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Statistical process monitoring in the era of smart manufacturing

One of the focuses of smart manufacturing is to create manufacturing intelligence from real-time data to support accurate and timely decision-making. Therefore, data-driven statistical process monitoring is expected to contribute significantly to the advancement of smart manufacturing. In this work, a roadmap of statistical process monitoring (SPM) is presented and we propose statistics pattern analysis (SPA) as a promising SPM tool for smart manufacturing. The rationale behind SPA is discussed and compared with other SPM methods. Simulated and industrial case studies are presented to demonstrate the superior performance of SPA in fault detection and diagnosis. The potential capabilities of SPA to address the characteristics of the big data from smart manufacturing are discussed.