An EWMA and region growing based control chart for monitoring image data

ABSTRACT

The widespread application of machine vision system promotes the development of image-based statistical process control methodologies to improve the utilization of image data. Previous research has focused on either identification of fault size and/or location or detection of fault occurrence. There is limited research on both fault detection and identification. In this paper, an EWMA and region growing based control charting method is proposed for monitoring images of industrial products of which quality is either characterized by uniformity (e.g. LCD monitors) or a specific pattern (e.g. manufactured tiles). Simulation results show that the proposed method is not only effective in quick detection of the fault but also accurate in estimating the fault size and location. An experimental study is also provided to highlight how practitioners can implement the proposed method in applications.

KEYWORDS:

• Machine vision system
• image data
• high dimension
• statistical process control
• region growing algorithm
• EWMA based statistic

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by the National Natural Science Foundation of China [grant numbers 71871204].

Notes on contributors

Ling Zuo

Ling Zuo is a lecturer in the School of Economics and Management at Shanghai Maritime University in China. She received her PhD in management science from Tianjin University in 2016. Her research interests include SPC and quality improvement. Her research appears in International Journal of Production Research, Journal of Intelligent Manufacturing and Journal of Systems Engineering (Chinese).

Zhen He

Zhen He is a professor in the College of Management and Economics at Tianjin University in China. He received his PhD in management science from Tianjin University in 2002. His research interests include SPC, quality improvement and Six Sigma management. His research appears in European Journal of Operational Research, International Journal of Production Economics, International Journal of Production Research, Journal of Applied Statistics, Quality and Reliability Engineering International, Total Quality Management and Business Excellence, Quality Progress et al.

Min Zhang

Min Zhang is a professor in the College of Management and Economics at Tianjin University in China. She received her PhD in management science from Tianjin University in 2006. Her research interests include SPC and quality improvement. Her research appears in International Journal of Production Economics, International Journal of Production Research, Quality and Reliability Engineering International, Production Planning & Control et al.