurface cracks causing rail breaks and derailments and wear loss due to gauge face lubrication problems and intervention costs in inspections and interventions using progressive rail grinding and solar powered electric lubricators with remote performance monitoring. Illustrative examples are used to show how actions in inspection and subsequent rail grinding for controlling rolling contact fatigue (RCF) along with gauge face lubrication for controlling wear can be achieved in heavy haul railway. This maintenance and capital investment policy and decisions based on life cycle cost models can be used as reference for capital expenditure (capex) and operational expenditure (opex) balancing in any industry in general and heavy haul in particular.

Author :
Gopinath Chattopadhyay
School of Science Engineering and Information Technology, Federation University Northways Road, Churchill, PO Box 3191, Gippsland Mail Centre, Vic 3841.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2020.44.02.1

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Bayesian Analysis of Exponential Distribution Based on Progressive Type-II Censored Competing Risks Data with Binomial Removals

By: Manoj Chacko , Rakhi Mohan

Page No : 127-156

Abstract
In reliability studies, the failure of individuals or items may be due to more than one causes or factors. These risk factors in some sense compete for the failure of the experimental units. Analysis of data in these circumstances is called competing risks analysis. In this paper, we consider the analysis of competing risk data under progressive type-II censoring by assuming the number of units removed at each stage is being random and follows a binomial distribution. Bayes estimators are obtained by assuming the population under consideration follows an exponential distribution. A simulation study is carried out to study the performance of different estimators derived in this paper. A real data set is also used for illustration.

Authors :
Manoj Chacko
Department of Statistics, University of Kerala Trivandrum 695 581, India.

Rakhi Mohan
Department of Statistics, University of Kerala Trivandrum 695 581, India.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2020.44.02.2

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Sampling Inspection Plan For Exponentially Distributed Quality Characteristic And Beyond

By: Harsh Tripathi , Sudhansu S. Maiti , Shovan Biswas , Mahendra Saha

Page No : 157-173

Abstract
In this article, an acceptance sampling inspection plan for variable is discussed when the quality characteristic follows some non-normal distributions, viz., the exponential, Lindley, xgamma or Akash distribution. In this plan, the lot quality is to be measured by the lot mean (
). The plan parameters have been obtained by the two point approaches: the acceptable quality level (AQL) and the limiting quality level (LQL) or the rejectable quality level (RQL). For the given producer’s risk () and consumer’s risk (), the plan parameters: sample size () and acceptance number () are determined for different choices of AQL and LQL. A comparison study has been made in terms of the sample size () and an example is provided to illustrate the performance of the proposed plan

Authors :
Harsh Tripathi
Department of Statistics, Central University of Rajasthan, Rajasthan, India.

Sudhansu S. Maiti
Department of Statistics, Visva-Bharati University, Santiniketan, India.

Shovan Biswas
Department of Statistics, Visva-Bharati University, Santiniketan, India.

Mahendra Saha
Department of Statistics, Central University of Rajasthan, Rajasthan, India.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2020.44.02.3

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A Generalization of Exponentiated Rectangular Distribution

By: E.S. Sindhu , Sophia P. Thomas , Jiju Gillariose

Page No : 174-200

Abstract
This paper introduces a new generalization of the exponentiated rectangular distribution namely, Marshall-Olkin exponentiated rectangular distribution and studied its various properties. Also we illustrated empirically the potentiality of the new family by applying to real data sets. Applications in autoregressive time series modeling and stress-strength analysis are also considered. A simulation study is carried out to study the behaviour of estimates. Sample path properties of the newly developed time series models are also discussed.

Author :
E.S. Sindhu
Department of Statistics, Kuriakose Elias College, Mannanam, Kerala, India.

Sophia P. Thomas
Department of Statistics, St,Thomas College, Pala, Kerala, India.

Jiju Gillariose
Department of Statistics, St,Thomas College, Pala, Kerala, India.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2020.44.02.4

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News Corner

By: Deepa H. Kandpal

Page No : 201-203

 

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Apr-2018 to Sep-2018

Marshall Olkin Exponential Power Distribution and its Generalization : Theory and Applications

By: K. K. Jose , Albin Paul

Page No : 1-29

Abstract
In this paper we introduce a new family of distributions namely Marshall Olkin Exponential Power (MOEP) distribution and its extensions. The advantage of studying this new family of distributions is the wide use of the model with respect to various data sets obtained from different areas. Some statistical and reliability properties of the new family of distributions are discussed. The method of maximum likelihood estimation is used to estimate the unknown parameters. The obtained results are validated using some real data set and it is shown that the new family provides a better fit than its base distributions. The stress strength reliability analysis is also carried out. Average mean square error, average confidence length, coverage probability etc. are computed using simulated data. Using the proposed model we develop autoregressive process with minification structure. We further extend the new distribution to obtain the Harris generalized exponential power distribution and some of its properties are studied.

In this paper we introduce a new family of distributions namely Marshall Olkin Exponential Power (MOEP) distribution and its extensions. The advantage of studying this new family of distributions is the wide use of the model with respect to various data sets obtained from different areas. Some statistical and reliability properties of the new family of distributions are discussed. The method of maximum likelihood estimation is used to estimate the unknown parameters. The obtained results are validated using some real data set and it is shown that the new family provides a better fit than its base distributions. The stress strength reliability analysis is also carried out. Average mean square error, average confidence length, coverage probability etc. are computed using simulated data. Using the proposed model we develop autoregressive process with minification structure. We further extend the new distribution to obtain the Harris generalized exponential power distribution and some of its properties are studied.

Authors :
K.K. Jose
Department of Statistics and Biostatistics, St. Thomas College Pala, Arunapuram.

Albin Paul
Mahatma Gandhi University, Kottayam, Kerala, India.

DOI : DOI- https://doi.org/10.32381/IAPQRT.2018.43.01.1

Price: 251

Computation of Reliability and Probability Weighted Moment Estimation for Three Parameter Mukherjee-Islam Failure Model

By: Showkat Ahmad Lone , A. Islam , Ahmdur Hrahman

Page No : 31-45

Abstract
The Mukherjee-Islam model is commonly used as a simple life time distribution to assess system reliability. We have introduced a location parameter ? (i.e. a time before which failure can’t occur) which makes it a more useful failure distribution than the existing ones. It has been shown to represent appropriate lower tail of the distribution of random variables having fixed lower bound. This study presents reliability computations and probability weighted moment estimation for this model. A comparative analysis is carried out between three-parameter finite range model and some existing bathtub shaped curve fitting models. Maximum likelihood estimation method has also been applied. Key words and Phrases: Reliability, Location parameter, Finite range failure model, Probability weighted moment, Comparative analysis.

Authors :
Showkat Ahmad Lone
Department of Statistics & Operations Research, Aligarh Muslim University, India. 

A. Islam
Department of Statistics & Operations Research, Aligarh Muslim University, India.

Ahmdur Hrahman
Department of Statistics & Operations Research, Aligarh Muslim University, India.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2018.43.01.2

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Inferential Aspects of a Three Unit Hot Standby System with Dependent Structure

By: V. S. Vaidyanathan , P. Chandrasekhar

Page No : 47-59

Abstract
Statistical analysis of standby systems with more than two units has received little attention because of mathematical intricacies involved in analyzing them. Also, such systems have been studied assuming the lifetime and repair time of the units to be independent. The present article is an attempt to study certain inferential aspects of a three unit hot standby system with dependent structure, assuming quadrivariate exponential distribution for the lifetimes of online unit, standby units and the repair time of a failed unit.

Authors :
V.S. Vaidyanathan
 Department of Statistics, Pondicherry University, India.

P. Chandrasekhar
Department of Statistics, Loyola College, Chennai, India.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2018.43.01.3

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A Case Study on Implementation of Mahalanobis-Taguchi System for Multivariate Manufacturing Process Control

By: Sagar Sikder , Indrajit Mukerjee , Subhash Chandra Panja

Page No : 61-71

Abstract
In manufacturing process, quality of an end product or component is often assessed by multiple critical output characteristics (or responses). These responses are often correlated or interacting. Change in process setting condition, with an intension to improve a particular response characteristic, may adversely affect another response. In this context, researchers had proposed various parametric and nonparametric Multivariate Statistical Process Control (MSPC) charts for monitoring of correlated responses and detecting out-of-control signal. However, there is little evidence of nonparametric MSPC research to identify influential response(s) for any out-of-control situation in a manufacturing process. In this paper, Mahalanobis-Taguchi System (MTS), based on Mahalanobis Distance (MD) scale and Taguchi’s Orthogonal Array (OA) design, is explored for detecting out-ofcontrol state and identify influential response(s) for an out-of-control state. Suitability of the approach is verified using a manufacturing process case study.

Authors :
Sagar Sikder
SQC & OR Unit, Indian Statistical Institute, Mumbai, India.

Iindrajit Mukerjee
Shailesh J. Mehta School of Management, IIT Bombay, India.

Subhash Chandra Panja
Department of Mechanical Engineering, Jadavpur University, Kolkata, India.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2018.43.01.4

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Finite Range Life Distributions of Coherent Dependent Systemsby

By: Subhradev Sen , Ahmed Z. Afify

Page No : 73-88

Abstract
Opposed to the general theory of infinite upper limit for lifetime distributions, Mukherjee and Islam ([4], 1983) proposed and studied a finite range distribution considering the fact that designed lifetime of equipment is actually finite. It is quite rational to consider interdependency of multi-component systems in analyzing reliability characteristics. In this article, we consider two-component coherent dependent systems by developing bivariate finite range distribution following the method of Farlie-Gumbel-Morgenstern copula. We investigate and study different reliability characteristics, such as mean time to system failure, system reliability and failure rate functions for finite range coherent dependent systems. We also compare the dependent finite range systems with independent finite range systems for mentioned reliability characteristics.

Authors :
Subhradev Sen
Alliance School of Business, Alliance University, Bangalore, India.

Ahmed Z. Afify
Department of Statistics, Mathematics and Insurance, Benha University, Egypt.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2018.43.01.5

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Reliability Test Plans based on Exponentiated Rayleigh Distribution

By: B. Sriram , R.R.L. Kantam

Page No : 89-100

Abstract
Sampling plans in which items are put to test, to collect the life of the items in order to decide upon accepting or rejecting a submitted lot, are called reliability test plans. The basic probability model of the life of the product is specified as exponentiated Rayleigh distribution. For a given producer’s risk sample size, termination number, the waiting time to terminate the test plan and the operating characteristics are presented. The preference of the test plan over similar plans existing in the literature is established with respect to cost and time of the experiment.

Authors :
B. Sriram
Acharya Nagarjuna University Nagarjuna Nagar, India.

R.R.L. Kantam
Acharya Nagarjuna University Nagarjuna Nagar, India.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2018.43.01.6

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Oct- to Mar-2019

Factor Screening for Formulation Development of a Novel Combined Nano Drug Delivery System using Taguchi Method 

By: Nabanita Mukherjee , Rita Lala , Indrajit Mukerjee

Page No : 101-116

Abstract
An antihyperlipidemic drug like Atorvastatin calcium (ATC) suffers from poor oral bioavailability due to low solubility and first-pass metabolism by the liver. Combination of cholesterol synthesis inhibitor (ATC) and cholesterol absorption inhibitor (Ezetimibe) lowers the cholesterol level more than ATC alone. The combined drug can also reduce the risk of Type II diabetes mellitus due to use of a lower dose of atorvastatin calcium, particularly for geriatric patients. The objective of this work is to screen critical factors for developing a novel combined antihyperlipidemic drug delivery system in nanostructured lipid carrier (NLC) considering percent drug loading, and particle size(nm), as responses. Taguchi’s L8 orthogonal array design with replicates was used to screen factors. TEM study and zeta potential study of the optimal formulation was done which shows formulation within nanometric size range with high stability. Results indicate all four factors are critical to determining optimal formulation.

Authors :
Nabanita Mukherjee
Principal K M Kundnani College of Pharmacy, Mumba.

Rita Lala
Principal K M Kundnani College of Pharmacy, Mumba.

Indrajit Mukherjee
Shailesh J. Mehta School of Management, IIT Bombay.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2019.43.02.1

Price: 251

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Improving Reliability of HTDC Compressor in a Petrochemical Industry using Six Sigma Methodologies 

By: Subrata Rath , Ashis Kumar Chakraborty

Page No : 117-134

Abstract
Low reliability problem due to high temperature direct chlorination (HTDC) vent gas compressor on Vinyl Chloride Monomer (VCM) plant of a petrochemical industry was solved. The study uses the conventional Six Sigma:Define, Measure, Analysis, Improvement and Control (DMAIC) phases to improve reliability of the HTDC compressor in terms of mean time between failure (MTBF). In many cases the Total Preventive Maintenance method or the classical reliability improvement method are adopted to solve such reliability problems. However, Authors found that the DMAIC approach of Six Sigma could solve this problem.

Authors :
Subrata Rath
Statistical Quality Control and Operations Research unit, Indian Statistical Institute, Pune.

Ashis Kumar Chakraborty
Statistical Quality Control and Operations Research unit, Indian Statistical Institute, Kolkata.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2019.43.02.2

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Odds Xgamma – G Family of Distributions

By: Sudhanshu S. Maiti , Sukanta Pramanik

Page No : 135-163

Abstract
A new class of distributions, called Odds xgamma-G family of distributions is proposed for modelling lifetime data. An account of the structural and reliability properties of the new class is presented. Maximum likelihood estimation of parameters of the class of distributions has been described. Two data sets have been analyzed to illustrate its applicability.

Authors :
Sudhansu S. Maiti
Department of Statistics, Visva-Bharati University, Santiniketan, India.

Sukanta Pramanik
Department of Statistics, Siliguri College, North Bengal University, Siliguri, India.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2019.43.02.3

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A two Non-Identical Unit Cold Standby System with Two Phase Repair of a Failed Unit

By: Rakesh Gupta , Vaishali

Page No : 165-177

Abstract
The paper deals with the two non-identical unit cold standby system with two phase repair (Phase-1 and Phase-2) of a failed unit. Unit-1 gets priority in operation over the unit-2. A failed unit first attended by the skilled repairman in phase-1 to inspect and identify the faults and then attended by an ordinary repairman in phase-2 who completes the process of repair. After phase-2 repair the unit becomes as good as new. The failure time distributions of both the units and repair time distributions of Phase-1 for both the units are taken as exponential with different parameters, whereas the repair time distributions of phase-2 for both the units are taken as general. The various measures of system effectiveness are obtained by using regenerative point technique.

Authors :
Rakesh Gupta
Department of Statistics Ch. Charan Singh University, Meerut, India.

Vaishali
Department of Statistics Ch. Charan Singh University, Meerut, India.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2019.43.02.4

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Variance Function Estimation using Signal-to-Noise Ratio

By: Soham Chakraborty , Pathik Mandal

Page No : 178-211

Abstract
A new methodology is developed for estimating the variance function in a heteroscedastic regression set up with a focus on small sample regression based estimation. The three main features of the proposed methodology are as follows: (i) Signal-to-noise ratio is used as the response for the purpose of regression instead of a function of only the residuals of the fitted mean function, (ii) Before fitting the variance function, the data are trimmed following an optimal trimming procedure and (iii) The estimates of the parameters of the variance function obtained from the trimmed data are adjusted to minimize the mean square error of the estimates of variances. The effectiveness of the proposed methods of trimming and adjustments are demonstrated through extensive simulation. It is shown that the variances can be estimated more accurately as above compared to those obtained directly from an estimate of the corresponding variance function. Four sets of real life data are also analyzed for the purpose of illustration.

Authors :
Soham Chakraborty
SQC & OR Unit, Indian Statistical Institute, Kolkata.

Pathik Mandal
SQC & OR Unit, Indian Statistical Institute, Kolkata.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2019.43.02.5

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On Suitable Model Selection Approach for Analysis of Mental Health Service use Data

By: Dulal K. Bhaumik , Subhash Aryal , Scott Hur

Page No : 212-223

Abstract
Various methods are available in the literature for analysis of multi-level longitudinal service utilization and expenditure data. We discuss implementation of several methods to analyze service utilization and cost data. Hierarchical longitudinal service utilization data was analyzed using a log-gamma model. Mixed-effects models with random intercept and trend are the most appropriate method for analyzing data from hierarchical longitudinal studies and they provide the best fitting models. But these models also suffer from non-convergence problem, especially in the presence of random-effects at multiple levels. Researchers generally perform log transformation and use normal-based method to analyze service utilization data due to ease of use. Even though they are difficult to implement, generalized linear models is a more appropriate choice for analyzing service utilization data.

Authors :
Dulal K. Bhaumik
Department of Psychiatry, University of Illinois at Chicago, USA.

Subhash Aryal
Department of Biostatistics and Epidemiology UNT Health Science Center Fort Worth, TX, USA.

Scott Hur
Department of Psychiatry, University of Illinois at Chicago, USA.

DOI : DOI-https://doi.org/10.32381/IAPQRT.2019.43.02.6

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