Circular and cylindrical profile monitoring considering spatial correlations. (January 2020)

• Record Type: Journal Article
• Authors: Zhao, Chen; Du, Shichang; Deng, Yafei; Li, Guilong; Huang, Delin
• Is Part Of: Journal of manufacturing systems. Volume 54(2020)
• Page Start: 35
• Page End: 49
• Publication Date: 2020-01
• Subjects: Circular and cylindrical profiles -- Statistical process control -- Profile monitoring -- Spatial correlations; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2019.11.011
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: A new model combining spatial correlations with circular and cylindrical profiles is proposed to monitoring parts quality. The proposed model can effectively represent the spatial correlations in observations. Control charts for monitoring the parameters and residuals are established based on statistical process control methods. The proposed model is superior to traditional methods in detecting out-of-control parts. Abstract: Geometric specifications are important control objects of mechanical components in modern manufacturing. For instance, circularity and cylindricity are essential indicators of high-precision rotary parts. With an increase in the number of measurement points, traditional statistical process control (SPC) methods cannot be applied in many processes because the measurements are highly correlated. During the past two decades, several studies have focused on profile monitoring. A profile, which describes the relationship between independent and response variables, is suitable for large-scale, complex and high-dimensional data monitoring. However, the issue of spatial correlations in measurement points remains unsolved. Considering spatial correlations, this study focuses on circular and cylindrical profiles and proposes a new method combining a spatial correlation model with control charting. SPC methods are utilized to establish control charts and analyze the control processes. The results of simulation and case study indicate that the proposed method is feasible and effective in monitoring circular and cylindrical profiles and can be extended to other geometric specifications.