Economic-statistical design of variable parameters s chart

ABSTRACT

In this paper, the economic-statistical design of the variable parameters (VP) s chart is investigated, where all the design parameters of the s chart are allowed to vary between two values as a function of the most recent process information. The optimal design parameters of the VP s chart are derived based on the economic and statistical criteria. The economic-statistical design is performed by minimizing the cost function with the imposed in-control and out-of-control statistical constraints. The cost of the economic-statistical design is slightly higher than the economic design due to the imposed statistical constraints. The effect of cost and process parameters on the optimal design parameters, statistical performance and minimum expected cost is examined and discussed. The comparison results indicate that the cost of the VP s chart is lower than the variable sample size and sampling interval (VSS) s chart, the variable sampling interval (VSI) s chart, the variable sample size (VSS) s chart and the standard s chart.

KEYWORDS:

• Economic-statistical design
• s chart
• variable parameters

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Ming Ha Lee

Ming Ha Lee is a Senior Lecturer in the Faculty of Engineering, Computing and Science at Swinburne University of Technology Sarawak Campus, Malaysia. She received her BTech degree from Universiti Sains Malaysia, her MSc degree from Universiti Putra Malaysia and her PhD degree from Universiti Sains Malayisa.

Michael B. C. Khoo

Michael B. C. Khoo is a Professor in the School of Mathematical Sciences, Universiti Sains Malaysia (USM). He received his PhD in Applied Statistics in 2001 from USM. His research interest is in statistical process control. He has published numerous papers on control charts in international journals. He is a member of the American Society for Quality and serves as a member of the editorial boards of several International journals.

Xinying Chew

XinYing Chew is a Senior Lecturer in the School of Computer Sciences, Universiti Sains Malaysia. She holds a PhD in statistical quality control from University Sains Malaysia. She is a certified trainer with Human Resources Development Fund (HRDF)/Pembangunan Sumber Manusia Berhad (PSMB), Malaysia. She is also the trainer for MDEC-Intel AI Academy Program. Her areas of research are in advanced analytics and statistical quality/process control.