Published since April 1, 2001

Stochastics and Quality Control

ISSN: 2367-2404

Editor-in-chief: George P. Yanev

Founded by: Elart von Collani

Editorial Board: Justin Chimka, Boyan Dimitrov, Miguel González, Olgierd Hryniewicz, Vladimir K. Kaishev, Magdi S. Moustafa, S.P. Mukherjee, Ken Nishina, Abdur Rahim, Erwin M. Saniga

About this journal

Objective
Stochastics and Quality Control is devoted to all fields related to reliability and quality control in economy, finance, manufacturing, production and inventory. It primarily publishes research articles, but survey articles on a topical area inside the scope are considered, too.

The journal pays special attention to the interdisciplinary character of the topic. Not only mathematicians, but also scientists, economists as well as scholars from other disciplines contribute papers. The methods and results published thus are of interest to various applications in real life.

Topics

• Applied Stochastic Processes
• Branching Processes: Theory and Applications
• Reliability
• Ordered Data Analysis
• Statistical Methodology
• Business Management
• Economy and Finance

Article formats
Research and survey articles

Information on submission process

Your Benefits

Your benefits

Up-to-date research on economic quality control
Interdisciplinary approach to the topic
Worldwide-known editors and reviewers
Rapid online publication of contributions “ahead-of-print”

History

History
Economic Quality Control (now, Stochastics and Quality Control) has emerged from the identically named Newsletter of the “Würzburg Research Group on Quality Control” which was founded in 1986 by Bernhard F. Arnolds, Elart von Collani and John Sheil. Until 2009 the journal was published in cooperation with Heldermann Verlag.　

Abstracting and Indexing

Stochastics and Quality Control is covered by the following services:

Baidu Scholar
Cabells Journalytics
CNKI Scholar (China National Knowledge Infrastructure)
CNPIEC - cnpLINKer
Dimensions
EBSCO (relevant databases)
EBSCO Discovery Service
EconBiz
EconLit
ERIH PLUS (European Reference Index for the Humanities and Social Sciences)
Genamics JournalSeek
Google Scholar
Japan Science and Technology Agency (JST)
J-Gate
JournalTOCs
KESLI-NDSL (Korean National Discovery for Science Leaders)
Mathematical Reviews (MathSciNet)
MyScienceWork
Naver Academic
Naviga (Softweco)
Primo Central (ExLibris)
ProQuest (relevant databases)
Publons
QOAM (Quality Open Access Market)
ReadCube
RePEc (Research Papers in Economics): IDEAS, EconPapers
Scilit
SCImago (SJR)
SCOPUS
Semantic Scholar
Sherpa/RoMEO
Summon (ProQuest)
TDNet
TEMA Technik und Management
Ulrich's Periodicals Directory/ulrichsweb
WanFang Data
WorldCat (OCLC)
X-MOL
Yewno Discover
zbMATH Open

Topics

External Links

Volume 37 Issue 2

December 2022

Publicly Available December 1, 2022

Frontmatter

Page range: i-iv

Download PDF

October 27, 2022

The 𝑛𝑝-Chart with 3-𝜎 Limits and the ARL-Unbiased 𝑛𝑝-Chart Revisited

Manuel Cabral Morais, Philipp Wittenberg, Camila Jeppesen Cruz

Page range: 107-116

Abstract

In the statistical process control literature, counts of nonconforming items are frequently assumed to be independent and have a binomial distribution with parameters ( n , p ) (n,p) , where 𝑛 and 𝑝 represent the fixed sample size and the fraction nonconforming. In this paper, the traditional n ⁢ p np -chart with 3-𝜎 control limits is reexamined. We show that, even if its lower control limit is positive and we are dealing with a small target value p 0 p_{0} of the fraction nonconforming ( p ) (p) , this chart average run length (ARL) function achieves a maximum to the left of p 0 p_{0} . Moreover, the in-control ARL of this popular chart is also shown to vary considerably with the fixed sample size 𝑛. We also look closely at the ARL function of the ARL-unbiased n ⁢ p np -chart proposed by Morais [An ARL-unbiased n ⁢ p np -chart, Econ. Qual. Control 31 (2016), 1, 11–21], which attains a pre-specified maximum value in the in-control situation. This chart triggers a signal at sample 𝑡 with probability one if the observed number of nonconforming items, x t x_{t} , is beyond the lower and upper control limits (𝐿 and 𝑈), probability γ L \gamma_{L} (resp. γ U \gamma_{U} ) if x t x_{t} coincides with 𝐿 (resp. 𝑈). A graphical display for the ARL-unbiased n ⁢ p np -chart is proposed, taking advantage of the qcc package for the statistical software R. Furthermore, as far as we have investigated, its control limits can be obtained using three different search algorithms; their computation times are thoroughly compared.

November 25, 2022

General Independent Competing Risks for Maintenance Analysis

Makram Krit

Page range: 117-126

Abstract

Repairable systems are submitted to corrective maintenance and condition-based preventive maintenance actions. Condition-based preventive maintenance occurs at times which are determined according to the results of inspections and degradation or operation controls. The generalization of the models suggested makes it possible to integrate the dependence between corrective and preventive maintenances. In order to take into account this dependency and the possibility of imperfect maintenances, generalized competing risks models have been presented in Doyen and Gaudoin (2006). In this study, we revise the general case in which the potential times to next corrective and preventive maintenance are independent conditionally to the past of the maintenance process. We address the identifiability issue and we find a result similar to that of Zhou, Lu, Shi and Cheng (2018) for usual competing risks. We propose realistic models with exponential risks and derive their likelihood functions.

November 23, 2022

On Normal-Laplace Stochastic Volatility Model

Shiji Kavungal, Rahul Thekkedath

Page range: 127-136

Abstract

This paper analyses a stochastic volatility model generated by first order normal-Laplace autoregressive process. The model parameters are estimated by the generalized method of moments. A simulation experiment is carried out to check the performance of the estimates. Finally, a real data analysis is provided to illustrate the practical utility of the proposed model and show that it captures the stylized factors of the financial return series.

October 28, 2022

Robust Optimization of an Imperfect Process when the Mean and Variance are Jointly Monitored under Dependent Multiple Assignable Causes

Ali Salmasnia, Samrad Jafarian-Namin, Behnam Abdzadeh

Page range: 137-151

Abstract

Imperfect processes experience fault productions over time due to specific causes. Integrating the statistical process control, maintenance policy, and economic production quantity has led to more favorable results for the imperfect processes in literature. When monitoring a process, multiple assignable causes (ACs) may shift it to an out-of-control state. As indicated recently, if the interdependency of ACs is neglected, the total cost will be underestimated. Moreover, the mean and variance can simultaneously be affected by the occurrence of ACs. A non-central chi-square (NCS) chart was suggested for its decent performance against X-R chart in detecting the process disturbances and lowering quality loss cost. Besides, the increased occurrence rate of ACs over time leads to higher quality and maintenance costs. Employing a non-uniform sampling (NUS) scheme can significantly reduce costs. In the literature of modeling for imperfect processes under multiple ACs, all input parameters have always been fixed. The effectiveness of the models depends somewhat on the accurate estimates of these parameters. In reality, the estimation of parameters may be associated with uncertainty. For the first time, a robust design approach is proposed for designing NCS chart by considering the interval estimation of uncertain parameters. A particle swarm optimization (PSO) algorithm is used to present solutions. The proposed model is investigated through a real numerical example.

November 2, 2022

Estimation and Confidence Intervals of Modified Process Capability Index Using Robust Measure of Variability

Mahendra Saha, Sanku Dey

Page range: 153-164

Abstract

The process capability index (PCI), denoted by 𝐼, is a well-known characteristic in quality control analysis. Using Gini’s mean difference, we construct a new PCI, I G I_{G} say, assuming the two-parameter Weibull distribution (WD). In order to estimate the proposed I G I_{G} when the process follows the WD, we use five classical methods of estimation and compare the performance of the obtained estimators with respect to their mean squared errors (MSEs) through a simulation study. Confidence intervals for the proposed PCI are constructed based on five bootstrap confidence intervals (BCIs) methods. Monte Carlo simulation study has been carried out to compare the performance of these five BCIs in terms of average widths and coverage probabilities. Finally, three real data sets from electronic and food industries are employed for illustrating the effectiveness of the proposed study. All these data sets show that the width of bias-corrected accelerated bootstrap interval is minimum among all other considered BCIs.

August 3, 2022

Cumulative Entropy and Income Analysis

N. Unnikrishnan Nair, B. Vineshkumar

Page range: 165-179

Abstract

In the present work, we investigate the applications of cumulative entropy as a tool in income analysis. The relationships the cumulative entropy has with income gap ratio, Lorenz curve, Gini index, Bonferroni curve and Zenga curve are provided. Applications of the results to real data are illustrated.

Ahead of Print / Just Accepted

Ahead of Print / Just Accepted

Volume 37 (2022)

Volume 36 (2021)

Volume 35 (2020)

Volume 34 (2019)

Volume 33 (2018)

Volume 32 (2017)

Volume 31 (2016)

Volume 30 (2015)

Volume 29 (2014)

Volume 28 (2013)

Volume 27 (2012)

Volume 26 (2011)

Volume 25 (2010)

Volume 24 (2009)

Volume 23 (2008)

Volume 22 (2007)

Volume 21 (2006)

Volume 20 (2005)

Volume 19 (2004)

Volume 18 (2003)

Volume 17 (2002)

Volume 16 (2001)

Cite Score	1.0
European Reference Index for the Humanities
SCImago Journal Rank	0.401
Source Normalized Impact per Paper	0.851

Submit

Submission
https://mc.manuscriptcentral.com/eqc

Your benefits of publishing with us

Rapid publication times
No submission fee
Optional open access publication open access publication
Accepted papers will be published online first as DOI-citable, forward-linked articles for quickest possible visibility for the scientific community
Every article easily discoverable because of Search Engine Optimization (SEO) and comprehensive abstracting and indexing services
Secure archiving by De Gruyter and the independent archiving service Portico
Professional sales and marketing activities

Submission process

Submit your paper via our Scholar One submission management tool following the Information for Authors. After logging in you will be guided through every step of the submission process
Peer review process
A decision on your paper made as soon as possible
Accepted articles are published online ahead of print

Please note

Manuscripts must be written in clear and concise English
Before submitting your article please have a look at the Ethical Guidelines and our Copyright Transfer Agreement
Once your article is accepted you have the option to publish it open access
Our Repository Policy allows you to distribute 30 PDF copies of your published article to colleagues (the PDF has to include the information that it is an author's copy). Please also feel free to distribute the link to the online abstract
If you have any general questions please visit our FAQ page for authors

We look forward to receiving your manuscript!

Hybrid Open Access

Please note that authors from institutions with which we have a transformative agreement can publish open access without paying an article processing charge (APC). More information on the eligible institutions and articles can be found under the "Funding and Support" tab here.

Editorial

Editor-in-Chief

George P. Yanev
School of Mathematical and Statistical Sciences
The University of Texas Rio Grande Valley
1201 West University Drive
Edinburg, Texas 78539-2999
USA
Email: george.yanev@utrgv.edu

Founding Editor

Elart von Collani
Stochastikon GmbH
Schießhausstr. 15
97072 Würzburg
Germany
Email: collani@stochastikon.com

Associate Editors

Justin R. Chimka
Department of Industrial Engineering
University of Arkansas
4207 Bell Engineering Center
Fayetteville, AR 72701
USA
Email: jchimka@uark.edu

Boyan Dimitrov
Science and Mathematics Department
Kettering University
1700 West Third Avenue
Flint, MI 48504-4898
USA
Email: bdimitro@kettering.edu

Miguel González
Department of Mathematics
University of Extremadura
Avda. de Elvas, s/n
06071 Badajoz
Spain
Email: mvelasco@unex.es

Olgierd Hryniewicz
Systems Research Institute
Polish Academy of Sciences
Newelska 6
01-447 Warszawa
Poland
Email: hryniewi@ibspan.waw.pl

Vladimir K. Kaishev
Faculty of Actuarial Science and Insurance
Cass Business School, City University London
106 Bunhill Row
London EC1Y 8TZ
UK
Email: v.kaishev@city.ac.uk

Magdi Moustafa
The American University
P.O.Box 2511
Cairo 11511, Egypt
Email: mmostafa@aucegypt.edu

S.P. Mukherjee
Department of Statistics
University College of Science
35 Ballygunge Circular Rd.
Calcutta 700 019, India

Email: prof.mukherjee@gmail.com

Ken Nishina
Nagoya Institute of Technology
Gokiso-cho, Showa-ku
Nagoya, Aichi, 466-8555
Japan
Email: nishina@nitech.ac.jp

Erwin Saniga
Department of Business Administration
University of Delaware
Newark, Delaware 19716
USA
Email: sanigae@be.udel.edu

(Deutsch)

Online ISSN: 2367-2404
Print ISSN: 2367-2390
Type: Journal
Language: English
Publisher: De Gruyter
First published: April 1, 2001
Publication Frequency: 2 Issues per Year
Audience: mathematicians, scientists, economists as well as scholars from other disciplines