Abstract
In many process control applications, the quality of a process or a product can be characterized by a functional relationship between a response variable and one or more explanatory variables which is typically referred to as a profile. Such profiles can be expressed by a linear or a non-linear model. On the other hand, for an in-control process, capability indices are used for process quality improvement. In this article, we propose a method to measure the process capability when the quality of the process is characterized by a Poisson regression profile. The performance of the proposed index is evaluated through simulations studies. Two real data examples illustrate this method.
Acknowledgments
The authors would like to thank the Editor and the referees for their useful comments which resulted in improving the quality of this article.
Disclosure statement
No potential conflict of interest was reported by the authors.
Additional information
Notes on contributors
Vasileios Alevizakos
Vasileios Alevizakos received his MSc in Mathematical Modelling in Modern Technologies and Financial Engineering in 2018 from the National Technical University of Athens. He is currently a PhD candidate at the National Technical University of Athens. His research interests are statistical process control, process capability analysis and robust parameter design.
Christos Koukouvinos
Christos Koukouvinos is a Professor at the National Technical University of Athens, Department of Mathematics. He received his Bachelor in Mathematics in 1983 and PhD in 1988 in Statistics both from the University of Thessaloniki. He is the author of numerous papers in the field of statistics and combinatorics and he served on the editorial board of 10 related journals and a guest editor for three special issues. He was awarded the prestigious Hall Medal of the ICA in 1996. He is a fellow of the ICA and a member of the Council of ICA from 2000–2003. His research interests include statistical experimental and optimal designs, biostatistics, statistical quality control, and combinatorial designs.
Philippe Castagliola
Philippe Castagliola is graduated (PhD 1991) from the UTC (Université de Technologie de Compiègne, France). He is currently 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 the Journal of Quality Technology, Communications in Statistics, Quality Technology and Quantitative Management and for the International Journal of Reliability, Quality and Safety Engineering. His research activity includes developments of new Statistical Process Monitoring techniques.