Robust yield test for a normal production process

Abstract

Testing the performance of a production process is a very serious and important topic in statistical quality control. This article presents a robust yield test to investigate the performance of an industrial production process in the presence of outliers. For this purpose, a new robust estimator of S_pk is introduced to test the production yield for any normal distribution in the presence of various numbers of outliers. Moreover, a Monte Carlo simulation method to estimate the decision-making components is proposed for testing the production yield based on the yield index S_pk by normal data. Meanwhile, this article discusses how well the proposed Monte Carlo method can be used for some non-normal data. Numerical computations of the simulation and real data analyses are provided to explain the proposed method.

Keywords:

• yield analysis
• testing capability
• Monte Carlo simulation
• outliers
• robustness

Acknowledgment

The authors would like to thank anonymous referees for their constructive suggestions and insightful comments, which significantly improved the presentation of this article.

Additional information

Funding

This research was supported by a grant from Ferdowsi University of Mashhad; No. 2/58123.

Notes on contributors

Hamideh Iranmanesh

Hamideh 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: [email protected]

Mehdi Jabbari Nooghabi

Dr 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: [email protected], [email protected]

Abbas Parchami

Dr 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: [email protected]