tandf: Quality Engineering: Table of ContentsTable of Contents for Quality Engineering. List of articles from both the latest and ahead of print issues.
https://www.tandfonline.com/loi/lqen20?af=R
tandf: Quality Engineering: Table of Contentstandfen-USQuality EngineeringQuality Engineeringhttps://www.tandfonline.com/cms/asset/68fde9e9-a67e-48d3-8841-ff5413faa8b3/default_cover.jpg
https://www.tandfonline.com/loi/lqen20?af=R
Tukey-EWMA control chart with variable sampling intervals for process monitoring
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2199824?af=R
<a href="/toc/lqen20/36/2">Volume 36, Issue 2</a>, 2024, Page 249-272<br/>. <br/>Volume 36, Issue 2, 2024, Page 249-272<br/>. <br/>Tukey-EWMA control chart with variable sampling intervals for process monitoringdoi:10.1080/08982112.2023.2199824Quality Engineering2023-04-24T01:46:00ZSelcem AdsızBurcu AytaçoğluDepartment of Statistics, Ege University, İzmir, TurkeySelcem Adsız is currently continuing Ph.D program in the Department of Statistics at Ege University. She obtained her BS from the Department of Statistics, Çukurova University in 2018. She received MSc degree in Statistics from Ege University in 2021. Her research interests include Statistical Process Control, and Control Charts.Dr. Burcu Aytaçoğlu is an assistant professor in the Department of Statistics at Ege University, Izmir, Turkey. She received her BS from the Department of Statistics, Middle East Technical University (METU) and MSc degree both from the Department of Statistics and Department of Industrial Engineering, METU. After working as a production planning engineer in the automotive industry for about 6 years in Izmir, she received her PhD in Statistics from Ege University in 2013. Her research interests are Statistical Inference, Statistical Process Control, Process Capability, and Control Charts.Quality Engineering3622492722024-04-02T07:00:00Z2024-04-02T07:00:00Z10.1080/08982112.2023.2199824https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2199824?af=RRobust yield test for a normal production process
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2202727?af=R
<a href="/toc/lqen20/36/2">Volume 36, Issue 2</a>, 2024, Page 273-286<br/>. <br/>Volume 36, Issue 2, 2024, Page 273-286<br/>. <br/>Robust yield test for a normal production processdoi:10.1080/08982112.2023.2202727Quality Engineering2023-05-15T05:45:37ZHamideh IranmaneshMehdi Jabbari NooghabiAbbas Parchamia Department of Statistics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, Iranb Department of Mathematical Sciences, University of Copenhagen, Copenhagen Ø, Denmarkc Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, IranHamideh Iranmanesh was born at Kerman in the south part of Iran in 1989. She received his BSc (2011), MSc (2014) in Statistics from Shahid Bahonar University of Kerman (SBUK). Currently, she is a PhD student at Ferdowsi University of Mashhad in Iran. Her current research focuses on Statistical Quality Control, Fuzzy Quality, Process Capability Indices, Statistical Testing of Hypotheses, etc. E-mail: iranmanesh.hamideh@mail.um.ac.irDr Mehdi Jabbari Nooghabi obtained his master's degree in mathematical statistics at Ferdowsi University of Mashhad in 2002 and he received his Ph.D. from University of Mumbai in 2011. Currently, he is Associate Professor at Ferdowsi University of Mashhad and University of Copenhagen. His current research focuses on, Inference in the presence of Outliers, Applied Statistics, Statistical Quality Control, Financial Mathematics, Insurance, Data Science, etc. E-mail: jabbarinm@um.ac.ir, mjn@math.ku.dkDr Abbas Parchami was born at Mashhad in the north-eastern part of Iran in 1977. He received his BSc (2001), MSc (2004) and PhD (2015) in Statistics from Ferdowsi University of Mashhad, Shahid Bahonar University of Kerman (SBUK) and Ferdowsi University of Mashhad, respectively. He is currently working as an Associate Professor of Statistics at the Department of Statistics of SBUK. His research interests include Statistical Simulation, Fuzzy Statistics, Data Mining, Decision Making and Quality Control. E-mail: parchami@uk.ac.irQuality Engineering3622732862024-04-02T07:00:00Z2024-04-02T07:00:00Z10.1080/08982112.2023.2202727https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2202727?af=RThe decay of Six Sigma and the rise of Quality 4.0 in manufacturing innovation
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2206679?af=R
<a href="/toc/lqen20/36/2">Volume 36, Issue 2</a>, 2024, Page 316-335<br/>. <br/>Volume 36, Issue 2, 2024, Page 316-335<br/>. <br/>The decay of Six Sigma and the rise of Quality 4.0 in manufacturing innovationdoi:10.1080/08982112.2023.2206679Quality Engineering2023-05-18T01:41:22ZCarlos A. EscobarDaniela Macias-ArregoytaRuben Morales-MenendezTecnológico de Monterrey, Monterrey, NL, MéxicoCarlos A Escobar is has a Ph.D. in Engineering Sciences at Tecnológico de Monterrey. He was a researcher and developer at General Motors Technical Center, Warren, MI, for over six years. He is a Research Scientist at Amazon Flex, Headquarters, Seattle, WA.Daniela Macias is pursuing a Master of Science in Manufacturing Systems at Tecnológico de Monterrey.Ruben Morales-Menendez has a Ph.D. in Artificial Intelligence. He is Dean of Graduate Studies at the School of Engineering and Sciences at Tecnológico de Monterrey. He belongs to the National Research System (Level II) and is a Mexican Academy of Sciences and Engineering member.Quality Engineering3623163352024-04-02T07:00:00Z2024-04-02T07:00:00Z10.1080/08982112.2023.2206679https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2206679?af=RReliability modeling for failure correlations to a CNC lathe subsystem based on Pagerank Algorithm
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2208664?af=R
<a href="/toc/lqen20/36/2">Volume 36, Issue 2</a>, 2024, Page 336-349<br/>. <br/>Volume 36, Issue 2, 2024, Page 336-349<br/>. <br/>Reliability modeling for failure correlations to a CNC lathe subsystem based on Pagerank Algorithmdoi:10.1080/08982112.2023.2208664Quality Engineering2023-05-08T08:47:59ZDongwei GuJin GuoWenbo HanSong GaoXilu ZhaoZhen Xua School of Mechatronic Engineering, Changchun University of Technology, Changchun, Jilin, Chinab Saitama Institute of Technology, Fukaya, Saitama, Japanc Shandong Dongyue Polymer Material Co., Ltd., Zibo, Shandong, ChinaDongwei Gu received the BS degree in Mechatronic Engineering and Automation Major from the Shijiazhuang Tiedao University, Shijiazhuang, China, in 2006, the MS degree in Mechanical Manufacture and Automation Major from Changchun University of Science and Technology, Changchun, China, in 2010 and the Ph.D. degree in Mechatronic Engineering from Jilin University, Changchun, China, in 2013. In 2019, he is a visiting scholar at Oakland University. His main research interests include importance measures of complex systems, accelerated life reliability test, and system reliability evaluation and maintenance strategy.Jin Guo received the BS degree in Mechatronic Engineering from the Changchun University of Technology, Changchun, China, in 2021. He is currently pursuing the MS degree in mechanical engineering at Changchun University of Technology, Changchun, China. His main research interests include theory and method of dynamic resilience assessment and dynamic reliability.Wenbo Han received the BS degree in Mechatronic Engineering from the Changchun University of Technology, Changchun, China, in 2021. He is currently pursuing the MS degree in mechanical engineering at Changchun University of Technology, Changchun, China. His main research interests include theory and method of structural reliability and mechanical reliability.Song Gao received the BS degree in Electronic Information Engineering from the Central South University, Changsha, China, in 2009, the MS and PhD degrees in Vehicle Engineering from the Dalian University of Technology, Dalian, China, in 2015. From 2015 to now, he was a lecturer at Changchun University of Technology. His main research interests include theory and method of flexible 3D stretch-bending process and rivetless joining process.Xilu Zhao received the BS degree in mechanics from the Harbin Institute of Technology, Harbin, China, in 1983, the MS degree in Pressure processing from Yanshan University, Yanshan, China, in 1988, and the Ph.D. degree in mechanical physics from Tokyo Institute of Technology, Tokyo, Japan, in 2011. Now he is working at Saitama Institute of Technology, Japan. His research interest covers mechanical optimization design.Zhen Xu received the MS degree in Mechatronic Engineering from the Changchun University of Technology, Changchun, China, in 2021. Now he is working at Shandong Dongyue Polymer Material Co., Ltd.Quality Engineering3623363492024-04-02T07:00:00Z2024-04-02T07:00:00Z10.1080/08982112.2023.2208664https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2208664?af=RFlexible, efficient borrowing: A power prior structure for Bayesian interim analysis
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2209160?af=R
<a href="/toc/lqen20/36/2">Volume 36, Issue 2</a>, 2024, Page 350-364<br/>. <br/>Volume 36, Issue 2, 2024, Page 350-364<br/>. <br/>Flexible, efficient borrowing: A power prior structure for Bayesian interim analysisdoi:10.1080/08982112.2023.2209160Quality Engineering2023-05-19T04:28:38ZVictoria R. C. SieckFletcher G. W. Christensena Department of Mathematics and Statistics, Air Force Institute of Technology, Wright Patterson AFB, Ohiob Department of Mathematics and Statistics, University of New Mexico, Albuquerque, New MexicoVictoria R.C. Sieck earned her Ph.D. in statistics from the from the University of New Mexico in 2021. She is an Assistant Professor of Statistics at the Air Force Institute of Technology (AFIT), Department of Mathematics and Statistics and an Operations Research Analyst in the US Air Force (USAF). Her research interests include design of experiments and developing innovate Bayesian approaches to DoD testing.Fletcher G.W. Christensen earned his Ph.D. in statistics from UC Irvine in 2017. He is an Assistant Professor of Statistics at the University of New Mexico, Department of Mathematics and Statistics. His research interests include Bayesian nonparametrics, model selection methods, and foundations of statistics.Quality Engineering3623503642024-04-02T07:00:00Z2024-04-02T07:00:00Z10.1080/08982112.2023.2209160https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2209160?af=RReevaluating the performance of control charts based on ranked-set sampling
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2212751?af=R
<a href="/toc/lqen20/36/2">Volume 36, Issue 2</a>, 2024, Page 365-370<br/>. <br/>Volume 36, Issue 2, 2024, Page 365-370<br/>. <br/>Reevaluating the performance of control charts based on ranked-set samplingdoi:10.1080/08982112.2023.2212751Quality Engineering2023-06-12T07:36:24ZWilliam H. WoodallAbdul HaqMahmoud A. MahmoudNesma A. Saleha Department of Statistics, Virginia Tech, Blacksburg, Virginiab Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistanc Statistics Department, Faculty of Economics and Political Science, Cairo University, Giza, EgyptWilliam H. Woodall is an Emeritus Professor in the Department of Statistics at Virginia Tech. He is a former editor of the Journal of Quality Technology (2001–2003). He is the recipient of the Box Medal (2012), Shewhart Medal (2002), Hunter Award (2019), Youden Prize (1995, 2003), Brumbaugh Award (2000, 2006), Bisgaard Award (2012), Nelson Award (2014), Ott Foundation Award (1987), and best paper award for the IIE Transactions on Quality and Reliability Engineering (1997). He is a Fellow of the American Statistical Association, a Fellow of the American Society for Quality, and an elected member of the International Statistical Institute.Abdul Haq is an Associate Professor at the Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan. His research interest is in Statistical Process Control.Mahmoud A. Mahmoud is Dean of the Faculty of Economics and Political Science, Cairo University. Prior to becoming Dean, he was the Vice Dean for Education and Students’ Affairs, and a Professor of Statistics at Cairo University, Faculty of Economics and Political Science. He holds his BS (1992) and MS (1997) in statistics from Cairo University, and PhD (2004) in statistics from Virginia Tech—USA. His primary area of interest is statistical quality control and improvement. He is a member of the Editorial Board of Quality and Reliability Engineering International, and Review of Economics and Political Science (REPS). He is a Deputy Editor-in-Chief for Journal of Humanities and Applied Social Sciences (JHASS).Nesma A. Saleh is an Associate Professor of Statistics at the Department of Statistics, Faculty of Economics and Political Science, Cairo University. She holds her B.Sc. (2009), M.Sc. (2012), and PhD (2016) in statistics from Cairo University. Her main area of interest is statistical quality control.Quality Engineering3623653702024-04-02T07:00:00Z2024-04-02T07:00:00Z10.1080/08982112.2023.2212751https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2212751?af=ROptimized control charts using indifference regions
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2218904?af=R
<a href="/toc/lqen20/36/2">Volume 36, Issue 2</a>, 2024, Page 371-389<br/>. <br/>Volume 36, Issue 2, 2024, Page 371-389<br/>. <br/>Optimized control charts using indifference regionsdoi:10.1080/08982112.2023.2218904Quality Engineering2023-06-20T09:03:23ZAlex KuiperRob GoedhartDepartment of Business Analytics, Amsterdam Business School, University of Amsterdam, Amsterdam, The NetherlandsAlex Kuiper is an Associate Professor in the Department of Business Analytics at the Amsterdam Business School of the University of Amsterdam and a senior consultant at the Institute for Business and Industrial Statistics of the University of Amsterdam, the Netherlands. In 2013, he received a double MSc in Stochastics & Financial Mathematics and Econometrics from the University of Amsterdam. He completed his Ph.D. in Operations Research at the same university in 2016. His current research includes various topics, such as operations improvement, logistics, and healthcare optimization.Rob Goedhart is an Assistant Professor in the Department of Business Analytics at the Amsterdam Business School of the University of Amsterdam and a senior consultant at the Institute for Business and Industrial Statistics of the University of Amsterdam, the Netherlands. He obtained his MSc in Econometrics at the University of Amsterdam in 2014 and his Ph.D. in Statistics at the same university in 2018. His current research revolves around estimation techniques in statistical and predictive process monitoring as well as explainable artificial intelligence (XAI).Quality Engineering3623713892024-04-02T07:00:00Z2024-04-02T07:00:00Z10.1080/08982112.2023.2218904https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2218904?af=RA new multivariate control chart based on the isolation forest algorithm
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2220773?af=R
<a href="/toc/lqen20/36/2">Volume 36, Issue 2</a>, 2024, Page 390-406<br/>. <br/>Volume 36, Issue 2, 2024, Page 390-406<br/>. <br/>A new multivariate control chart based on the isolation forest algorithmdoi:10.1080/08982112.2023.2220773Quality Engineering2023-06-20T09:02:42ZJing WangLiu Liua School of Mathematics and VC and VR Key laboratory of Sichuan Province, Sichuan Normal University, Chengdu, Sichuan, Chinab School of Medical Information and Engineering, Southwest Medical University, Luzhou, Sichuan, Chinac College of Mathematics and Physics, Chengdu University of Technology, Chengdu, Sichuan, ChinaJing Wang is a doctoral student at the School of Mathematical Sciences, Sichuan Normal University. Her research interests include machine learning and statistical process control.Liu Liu is the dean of the College of Mathematics and Physics at Chengdu University of Technology. He is a professor and a doctoral supervisor. He obtained his PhD degree in Mathematics from Sichuan Normal University and his research interests include big data analysis, statistical process control, and medical statistics.Quality Engineering3623904062024-04-02T07:00:00Z2024-04-02T07:00:00Z10.1080/08982112.2023.2220773https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2220773?af=RA latent process approach to change-point detection of mixed-type observations
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2223617?af=R
<a href="/toc/lqen20/36/2">Volume 36, Issue 2</a>, 2024, Page 407-426<br/>. <br/>Volume 36, Issue 2, 2024, Page 407-426<br/>. <br/>A latent process approach to change-point detection of mixed-type observationsdoi:10.1080/08982112.2023.2223617Quality Engineering2023-06-28T07:49:42ZShuyu ChuXueying LiuAchla MaratheXinwei Denga Department of Statistics, Virginia Tech, Blacksburg, Virginiab Biocomplexity Institute, University of Virginia, Charlottesville, VirginiaShuyu Chu is a Ph.D. Student in the Department of Statistics at Virginia Tech. Her research interests include change-point detection and modeling complex data.Xueying Liu is a Ph.D. Student in the Department of Statistics at Virginia Tech. Her research interests focus on uncertainty quantification and big data analytics.Achla Marathe is a professor at the Biocomplexity Institute and at the Department of Public Health Sciences, School of Medicine, at the University of Virginia. Her research interest include health economics, social epidemiology, data driven modeling of socially coupled systems, and energy markets.Xinwei Deng is a Professor of Statistics and Data Science Faculty Fellow at Virginia Tech. His research interest focus on modeling and analysis of data with complex structures, machine learning, design of experiments, and uncertainty quantification.Quality Engineering3624074262024-04-02T07:00:00Z2024-04-02T07:00:00Z10.1080/08982112.2023.2223617https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2223617?af=RHow generative AI models such as ChatGPT can be (mis)used in SPC practice, education, and research? An exploratory study
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2206479?af=R
<a href="/toc/lqen20/36/2">Volume 36, Issue 2</a>, 2024, Page 287-315<br/>. <br/>Volume 36, Issue 2, 2024, Page 287-315<br/>. <br/>How generative AI models such as ChatGPT can be (mis)used in SPC practice, education, and research? An exploratory studydoi:10.1080/08982112.2023.2206479Quality Engineering2023-06-16T03:36:38ZFadel M. MegahedYing-Ju ChenJoshua A. FerrisSven KnothL. Allison Jones-Farmera Farmer School of Business, Miami University, Oxford, Ohiob Department of Mathematics, University of Dayton, Ohioc Department of Mathematics & Statistics, Helmut Schmidt University, Hamburg, GermanyFadel M. Megahed is a Miami University Faculty Scholar and the Endres Associate Professor in the Department of Information Systems & Analytics at Miami University in Oxford, Ohio. He received his Ph.D. and M.S. in Industrial and Systems Engineering from Virginia Tech and a B.S. in Mechanical Engineering from the American University in Cairo. His research interests include statistical process monitoring and applied machine learning with applications in manufacturing, healthcare, and occupational safety. His work in these areas has been funded by the National Institute for Occupational Safety and Health (NIOSH), the National Science Foundation (NSF), the American Society of Safety Professionals (ASSP) Foundation, and several industrial partners. Dr. Megahed is the Editor of the Case Study Section for the Journal of Quality Technology.Ying-Ju (Tessa) Chen is an Assistant Professor in the Department of Mathematics at the University of Dayton, Ohio. Her research interests focus on Statistical Modeling and Data Science applications in manufacturing, healthcare operations, and transportation safety. Specifically, she is dedicated to working on research related to people's daily lives and well-being.Joshua A. Ferris is a Miami University Visiting Assistant Lecturer in the department of Information Systems & Analytics at Miami University in Oxford, Ohio. He enjoys assisting non-profits with technology-related problems such as website development. He received a B.S. in Mathematics from the University of York and an M.S. in Business Analytics from Miami University.Sven Knoth is a Professor of Statistics in the Department of Mathematics and Statistics within the School of Economic and Social Sciences at the Helmut Schmidt University, Hamburg, Germany. Prior to that, he worked as a Senior SPC Engineer at Advanced Mask Technology Center (AMTC) Dresden, Germany, from 2004 to 2009. He is an Associate Editor of Computational Statistics and Editorial Board member of Journal of Quality Technology and Quality Engineering. He received a Diploma (equivalent to M.S.) and a Ph.D. both in Mathematics from the Technical University Chemnitz, Germany.L. Allison Jones-Farmer is the Van Andel Professor of Business Analytics at Miami University in Oxford, Ohio. Her research focuses on developing practical methods for analyzing data in industrial and business settings. She is the current Editor-in-Chief of Journal of Quality Technology; is on the editorial board of Quality Engineering and is a former Associate Editor for Technometrics. In addition to her research in industrial analytics, Allison enjoys helping organizations improve their analytics capability, developing innovative curricula, and teaching data science. Prior to joining Miami University, Allison was a Professor of Statistics and Analytics at Auburn University where she held the C&E Smith chair. She received a B.S. in Mathematics from Birmingham-Southern College, an M.S. in Applied Statistics from the University of Alabama, and a Ph.D. in Applied Statistics from the University of Alabama.Quality Engineering3622873152024-04-02T07:00:00Z2024-04-02T07:00:00Z10.1080/08982112.2023.2206479https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2206479?af=RFirst to signal criterion for comparing control chart performance
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2223690?af=R
<a href="/toc/lqen20/36/2">Volume 36, Issue 2</a>, 2024, Page 427-438<br/>. <br/>Volume 36, Issue 2, 2024, Page 427-438<br/>. <br/>First to signal criterion for comparing control chart performancedoi:10.1080/08982112.2023.2223690Quality Engineering2023-08-14T05:48:06ZSteven E. RigdonNathaniel T. StevensJames D. WilsonWilliam H. Woodalla Department of Epidemiology and Biostatistics, Saint Louis University, Saint Louis, Missouri, USAb Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, USAc Department of Mathematics and Statistics, University of San Francisco, San Francisco, California, USAd Department of Statistics, Virginia Tech, Blacksburg, Virginia, USAQuality Engineering3624274382024-04-02T07:00:00Z2024-04-02T07:00:00Z10.1080/08982112.2023.2223690https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2223690?af=RA control chart for monitoring images using jump location curves
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2232441?af=R
<a href="/toc/lqen20/36/2">Volume 36, Issue 2</a>, 2024, Page 439-452<br/>. <br/>Volume 36, Issue 2, 2024, Page 439-452<br/>. <br/>A control chart for monitoring images using jump location curvesdoi:10.1080/08982112.2023.2232441Quality Engineering2023-07-10T06:40:06ZAnik RoyPartha Sarathi MukherjeeIndian Statistical Institute, Kolkata, IndiaAnik Roy is currently a research fellow at Indian Statistical Institute, Kolkata, and he is pursuing his doctoral studies in statistics. His research interests include control charts for image processing.Partha Sarathi Mukherjee is currently an associate professor at Indian Statistical Institute, Kolkata. His research interests include image processing and statistical process control.Quality Engineering3624394522024-04-02T07:00:00Z2024-04-02T07:00:00Z10.1080/08982112.2023.2232441https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2232441?af=RI-optimal or G-optimal: Do we have to choose?
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2194963?af=R
<a href="/toc/lqen20/36/2">Volume 36, Issue 2</a>, 2024, Page 227-248<br/>. <br/>Volume 36, Issue 2, 2024, Page 227-248<br/>. <br/>I-optimal or G-optimal: Do we have to choose?doi:10.1080/08982112.2023.2194963Quality Engineering2023-04-13T07:30:33ZStephen J. WalshLu LuChristine M. Anderson-Cooka Department of Mathematics and Statistics, Utah State University, Logan, UT, USAb Department of Mathematics and Statistics, University of South Florida, Tampa, FL, USAc Los Alamos, NM, USADr. Stephen J. Walsh is a faculty member in the Department of Mathematics and Statistics at Utah State University. He has over a decade of experience practicing as a quality assurance and experimental design expert in laboratory environments. From 2007 to 2011 he was a researcher at Pacific Northwest National Laboratory in Richland, WA. From 2011 to 2017 he worked as a government Statistician and Quality Manager at the International Atomic Energy Agency in Vienna, Austria. His Ph.D., earned in 2021, provided an adaptation of the Particle Swarm Optimization to solving several difficult optimal design problems. His current research program focuses on the synergistic research bridge between design of experiments and machine learning algorithms.Lu Lu is an Associate Professor of Statistics in the Department of Mathematics and Statistics at the University of South Florida in Tampa. She was a postdoctoral research associate in the Statistics Sciences Group at Los Alamos National Laboratory. Her research areas include statistical engineering, reliability analysis, design of experiments, response surface methodology, survey sampling, and multiple objective/response optimization.Christine M. Anderson-Cook is a statistician and Retired Guest Scientist in the Statistical Sciences Group at Los Alamos National Laboratory. Her research areas include statistical engineering, reliability, design of experiments, multiple criterion optimization, and response surface methodology. She is a Fellow of the American Statistical Association (ASA) and the American Society for Quality (ASQ).Quality Engineering3622272482024-04-02T07:00:00Z2024-04-02T07:00:00Z10.1080/08982112.2023.2194963https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2194963?af=RMutual combination of selected principles and technologies of Industry 4.0 and quality management methods - case study
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2193895?af=R
<a href="/toc/lqen20/36/2">Volume 36, Issue 2</a>, 2024, Page 207-226<br/>. <br/>Volume 36, Issue 2, 2024, Page 207-226<br/>. <br/>Mutual combination of selected principles and technologies of Industry 4.0 and quality management methods - case studydoi:10.1080/08982112.2023.2193895Quality Engineering2023-04-13T04:00:15ZPavel KlaputRadim HercíkZdeněk MacháčekDarja NoskievičováVladimír DostálDavid Vykydala Faculty of Materials Science and Technology, VŠB-TUO, Ostrava, Czech Republicb Faculty of Electrical Engineering and Computer Science, VŠB-TUO, Ostrava, Czech Republicc IdeaHub, z. s., the shared development center in Science and Technology Park, Ostrava-Pustkovec, Czech RepublicPavel Klaput graduated with a master’s degree in quality management in 2009 and in 2015 with a doctoral degree in Industrial systems management, both at the Faculty of Materials Science and Technology, VSB-Technical University of Ostrava, the Czech Republic. After finishing the studies he was an assistant professor at the Department of Quality Management (Faculty of Materials Science and Technology, VSB-Technical University of Ostrava). He supervised many bachelor and diploma theses. His research activities are focused on the development and application of statistical methods for quality planning, statistical process control and continuous improvement. He has been the project leader of several educational development projects and a co-investigator of various research and educational development projects. He has also been involved as an expert in three ESF projects. He is author or coauthor of 39 scientific papers in professional journals and proceedings of conferences.Radim Hercik obtained a bachelor’s degree in Control and Information Systems in 2009, a master’s degree in Measurement and Control Engineering in 2011, and a PhD in Technical Cybernetics in 2014 at VŠB – Technical University of Ostrava, the Czech Republic. Until 2020 his professional career included the position of a developer of ultrasonic automotive sensors at Continental Automotive Czech Republic, Ltd. Since 2020 he has been working at the Department of Cybernetics and Biomedical Engineering, VSB – Technical University of Ostrava and currently he is an assistant professor. He is an author of more than 20 articles and conference papers and has 6 registered inventions. His research topics include embedded systems, automation, industrial robotics and mobile robotics.Zdeněk Macháček obtained a master’s degree in Measurement and Control Engineering, and a PhD in Technical Cybernetics. His professional career includes the positions of the researcher at VŠB-Technical University of Ostrava, the Czech Republic. He has been working at the Department of Cybernetics and Biomedical Engineering, VSB – Technical University of Ostrava, the Czech Republic as an assistant professor. He is the author of more than 30 articles and conference papers and has 10 registered inventions. His research topics include signal processing, machine vision, industrial robotics and digitalization.Darja Noskievičová is a Professor at the Department of Quality Management, Faculty of Materials Science and Technology at VŠB-Technical University of Ostrava in the Czech Republic. She holds a PhD. in Industrial Economics. Her teaching and research activities are focused on the practical applications of industrial statistics, esp. statistical process control, and topics related to the process management, modern manufacturing systems issues (lean and agile management, Six Sigma methodology, principles and methods of Industry 4.0) including. She has published scientific papers in international journals and conferences proceedings. She is also a coauthor of seven monographs. At present she participates in the European Regional Development Fund project ERDF “A Research Platform focused on Industry 4.0 and Robotics in Ostrava”. For many years she has been a member of Group of specialists for statistical methods by the Czech Society for Quality and she has been also a member of the National Mirror Committee no. 4 for application of statistical methods in the Czech Standardization Agency by the Czech Office for Standards, Metrology and Testing. Many diploma theses of her students won the national competition organized by the Czech Society for Quality. She has been also a supervisor of PhD. students.Vladimír Dostál graduated as an engineer from VŠB-Technical university of Ostrava, Faculty of Mechanical Engineering, study branch of Engineering Technology, Czech Republic. His professional career has covered various positions in the industrial organizations (design engineer, designer-in-chief, developer-in-chief, technical director). He has been also a founder of two companies. During this period he obtained also experiences with practical applications of various instruments and methods of quality management such as PPAP, APQP, FMEA, QP, 8D, ISO TS 16949, Lean Design a Manufacturing. Currently he is a chairman of IdeaHub, z.s., a shared development center with the main aim to create the community (from students, academicians and professionals from industrial organizations) and a framework for work on innovative technology projects and their production as well as the mutual exchange of information and knowledge among its members. He is an author of 4 utility models a 5 patents and coauthor of the publication on TRIZ methodology.David Vykydal holds a Ph.D. in Industrial Systems Management. Currently he has been working as an assistant professor at the Department of Quality Management at the Faculty of Materials Science and Technology of VŠB-Technical University of Ostrava in the Czech Republic and also holds the position of quality manager of this university. His teaching and research activities are focused on the issue of quality management, the development and practical use of methods and tools for planning and quality improvement, and the application of computer support in this area. He was a manager or co-researcher of various national or international projects. In the field of quality management, he is the coauthor of three book publications and number of scientific papers published in international journals and proceedings of conferences. Some of the diploma theses of the students, where he was a supervisor, won the national competition for the “František Egermayer Award”, organized by the Czech Society for Quality. During his professional career he co-operated with a number of industrial enterprises as well as organizations from the public sector.Quality Engineering3622072262024-04-02T07:00:00Z2024-04-02T07:00:00Z10.1080/08982112.2023.2193895https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2193895?af=RA Bayesian ARMA-GARCH EWMA monitoring scheme for long run: A case study on monitoring the USD/ZAR exchange rate
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2234458?af=R
. <br/>. <br/>A Bayesian ARMA-GARCH EWMA monitoring scheme for long run: A case study on monitoring the USD/ZAR exchange ratedoi:10.1080/08982112.2023.2234458Quality Engineering2023-07-20T03:33:38ZM. ShingwenyanaJ.-C. Malela-MajikaP. CastagliolaS. W. Humana Faculty of Natural and Agricultural Sciences, Department of Statistics, University of Pretoria, Hatfield, Pretoria, South Africab Nantes Université & LS2N UMR CNRS 6004, Nantes, FranceMxengeni Shingwenyana graduated from the University of Pretoria with BCom (Honours) in Statistics and Data Science. His research interests include Statistical Process Control, Artificial Intelligence and Machine Learning.Jean‐Claude Malela‐Majika obtained his BSc (Honours) degree in Mathematical Statistics from the High Institute of Statistics from the D.R. Congo (Known as ISS), Honours and Master's degrees in Statistics from the University of Pretoria, and a PhD in Statistics from the University of South Africa. He is currently working as a Senior lecturer at the University of Pretoria in the Department of Statistics and he is a member of the South African Statistical Association, the International Statistical Institute (ISI), and the Institute of Certificated and Chartered Statisticians of South Africa (ICCSSA). His principal research interests include statistical process/quality control, distribution theory and Statistical inference.Schalk W Human is an extra-ordinary lecturer in Statistics at the University of Pretoria. His research mainly focuses on the characteristics of the run-length distribution of control charts in case the parameters of the distribution are estimated. His favourite hobbies are cycling and playing online chess.Philippe Castagliola graduated (PhD 1991) from the UTC (Université de Technologie de CompiÃgne, France). He is currently full professor at the Université de Nantes, Nantes, France, and he is also a member of the LS2N (Laboratoire des Sciences du Numérique de Nantes), UMR CNRS 6004. He is an associate editor for Quality Engineering, Communications in Statistics (LSTA, LSSP, and UCAS), and Quality Technology & Quantitative Management. His research activity includes developments of new statistical process monitoring techniques.Quality Engineering11610.1080/08982112.2023.2234458https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2234458?af=RMonitoring univariate processes using control charts: Some practical issues and advice
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2238049?af=R
. <br/>. <br/>Monitoring univariate processes using control charts: Some practical issues and advicedoi:10.1080/08982112.2023.2238049Quality Engineering2023-07-26T01:57:20ZI. M. ZwetslootL. A. Jones-FarmerW. H. Woodalla Department of Business Analytics, University of Amsterdam, Amsterdam, The Netherlandsb Department of Information Systems and Analytics, Miami University, Oxford, Ohio, USAc Department of Statistics, Virginia Tech, Blacksburg, Virginia, USAInez M. Zwetsloot is assistant professor in the Department of Business Analytics at the University of Amsterdam, The Netherlands. Previously she was assistant professor at the Department of Systems Engineering, City University of Hong Kong. She is the recipient of the Young Statistician Award (ENBIS, 2021) and the Feigenbaum Medal (ASQ, 2021). Her research focuses on using statistics and analytics for solving business challenges using data. This includes work on statistical process monitoring, network analytics, quality engineering, and data science. Her email address is i.m.zwetsloot@uva.nl.L. Allison Jones-Farmer is the Van Andel Professor of Business Analytics at Miami University in Oxford, Ohio. She is the current Editor-in-Chief of Journal of Quality Technology. Her research focuses on developing practical methods for analyzing data in industrial and business settings, including statistical process monitoring and business analytics. She is a senior member of ASQ. Her email address is farmerl2@miamioh.edu.William H. Woodall is an emeritus professor in the Department of Statistics at Virginia Tech. He is a former editor of the Journal of Quality Technology (2001–2003). He is the recipient of the Box Medal (2012), Shewhart Medal (2002), Hunter Award (2019), Youden Prize (1995, 2003), Brumbaugh Award (2000, 2006), Bisgaard Award (2012), Nelson Award (2014), Ott Foundation Award (1987), and best paper award for IIE Transactions on Quality and Reliability Engineering (1997). He is a Fellow of the American Statistical Association, a Fellow of the American Society for Quality, and an elected member of the International Statistical Institute. His email address is bwoodall@vt.edu.Quality Engineering11310.1080/08982112.2023.2238049https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2238049?af=RRedefining software reliability modeling: embracing fault-dependency, imperfect removal, and maximum fault considerations
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2241067?af=R
. <br/>. <br/>Redefining software reliability modeling: embracing fault-dependency, imperfect removal, and maximum fault considerationsdoi:10.1080/08982112.2023.2241067Quality Engineering2023-08-08T12:45:28ZUmashankar SamalAjay KumarAtal Bihari Vajpayee Indian Institute of Information Technology and Management, Gwalior, IndiaUmashankar Samal graduated with a master’s degree in Mathematics in 2019 from Sant Longowal Institute of Engineering &Technology, India. Currently, he is a research scholar at Atal Bihari Vajpayee-Indian Institute of Information Technology and Management, Gwalior, India. His research interests include safety, quality, and reliability engineering.Ajay Kumar joined ABV-IIITM, Gwalior in July 2009 and now he is an associate professor at Department of Applied Sciences, ABV-IIITM, Gwalior. He obtained his MSc degree in Industrial Mathematics and Informatics from the Department of Mathematics, IIT Roorkee in 2003, and his Ph.D. in Reliability of Industrial Systems from the Department of Mathematics, IIT Roorkee, in 2009. His primary areas of interest are Reliability, Statistics, Fuzzy Sets, Fuzzy Logic, Optimization, Machine Learning, and Modeling & Simulation. He has published over 45 research papers in reputed journals and conferences.Quality Engineering11010.1080/08982112.2023.2241067https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2241067?af=RStatistical process control (SPC) for double-bounded information: Choosing wisely the parametric family for unit data
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2254843?af=R
. <br/>. <br/>Statistical process control (SPC) for double-bounded information: Choosing wisely the parametric family for unit datadoi:10.1080/08982112.2023.2254843Quality Engineering2023-09-11T05:30:10ZDiego C. NascimentoOilson A. Gonzatto JuniorDavid Elal-OliveroEstefania BonnailPaulo H. Ferreiraa Departamento de Matemática, Facultad de Ingeniería, Universidad de Atacama, Copiapó, Chileb Institute of Mathematics and Computer Science, University of São Paulo, São Carlos, Brazilc Coastal Research Center, Universidad de Atacama, Copiapó, Chiled Department of Statistics, Federal University of Bahia, Salvador, BrazilDiego C. Nascimento is an Associate Professor at Universidad de Atacama, Copiapó, Chile. He holds a Ph.D. degree in Statistics from the Federal University of São Carlos/University of São Paulo (UFSCar/USP), a M.Sc. degree in Business Management from the Federal University of Pernambuco (UFPE), and a B.Sc. degree in Statistics from the Federal University of Rio Grande do Norte (UFRN). He works mainly on the following topics: statistical learning, data visualization and analytics.Oilson A. Gonzatto Junior is a Professor of Statistics at University of São Paulo (USP), São Carlos, São Paulo, Brazil. He received his Ph.D. degree in Statistics in 2021 from UFSCar/USP, his M.Sc degree in Biostatistics in 2017 and B.Sc degree in Statistics in 2016 both from State University of Maringá (UEM), Maringá, Paraná, Brazil, and his licentiate degree in Mathematics in 2014 from State University of Paraná (UNESPAR). He also has a Postdoctoral training at the University of São Paulo (USP), Brazil, in 2021–2023. Currently researches in survival and reliability analysis.David Elal-Olivero is a Full Professor at Universidad de Atacama, Copiapó, Chile. He received his Ph.D. degree in Ciencias Matemáticas in 1987 from the Universidad Complutense de Madrid, Spain. His main research interests include distribution theory.Estefania Bonnail is an Associate Professor at Universidad de Atacama, Copiapó, Chile. She received her Ph.D. degree in Marine and Coastal Management (Erasmus Mundus Ph.D. program) in 2016 from the Universidad de Cádiz, Spain. She has done intensive research in the field of ecotoxicology.Paulo H. Ferreira is a Professor of Statistics at the Institute of Mathematics and Statistics, Federal University of Bahia (UFBA), Brazil. He received his Ph.D., M.Sc. and B.Sc. degrees in Statistics all from the Federal University of São Carlos (UFSCar), Brazil. He also has a Postdoctoral training at the University of São Paulo (USP), Brazil. His main research interests include survival and reliability analysis, data mining and statistical process control.Quality Engineering11910.1080/08982112.2023.2254843https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2254843?af=RA hierarchical model-based method for wafer level virtual metrology under process information deficiency
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2252891?af=R
. <br/>. <br/>A hierarchical model-based method for wafer level virtual metrology under process information deficiencydoi:10.1080/08982112.2023.2252891Quality Engineering2023-09-13T03:31:10ZYu-Jun LiuDong NiXiong ShaoDan-Li GongJin-Jin Lia College of Control Science and Engineering, Zheiang University, Hangzhou, Zhejiang, Chinab Shanghai Huali Integrated Circuit Corporation, Shanghai, Shanghai, ChinaYu-Jun Liu received her B.S. degree in Ocean College from Zhejiang University in 2015. She is currently a Ph.D. candidate in the College of Control Science and Engineering, Zheiang University. Her research focuses on virtual metrology in batch process.Dong Ni is a professor with the College of Control Science and Engineering, Zheiang University. He received a B.S. degree in Industria Automation from Zhejiang University in 2001 and a Ph.D. degree in Chemical Engineering from the University of California, Los Angeles in 2005. His research interests include artificial intelligence, multiscale system modeling and control, big data analytics, and their applications in semiconductor manufacturing and renewable energy.Xiong Shao, Associate Division Director of Shanghai Huali Integrated Circuit Manufacturing Corporation, graduated from physics department of Shanghai University in 2002, specializing in data analysis and application support in IC manufacturing field.Dan-Li Gong is the Director of Engineering Support Section of Huali Itegrated Circuit Manufacturing Co., Ltd. She graduated from the Mathematics Department of Shanghai University. Her main research interests are big data analysis, machine learning and artificial intelligence.Jin-Jin Li received her master’s degree in 2020 from Tongji University. She is currently an engineer in Shanghai Huali Integrated Circuit Manufacturing Co. Ltd. Her research interests mainly focus on the Neural Networks.Quality Engineering11410.1080/08982112.2023.2252891https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2252891?af=ROptimal diagnosis interval for online quality control methods
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2256372?af=R
. <br/>. <br/>Optimal diagnosis interval for online quality control methodsdoi:10.1080/08982112.2023.2256372Quality Engineering2023-09-14T01:31:49Z SandeepArup Ranjan MukhopadhyayStatistical Quality Control and Operations Research Unit, Indian Statistical Institute, Kolkata, West Bengal, IndiaSandeep joined as a Junior Research Fellow in the SQC and OR Division of the Indian Statistical Institute on July 17, 2019. On December 1, 2021, he was promoted to the position of senior research fellow. At present, he is pursuing his PhD work in quality, reliability, and operations research from ISI. Before joining ISI as a research fellow, he completed his MSc in Mathematics in 2018 from the Central University of Haryana in India.Dr. Arup Ranjan Mukhopadhyay has been working as a faculty member [at present, Senior Technical Officer (Professor Grade)] in the Statistical Quality Control and Operations Research Division of the Indian Statistical Institute for more than three decades, which involves applied research, teaching, training, and consultancy in the field of quality management and operations research. Dr. Mukhopadhyay was the Head of the SQC and OR Division at the Indian Statistical Institute for two years during 2020–2022. He has published more than 50 papers in renowned national and international journals. He received a B. Tech. from Calcutta University in 1983, a PGD in SQC and OR in 1985 from the Indian Statistical Institute (ISI), and a two-year Specialist Development Fellowship Program from ISI in 1989. He obtained his PhD (engineering) from Jadavpur University in 2007 in the area of quality engineering. Apart from teaching regularly in the two-year M.Tech. (QROR) course offered by ISI, he has successfully guided several students for PhD work in the fields of quality, reliability, and operations research.Quality Engineering11510.1080/08982112.2023.2256372https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2256372?af=RMulti-branch convolutional attention network for multi-sensor feature fusion in intelligent fault diagnosis of rotating machinery
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2257762?af=R
. <br/>. <br/>Multi-branch convolutional attention network for multi-sensor feature fusion in intelligent fault diagnosis of rotating machinerydoi:10.1080/08982112.2023.2257762Quality Engineering2023-09-19T02:48:04ZKe WuZirui LiChong ChenZhenguo SongJun Wua School of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, Wuhan, Chinab China Ship Development and Design Center, Wuhan, ChinaKe Wu received his B.S. and M.S. degrees in mechanical engineering from Hunan University of Science and Technology, in 2017 and 2020, respectively. He is currently a Ph.D candidate at marine engineering with the School of Naval Architecture and Ocean Engineering from Huazhong University of Science and Technology, China. His main research interests include big data analytics, health monitoring and fault diagnosis for equipment.Zirui Li received the B.S. degree in marine engineering from the Huazhong University of Science and Technology (HUST), China, in 2020, where he is currently pursuing the master’s degree with the School of Naval Architecture and Ocean Engineering at HUST. His main research interests include health monitoring for equipment, deep learning and reinforcement learning.Chong Chen received his B.S. degree in Nuclear science and technology from Harbin Engineering University, China, in 2011, and received his M.S. degrees in Nuclear science and technology from Harbin Engineering University, in 2013. His Ph.D degree in Nuclear science and technology with the school of Fundamental Science on Nuclear Safety and Simulation Technology Laboratory from Harbin Engineering University. His main research interests include reactor thermal-hydraulic and big data analytics.Zhenguo Song received his B.S. and M.S. degree in marine engineering from Dalian Maritime University, China. He is currently a senior engineer at China Ship Development and Design Center. His main research interests include Integrated design of ship dynamics and big data analytics.Jun Wu received his B.S. degree in mechanical engineering from Hubei University of Technology, China, in 2001, and received his M.S. and Ph.D. degrees in mechanical engineering from Huazhong University of Science and Technology (HUST), in 2004 and 2008, respectively. He is currently a full Professor of School of Naval Architecture and Ocean Engineering at HUST. He worked as a visiting scholar at Stanford University, CA, USA from 2014 to 2015, and 2019, where he conducted technical research in the area of structure health monitoring. His research interests include equipment health monitoring, fault diagnosis and remaining useful life prediction. He has more than 80 publications and the award of 12 patents, and receives several awards for his teaching activities.Quality Engineering11510.1080/08982112.2023.2257762https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2257762?af=RRobust confidence intervals for the process capability index Cpk with bootstrap improvement
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2263523?af=R
. <br/>. <br/>Robust confidence intervals for the process capability index Cpk with bootstrap improvementdoi:10.1080/08982112.2023.2263523Quality Engineering2023-10-06T02:35:51ZLinhan OuyangSanku DeyChanseok Parka College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, Chinab Department of Statistics, St. Anthony’s College, Shillong, Indiac Applied Statistics Laboratory, Department of Industrial Engineering, Pusan National University, Busan, South KoreaLinhan Ouyang is an associate professor in the College of Economics and Management at Nanjing University of Aeronautics and Astronautics, China. He holds a BEng degree in industrial engineering from Nanchang University, P.R. China, and a PhD degree in management science and engineering from Nanjing University of Science and Technology, P.R. China. His research interests are process modeling and design of experiments.Sanku Dey is currently working as an associate professor in the Department of Statistics, St. Anthony’s College, Shillong, Meghalaya, India. He did his MSc in Statistics in the year of 1991 from Gauhati University, Guwahati, India and PhD in Statistics (reliability theory) in the year 1998 from the same university. He has published more than 270 research articles in journals of repute. He is an associate editor of American Journal of Mathematical and Management Sciences and also the member of editorial board of several journals of repute. He is a researcher and has a good number of contributions in almost all fields of Statistics viz., distribution theory, discretization of continuous distribution, reliability theory, multicomponent stress-strength reliability, survival analysis, Bayesian inference, record statistics, statistical quality control, order statistics, lifetime performance index based on classical and Bayesian approach as well as different types of censoring schemes, etc.Chanseok Park started college as an engineering student in the Department of Mechanical Engineering at Seoul National University and obtained a BS degree. He then received his MA in Mathematics from the University of Texas at Austin and his Doctorate in Statistics from the Pennsylvania State University. He is at present a professor of Industrial Engineering at Pusan National University. He is also a Director of Applied Statistics Laboratory in the department where he leads the applied statistics group, teaches courses, and conducts various research on quality and reliability engineering, competing risks models, robust inference, solid mechanics, etc. Before joining Pusan National University, he was a faculty member of Mathematical Sciences at Clemson University, Clemson, SC, USA from 2001 to 2015.Quality Engineering11410.1080/08982112.2023.2263523https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2263523?af=RCause-and-effect diagram-based supersaturated designs
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2269437?af=R
. <br/>. <br/>Cause-and-effect diagram-based supersaturated designsdoi:10.1080/08982112.2023.2269437Quality Engineering2023-10-26T02:37:47ZChang-Yun LinDepartment of Applied Mathematics and Institute of Statistics, National Chung Hsing University, Taichung, TaiwanChang-Yun Lin is a Professor in the Department of Applied Mathematics and Institute of Statistics at the National Chung Hsing University in Taiwan. He received his Ph.D. degree from the Tsing Hua University in Taiwan in 2009. His research areas concern design of experiments, machine learning, Bayesian analysis, and genetic statistics.Quality Engineering11610.1080/08982112.2023.2269437https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2269437?af=RA note on compositional data gauge R&R studies
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2276779?af=R
. <br/>. <br/>A note on compositional data gauge R&R studiesdoi:10.1080/08982112.2023.2276779Quality Engineering2023-11-16T04:01:58ZM. S. HamadaStatistical Sciences Group, Los Alamos National Laboratory, Los Alamos, New MexicoMichael Hamada is a retired scientist from Los Alamos National Laboratory (LANL). He earned a PhD in statistics from the University of Wisconsin–Madison. He is a fellow of LANL, ASQ, and ASA. His research interests include design of experiments, reliability, quality control, and measurement system assessment.Quality Engineering11310.1080/08982112.2023.2276779https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2276779?af=RReliability evaluation of a novel metal oxide-aluminum glycerol film capacitor using nonlinear degradation modeling with dependency considerations
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2285298?af=R
. <br/>. <br/>Reliability evaluation of a novel metal oxide-aluminum glycerol film capacitor using nonlinear degradation modeling with dependency considerationsdoi:10.1080/08982112.2023.2285298Quality Engineering2023-11-30T04:44:55ZEkene Gabriel OkaforXin WangBahktiyar Mohammed NafisAndrew LedaDavid Ryan HuitinkXiangbo MengDepartment of Mechanical Engineering, University of Arkansas, Fayetteville, Arkansas, USAQuality Engineering11310.1080/08982112.2023.2285298https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2285298?af=RSimultaneous classification and out-of-distribution detection for wafer bin maps
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2286497?af=R
. <br/>. <br/>Simultaneous classification and out-of-distribution detection for wafer bin mapsdoi:10.1080/08982112.2023.2286497Quality Engineering2023-12-05T07:26:12ZJeongman ChoiEun-Yeol MaHeeyoung KimDepartment of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of KoreaJeongma Choi received a B.S. degree in industrial engineering from Hanyang University and an M.S. degree in industrial and systems engineering from KAIST. His research interests include machine learning and applied statistics.Eun-Yeol Ma received his B.S. and M. S. degrees in industrial and systems engineering from KAIST. His research interests include machine learning and artificial intelligence.Heeyoung Kim received a B.S. degree in industrial engineering from KAIST, M.S. degrees in industrial engineering and statistics from KAIST and the Georgia Institute of Technology, respectively, and a Ph.D. degree in industrial engineering from the Georgia Institute of Technology. She is an associate professor with the Department of Industrial and Systems Engineering, KAIST. She was a Senior Member of Technical Staff with AT&T Laboratories. Her research interests include applied statistics and machine learning.Quality Engineering11310.1080/08982112.2023.2286497https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2286497?af=RMixed-type defect pattern recognition in noisy labeled wafer bin maps
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2286502?af=R
. <br/>. <br/>Mixed-type defect pattern recognition in noisy labeled wafer bin mapsdoi:10.1080/08982112.2023.2286502Quality Engineering2023-12-06T06:25:04ZSumin KimHeeyoung KimDepartment of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of KoreaSumin Kim received a B.S. degree in industrial engineering from Yonsei University and M.S. degree in industrial and systems engineering from KAIST. His research interests include machine learning and applied statistics.Heeyoung Kim received a B.S. degree in industrial engineering from KAIST, M.S. degrees in industrial engineering and statistics from KAIST and the Georgia Institute of Technology, respectively, and a Ph.D. degree in industrial engineering from the Georgia Institute of Technology. She is an associate professor with the Department of Industrial and Systems Engineering, KAIST. She was a Senior Member of Technical Staff with AT&T Laboratories. Her research interests include applied statistics and machine learning.Quality Engineering11510.1080/08982112.2023.2286502https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2286502?af=RUtilizing jackknife and bootstrap to understand tensile stress to failure of an epoxy resin
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2286500?af=R
. <br/>. <br/>Utilizing jackknife and bootstrap to understand tensile stress to failure of an epoxy resindoi:10.1080/08982112.2023.2286500Quality Engineering2023-12-11T04:45:44ZR. Caro-CarreteroA. CarniceroJ. R. Jiménez-OctavioD. Cousineaua Organizational Industrial Department, ICAI-Higher Technical School of Engineering, Universidad Pontificia Comillas, Madrid, Spainb Department of Mechanical Engineering, Universidad Pontificia Comillas, Madrid, Spainc Institute for Research in Technology, Madrid, Spaind Université d’Ottawa, Ottawa, CanadaRaquel Caro-Carretero, Professor in the Department of Industrial Organization at ICAI-Higher Technical School of Engineering (ICAI) of the Pontifical Comillas University in Madrid, has extensive teaching and research experience in various areas related to the application of statistics in engineering, economics and finance, tourism, migrations, disaster management, resilence and Space Sciences. She has taught classes at the Faculty of Economics and Business Administration of Comillas (ICADE) for 10 years. She has been recognized with two six-year research periods and is accredited by ANECA and ACAP.Alberto Carnicero López studied at the Pontifical Comillas University (ICAI), where he graduated in 1995 and obtained his doctorate in 1999 under the supervision of Professor Enrique Alarcón and Ricardo Perera from the ETSII-UPM. He began his teaching career at ETSI-ICAI, where he has taught various subjects related to Continuum Mechanics. He has been recognized with two six-year research periods and is accredited by ANECA and ACAP.Jesús R. Jiménez-Octavio obtained a degree in Industrial Engineering in 2004 from the Pontifical Comillas University and a Ph.D. in Industrial Engineering in 2009 from the same university, with a doctoral thesis titled “Dynamic Analysis and Optimization of Overhead Lines for High-Speed Rail”. He currently works as a Professor in the Department of Mechanical Engineering at ICAI, specializing in the area of Continuum Mechanics and conducts research in the fields of Railway Systems and Bioengineering at the Technological Research Institute. He received the Talgo Prize for Technological Innovation in 2010 for his work on “Railway Simulation, Calculation and Optimization”.Denis Cousineau is a Professor at the Université d’Ottawa since 2011. He previously was a Professor at the Université de Montréal and before that, post-doctoral fellow at Indiana University. He holds B.Sc. degree in computer science, in education and in psychology. His areas of research include response time models, attention and visual search. From 2002 to 2007, he organized yearly the Summer School in Advanced Methodological Methods and he founded in 2005 the Tutorials in Quantitative Methods for Psychology journal. He just published his second textbook (in French), Panorama des statistiques.Quality Engineering11710.1080/08982112.2023.2286500https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2286500?af=RA Bayesian nonparametric system reliability model which integrates multiple sources of lifetime information
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2292602?af=R
. <br/>. <br/>A Bayesian nonparametric system reliability model which integrates multiple sources of lifetime informationdoi:10.1080/08982112.2023.2292602Quality Engineering2024-01-02T07:18:30ZRichard L. WarrJeremy M. MeyerJackson T. CurtisDepartment of Statistics, Brigham Young University, Provo, Utah, USARichard L. Warr is an Assistant Professor of Statistics at Brigham Young University. He obtained a Ph.D. in Statistics from the University of New Mexico. His research interests include Bayesian statistics, Bayesian nonparametric methods, and reliability.Jeremy M. Meyer earned a master’s degree from Brigham Young University with a research emphasis in Bayesian nonparametric methods. He is currently working as a data scientist for MScience doing big data analytics.Jackson T. Curtis earned his Master’s degree in statistics from Brigham Young University. He currently works as a data scientist at a software company.Quality Engineering11610.1080/08982112.2023.2292602https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2292602?af=RModified Imperfect Repair Model (ARAM1) and new PLP parameterization
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2300814?af=R
. <br/>. <br/>Modified Imperfect Repair Model (ARAM1) and new PLP parameterizationdoi:10.1080/08982112.2023.2300814Quality Engineering2024-01-11T04:07:43ZTito LopesVera TomazellaJeremias LeaoFrancisco Louzadaa Statistics Department, Federal University of São Carlos, São Carlos, Brazilb Departamento de Estatística, Universidade Federal do Amazonas, Manaus, Brazilc Institute of Mathematical Science and Computing, University of São Paulo, São Carlos, BrazilQuality Engineering11610.1080/08982112.2023.2300814https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2300814?af=RA new approach to risk assessment in failure mode and effect analysis based on engineering textual data
https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2304815?af=R
. <br/>. <br/>A new approach to risk assessment in failure mode and effect analysis based on engineering textual datadoi:10.1080/08982112.2024.2304815Quality Engineering2024-01-19T06:30:37ZWenyan SongJianing Zhenga School of Economics and Management, Beihang University, Beijing, Chinab Key Laboratory of Complex System Analysis, Management and Decision, Beihang University, Ministry of Education, Beijing, ChinaWenyan Song is a professor at the School of Economics and Management at Beihang University (formerly known as Beijing University of Aeronautics and Astronautics) in China. His principal research interests include Failure Mode and Effect Analysis, Quality Management, and Risk Management. He obtained his PhD in Industrial Engineering from Shanghai Jiao Tong University (SJTU) in 2014. Following this, in 2016, he served as a postdoctoral researcher at the Technische Universität München (TUM) in Germany. Professor Song’s work has been featured in prestigious journals such as the European Journal of Operational Research, IEEE Transactions on Reliability, IEEE Transactions on Engineering Management, International Journal of Operations & Production Management, and International Journal of Production Research. He is available for contact via email at songwenyan@buaa.edu.cn.Jianing Zheng is a researcher at the School of Economics and Management, Beihang University (Beijing Univ of Aeronautics and Astronautics), China. Her main research interest is Failure Mode and Effect Analysis and Risk Management. She can be contacted at zhengjianing@buaa.edu.cn.Quality Engineering11910.1080/08982112.2024.2304815https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2304815?af=RExploratory image data analysis for quality improvement hypothesis generation
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2285305?af=R
. <br/>. <br/>Exploratory image data analysis for quality improvement hypothesis generationdoi:10.1080/08982112.2023.2285305Quality Engineering2024-01-22T04:08:36ZYifei ZhangTheodore T. AllenRamiro Rodriguez BunoIntegrated Systems Engineering, The Ohio State University, Columbus, OhioYifei Zhang is a Ph.D. student in Integrated Systems Engineering at The Ohio State University. She is the author of four Chinese patents relating to fault diagnosis systems. Her research interests include quality engineering, nonlinear programming, sensor analytics, vision AI, and image analysis.Theodore T. Allen is an professor of Integrate Systems Engineering at The Ohio State University. He received his Ph.D. in Industrial Operations Engineering from the University of Michigan. He is the author of over 70 peer-reviewed publications including two textbooks. He is the vice president of Communications for the INFORMS PSOR section and a simulation area editor for Computers & Industrial Engineering. He was a 2023 finalist in the INFORMS Edelman Award Competition for his work with the DHL Supply Chain company.Ramiro Rodriguez Buno is a Ph.D. student in Integrated Systems Engineering at The Ohio State University. His research interests include quality engineering, operations research, AI, and digital manufacturing.Quality Engineering12010.1080/08982112.2023.2285305https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2285305?af=RGrey Duane model for reliability growth prediction under small sample uncertain failure data
https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2304795?af=R
. <br/>. <br/>Grey Duane model for reliability growth prediction under small sample uncertain failure datadoi:10.1080/08982112.2024.2304795Quality Engineering2024-01-23T02:18:31ZLianyi LiuSifeng LiuWenjie DongCollege of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, P.R. ChinaLianyi Liu received the MSc in management science and engineering from Hebei University of Engineering, Handan, China, in 2021. He is currently pursuing his PhD degree in management science and engineering at the College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China. His research interests are uncertainty modeling and reliability growth management.Sifeng Liu received the Ph.D. degree in system engineering from Huazhong University of Science and Technology, Wuhan, China, in 1998. He is currently a Distinguished Professor with the College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China. His research interests include grey system theory and its application, and development and management of complex equipment.Wenjie Dong received the PhD degree in management science and engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2021. He is currently an assistant professor with the College of Economics and Management, Nanjing University of Aeronautics and Astronautics, China. His research interests include reliability modeling, maintenance planning, and spare unit management.Quality Engineering11510.1080/08982112.2024.2304795https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2304795?af=RA process capability function approach to multiple response surface optimization based on a posterior procedure
https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2310264?af=R
. <br/>. <br/>A process capability function approach to multiple response surface optimization based on a posterior proceduredoi:10.1080/08982112.2024.2310264Quality Engineering2024-02-01T04:46:38ZIn-Jun JeongDong-Hee LeeYoung-Jun Sona Department of Business Administration, Daegu University, Daegu, South Koreab Department of Industrial Engineering, Sungkyunkwan University, Suwon, South Koreac School of Industrial Engineering, Purdue University, West Lafayette, Indiana, USADr. In-Jun Jeong is a professor in the Department of Business Administration at Daegu University, Republic of Korea. He earned his BSc, MSc, and PhD in Industrial and Management Engineering from Pohang University of Science and Technology, Republic of Korea. His research interests include quality engineering and management, startup support and incubation, and broadcasting and telecommunications policy, and so on.Dong-Hee Lee is an associate professor at the Department of Industrial Engineering at Sungkyunkwan University (SKKU) in Korea. He received his bachelor’s degree (2006) and his PhD degree (2011) at the Department of Industrial and Management Engineering at POSTECH. Before joining SKKU, he was a senior researcher at the semiconductor division at Samsung Electronics. His current research interests include quality engineering, smart factory, big data analytics in manufacturing, design of experiments, response surface methods, and statistical process control.Young-Jun Son is the James J. Solberg Head and Ransburg Professor of School of Industrial Engineering at Purdue University. Before this position, he was the Department Head and Professor of Systems and Industrial Engineering at University of Arizona. His research focuses on a data-driven, multi-scale, simulation and decision model needed for design and control in various applications, including extended manufacturing enterprise, renewable energy and storage network, homeland security, transportation, and social network. He has authored/co-authored over 110 journal articles and 100 conference papers. He is a Fellow of Institute of Industrial and Systems Engineers (IISE).Quality Engineering11410.1080/08982112.2024.2310264https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2310264?af=RCumulative entropy of progressively type-II censored order statistics and associated optimal life testing-plans
https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2328022?af=R
. <br/>. <br/>Cumulative entropy of progressively type-II censored order statistics and associated optimal life testing-plansdoi:10.1080/08982112.2024.2328022Quality Engineering2024-03-14T04:44:10ZSiddhartha ChakrabortyRitwik BhattacharyaBiswabrata Pradhana SQC & Oregon Unit, Indian Statistical Institute, Kolkata, Indiab Department of Mathematical Sciences, University of Texas at El Paso, El Paso, TXSiddhartha Chakraborty completed his PhD in Quality, Reliability and Operations Research (QROR) in 2023. He received his 5-year Integrated MSc in Statistics from University of Kalyani, India, in 2017. His area of interests include reliability and life-testing, statistical inference and statistical aspects of information theory.Ritwik Bhattacharya is an Assistant Professor at University of Texas at El Paso, United States. He received his BSc degree in Mathematics from the University of Calcutta, India, in 2006, his MSc degree in Mathematics from Indian Institute of Technology Kharagpur, India, in 2008, and his PhD degree in Quality, Reliability, and Operations Research (QROR) from the Indian Statistical Institute Kolkata, India, in 2016. His research interests include censoring methodology, reliability theory, and statistical quality control.Biswabrata Pradhan is a Professor at the Statistical Quality Control & Operations Research (SQC & OR) Unit, Indian Statistical Institute, Kolkata. He received his BSc (Hons.) and MSc degrees in Statistics from the University of Calcutta in 1991 and 1993, respectively; MTech in Quality, Reliability, and Operations research (QR & OR) and PhD in Statistics from the Indian Statistical Institute in 1996 and 2010, respectively. His primary areas of research include inference based on censored data, design of censored life testing experiments, reliability theory, and survival analysis.Quality Engineering1910.1080/08982112.2024.2328022https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2328022?af=RToward a concept of digital twin for monitoring assembly and disassembly processes
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2234017?af=R
. <br/>. <br/>Toward a concept of digital twin for monitoring assembly and disassembly processesdoi:10.1080/08982112.2023.2234017Quality Engineering2023-07-26T01:59:56ZElisa VernaStefano PutteroGianfranco GentaMaurizio GalettoDepartment of Management and Production Engineering, Politecnico di Torino, Torino, ItalyElisa Verna received the master of science degree in Industrial Engineering and Management in 2016 and the PhD in Management, Production and Design in 2021 from Politecnico di Torino, Italy. She is currently assistant professor at the Department of Management and Production Engineering (DIGEP) of the Politecnico di Torino. She is fellow of A.I.Te.M. (Associazione Italiana delle Tecnologie Manifatturiere) and E.N.B.I.S. (European Network for Business and Industrial Statistics). Her current research interests are quality engineering and management, statistical process control, and innovative production systems. In particular, she is focusing on the study, implementation and planning of quality inspection procedures in manufacturing processes, and on the development of defect generation models in manual and human–robot collaborative assembly and disassembly processes.Stefano Puttero is a second-year PhD student in Management, Production and Design at Politecnico di Torino. He received the master of science degree in “engineering and Management” from Politecnico di Torino, Italy, in 2021. His main research interests are quality control and management in human–robot collaboration and the development of innovative defect generation models in the collaborative environment. His research also focuses on the central role of humans in the collaborative environment and the relationship between human well-being and the generation of defects.Gianfranco Genta received the master of science degree in Mathematical Engineering from Politecnico di Torino, Italy, in 2005 and the PhD degree in Metrology: Measuring Science and Technique from Politecnico di Torino in 2010. He is currently associate professor at the Department of Management and Production Engineering (DIGEP) of the Politecnico di Torino, where he teaches “Experimental Statistics and Mechanical Measurement” and “Industrial Quality Management”. He is research affiliate of CIRP (The International Academy for Production Engineering) and fellow of A.I.Te.M. (Associazione Italiana delle Tecnologie Manifatturiere). He is author and coauthor of three books and more than 70 publications on national/international journals and conference proceedings. His current research focuses on industrial metrology, quality engineering and experimental data analysis.Maurizio Galetto received the master of science degree in Physics from University of Turin, Italy, in 1995 and the PhD degree in Metrology: Measuring Science and Technique from Politecnico di Torino, Italy, in 2000. He is currently head of department and full professor at the Department of Management and Production Engineering (DIGEP) of the Politecnico di Torino, where he teaches “Quality Engineering” and “Experimental Statistics and Mechanical Measurement”. He is associate member of CIRP (The International Academy for Production Engineering) and Fellow of A.I.Te.M. (Associazione Italiana delle Tecnologie Manifatturiere) and E.N.B.I.S. (European Network for Business and Industrial Statistics). He is member of the editorial board of the scientific international journal nanomanufacturing and metrology and collaborates as referee for many international journals in the field of industrial engineering. He is author and coauthor of four books and more than 100 published papers in scientific journals and international conference proceedings. His current research interests are in the areas of quality engineering, statistical process control, industrial metrology and production systems. At present, he collaborates in some important research projects for public and private organizations.Quality Engineering11810.1080/08982112.2023.2234017https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2234017?af=RDesigning a variables two-plan sampling system with adjustable acceptance criteria for lot disposition
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2251571?af=R
. <br/>. <br/>Designing a variables two-plan sampling system with adjustable acceptance criteria for lot dispositiondoi:10.1080/08982112.2023.2251571Quality Engineering2023-09-05T06:24:54ZChien-Wei WuMing-Hung ShuTo-Cheng Wanga Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwanb Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwanc Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, Taiwand Department of Aviation Management, Republic of China Air Force Academy, Kaohsiung, TaiwanChien-Wei Wu is currently a Distinguished Professor in the Department of Industrial Engineering and Engineering Management at National Tsing Hua University (NTHU), Taiwan. Dr Wu received his Ph.D. degree in Industrial Engineering and Management with Outstanding Ph.D. Student Award from National Chiao Tung University in 2004 and the M.S. degree in Statistics from NTHU in 2002. Dr Wu has received Dr Ta-You Wu Memorial Award (Outstanding Young Researcher Award) from National Science Council (NSC) in 2011, Outstanding Young Industrial Engineer Award from Chinese Institute of Industrial Engineers (CIIE) in 2011, and Outstanding Research Award from the Ministry of Science and Technology (MOST) in 2021. He is also serving as one of Editors-in-Chief of Quality Technology and Quantitative Management (QTQM) and editorial board members for several international journals. His research interests include quality engineering and management, statistical process control, process capability analysis and data analysis.Ming-Hung Shu received Ph.D. in industrial, manufacturing, and system engineering in 1996 and an MS degree in Electrical Engineering in 1993 at the University of Texas, Arlington, USA. He is a Professor in Industrial Engineering and Management at the National Kaohsiung University of Science and Technology and an affiliate professor in the Department of Healthcare Administration and Medical Informatics at Kaohsiung Medical University, Taiwan. Prof. Shu has been awarded as an Outstanding Young Researcher and the best yearly research project from the Ministry of Science and Technology. His research interests include quality and reliability engineering, decision-making analysis, and applied soft computing.To-Cheng Wang received a bachelor’s degree in Aeronautical and Mechanical Engineering from R.O.C. Air Force Academy (ROCAFA), Kaohsiung, Taiwan, and the MS and Ph.D. degrees in Industrial Engineering and Management from the National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan. He is an Assistant Professor in the Department of Aviation Management at ROCAFA. His research interests lie in quality and reliability engineering and operations research.Quality Engineering11310.1080/08982112.2023.2251571https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2251571?af=RAlternative parameter learning schemes for monitoring process stability
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2253891?af=R
. <br/>. <br/>Alternative parameter learning schemes for monitoring process stabilitydoi:10.1080/08982112.2023.2253891Quality Engineering2023-09-20T05:47:39ZDaniele ZagoGiovanna CapizziDepartment of Statistical Sciences, University of Padua, Padua, ItalyDaniele Zago is a current Ph.D. student in Statistics at the University of Padua since 2021. He obtained his bachelor's degree in Statistics for Technology and Science and his master's degrees in Statistical Sciences from the University of Padua. His main research interests revolve around fundamental issues in practical applications of statistical process control and optimization.Dr. Giovanna Capizzi is a full Professor of Statistics at the University of Padua. She earned her Ph.D. in Statistics from the University of Padua in 1992. Dr. Capizzi's main research interest is in statistical process monitoring, and she has made significant contributions to the field. she has published extensively in several international peer-reviewed journals, including Statistics and Computing, Technometrics, Journal of Quality Technology, IIE Transactions, and Quality Engineering. Dr. Capizzi serves as an associate editor of Technometrics since 2013, and she is a member of the editorial board of the Journal of Quality Technology since 2014.Quality Engineering11510.1080/08982112.2023.2253891https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2253891?af=RA distribution-free phase II control chart for multivariate individual data with simple post signal diagnostics
https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2311253?af=R
. <br/>. <br/>A distribution-free phase II control chart for multivariate individual data with simple post signal diagnosticsdoi:10.1080/08982112.2024.2311253Quality Engineering2024-02-13T03:58:39ZChase HolcombeMosab AlqurashiSubhabrata Chakrabortia Department of Information Systems, Statistics and Management Science, University of Alabama, Tuscaloosa, Alabamab Department of Quantitative Analysis, King Saud University, Riyadh, Saudi ArabiaChase Holcombe is a PhD candidate in Applied Statistics at the University of Alabama. He holds an MS degree in Applied Statistics from the University of Alabama as well as a BS degree in mathematics and a BBA degree in economics from the University of North Alabama. His primary research interests are statistical process control, nonparametric statistical inference, and robust parametric methods to model and monitor integer-valued "count" processes. He is a member of the American Statistical Association.Mosab Alqurashi is currently an Assistant Professor at the King Saud University (KSU, Saudi Arabia). He received his PhD degree in Applied Statistics from the University of Alabama. He also holds an MSc degree in Applied Statistics with specialization in business analytics from Bowling Green State University (BGSU, USA). His research interests are in statistical process control, nonparametric statistical inference, and operations research.Subhabrata Chakraborti is Professor of Statistics and Robert C. and Rosa P. Morrow Faculty Excellence Fellow at the University of Alabama. He is a Fellow of the American Statistical Association and an Elected member of the International Statistical Institute. His current research interests are Nonparametric and Robust Statistical Inference methods with applications in areas such as Statistical Process Control, Survival/Reliability Analysis and Statistical Computing. He has extensive publications in peer‐review journals and is a co‐author of two books: Nonparametric Statistical Inference (2021), sixth edition, by CRC Press and Nonparametric Statistical Process Control (2019), by John Wiley and Sons. Professor Chakraborti serves as an Associate Editor of Communications in Statistics and Quality Engineering. He is a member of the American Statistical Association.Quality Engineering12110.1080/08982112.2024.2311253https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2311253?af=RA model for failure-time data with two dependent failure modes and prediction of future failures
https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2321839?af=R
. <br/>. <br/>A model for failure-time data with two dependent failure modes and prediction of future failuresdoi:10.1080/08982112.2024.2321839Quality Engineering2024-03-05T04:42:04ZAakash AgrawalDebanjan MitraAyon Gangulya Independent Researcher, Bengaluru, Karnataka, Indiab Indian Institute of Management Udaipur, Rajasthan, Indiac Indian Institute of Technology Guwahati, Assam, IndiaAakash Agrawal is a Data Scientist based out of Bengaluru, Karnataka, India. He graduated with a B.Tech degree from the Indian Institute of Technology (IIT) Guwahati, in 2020. He has also been working as an independent researcher post his graduation from IIT Guwahati. He is currently interested in exploring various problems in survival analysis, including modelling dependent competing risk data.Debanjan Mitra is an Associate Professor in the Quantitative Methods Division at Indian Institute of Management Udaipur, Rajasthan, India. He received his B.Sc. and M.Sc. degrees from the University of Calcutta, in 2006 and 2008, respectively. He earned his Ph.D. from McMaster University, Canada, in 2013. Areas of his research interests include models and methods for reliability and survival data, in particular, statistical analyses of truncated and censored data, competing risks data, failure-time data from reliability systems of various structures, and degradation models.Ayon Ganguly is an Assistant Professor in the Department of Mathematics, Indian Institute of Technology Guwahati. He joined the department in 2016. His primary research area includes lifetime data analysis and censoring schemes. He completed his Ph.D. in Statistics from the Indian Institute of Technology Kanpur in 2013. Before joining the Indian Institute of Technology Guwahati, he taught at the Indian Institute of Information Technology Allahabad. He did post-doctoral research at the Indian Statistical Institute, Chennai, and the Department of Statistics, Savitribai Phule Pune University.Quality Engineering11410.1080/08982112.2024.2321839https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2321839?af=RVerifying a dominant cause of output variation
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2253303?af=R
. <br/>. <br/>Verifying a dominant cause of output variationdoi:10.1080/08982112.2023.2253303Quality Engineering2023-09-11T04:52:42ZMahsa PanahiStefan H. SteinerJeroen De Masta Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canadab Amsterdam Business School, University of Amsterdam, Amsterdam, The NetherlandsMahsa Panahi is Ph.D. candidate in Statistics at the University of Waterloo, Canada. Her email address is mpanahi@uwaterloo.ca.Dr. Stefan H. Steiner is Professor of Statistics at the University of Waterloo, Canada, in the Department of Statistics and Actuarial Science. His email address is shsteiner@uwaterloo.ca.Dr. Jeroen De Mast is Professor of Data-Driven Business Innovation at the University of Amsterdam, The Netherlands. He is also adjunct Professor of Statistics at the University of Waterloo, Canada. His email address is j.demast@uva.nl.Quality Engineering11210.1080/08982112.2023.2253303https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2253303?af=RR&D culture change – A case study
https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2310259?af=R
. <br/>. <br/>R&D culture change – A case studydoi:10.1080/08982112.2024.2310259Quality Engineering2024-02-13T04:00:16ZLynne B. HareStatistical Strategies, LLCLynne Hare is a consulting statistician emphasizing business process improvement in R&D, Manufacturing and other strategic functions. Serving a large client base, he has helped bring about culture change in Research by accelerating speed to the successful launch of new products and processes and in Manufacturing through the reduction of process variation. His former positions include the Director of Applied Statistics at Kraft Foods, Chief of Statistical Engineering at the National Institute of Standards and Technology, Director of Technical Services at Unilever, Manager of Statistical Applications there as well, Statistics Group Leader at Hunt-Wesson Foods and Visiting Professor at Rutgers University. Lynne’s technical expertise includes experimental strategies and design of experiments for Research as well as quality and productivity improvement for Manufacturing. He holds MS and PhD degrees from Rutgers University and an A.B. in mathematics from Colorado College. Lynne is a Fellow of the American Statistical Association and former chairman of its Section on Quality and Productivity and holder of the Gerald J. Hahn Q&P Achievement Award. He is also a Fellow of the American Society for Quality and former chairman of its Statistics Division. The ASQ has awarded him the William G. Hunter and Ellis R. Ott Awards for excellence in quality management. Kraft Foods presented him with the Technology Leadership Award for career accomplishments. He writes a column for Quality Progress Magazine and has numerous publications in technical journals.Quality Engineering1710.1080/08982112.2024.2310259https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2310259?af=RRobust control chart based on mixed-effects modeling framework: A case study in NAND flash memory industry
https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2251570?af=R
. <br/>. <br/>Robust control chart based on mixed-effects modeling framework: A case study in NAND flash memory industrydoi:10.1080/08982112.2023.2251570Quality Engineering2023-09-08T04:13:30ZDaewon YangJinsu ParkHayang ParkSungki HongJongmin KimSeonghui HuhEunkyung KimJaeyong JeongYeonseung Chunga Department of Information and Statistics, Chungnam National University, Daejeon, South Koreab Department of Information and Statistics, Chungbuk National University, Chungcheongbuk-do, South Koreac Samsung Electronics, Gyeonggi-do, South Koread Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Daejeon, South KoreaDaewon Yang is an assistant professor in the Department of Information Statistics at Chungnam National University. He obtained his Ph.D. degree in Statistics from Korea Advanced Institute of Science and Technology. Before joining Chungnam national university, he worked for 1 year and 6 months as a staff engineer at Samsung Electronics. His research interests include statistical process control, Bayesian Nonparametrics, Biostatistics, and high-dimensional data analysis.Jinsu Park is an assistant Professor in the Department of Information Statistics at Chungbuk National University. He obtained his Ph.D. degree in Statistics from Korea Advanced Institute of Science and Technology. His research interests include Bayesian Nonparametrics, spatio-temporal model, and machine learning application in epidemiology.Hayang Park is an engineer at Samsung Electronics. His research interests include statistical process control, product engineering and generalized linear model.Sungki Hong is a staff engineer at Samsung Electronics. His research interests include statistical process control, product engineering and clustering.Jongmin Kim is a principal engineer at Samsung Electronics. His research interests include statistical process control, product engineering and machine learning.Seong-Hui Huh is an executive vice president at Samsung Electronics. His research interests include statistical process control, product engineering and machine learning.Eunkyung Kim is a vice president at Samsung Electronics. His research interests include statistical process control, product engineering and machine learning.Jaeyong Jung is a vice president at Samsung Electronics. His research interests include statistical process control and machine learning.Yeonseung Chung is an Associate Professor in the Department of Mathematical Sciences at Korea Advanced Institute of Science and Technology. She obtained her Ph.D. degree in Biostatistics from University of North Carolina, Chapel Hill. Her research interests include Environmental Epidemiology, Bayesian Nonparametrics, and Biostatistics.Quality Engineering11110.1080/08982112.2023.2251570https://www.tandfonline.com/doi/full/10.1080/08982112.2023.2251570?af=RA primer on predictive maintenance: Potential benefits and practical challenges
https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2331140?af=R
. <br/>. <br/>A primer on predictive maintenance: Potential benefits and practical challengesdoi:10.1080/08982112.2024.2331140Quality Engineering2024-03-25T07:03:55ZHenrik Hviid HansenMurat KulahciBo Friis Nielsena Ørsted A/S, Bioenergy & Thermal Power, Copenhagen, Denmarkb Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmarkc Department of Business Administration, Technology and Social Sciences, Luleå University of Technology, Luleå, SwedenHenrik Hviid Hansen is a senior data scientist at the Danish energy company Ørsted, where he has worked on a PhD project on the predictive maintenance of power plants. His research interests are in the fields of fault detection and diagnosis, remaining useful life prediction, statistical process control, and machine learning for the use in optimizing power plant processes.Murat Kulahci is a professor at the Technical University of Denmark and Luleå University of Technology in Sweden. His research currently focuses primarily on large data analytics for descriptive, inferential, and predictive purposes. Many of his research applications involve high dimensional, high frequency data demanding analysis methods in chemometrics and machine learning. He has been collaborating with various industries in many industrial statistics projects and digital manufacturing.Bo Friis Nielsen is a professor of applied probability in the engineering sciences at the Technical University of Denmark. Besides theoretical contributions to the field of applied probability, he has worked with researchers in transportation and health science. His main contributions concern the theory of uni- and multivariate matrix-exponential distributions.Quality Engineering11210.1080/08982112.2024.2331140https://www.tandfonline.com/doi/full/10.1080/08982112.2024.2331140?af=R