Review of Quality Engineering Technologies in the Context of Industry 4.0
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Date
2021-05
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The Ohio State University
Abstract
Quality engineering is arguably in crisis. The search phrase "quality engineering" has been trending downward for over a decade and traditional methods such as lean six sigma are garnering reduced interest. This review seeks to reinvigorate quality engineering by studying Quality 4.0, i.e., quality for smart manufacturing. Following questions are addressed: (i) What is Quality 4.0? (ii) What are its impacts on operational performance? (ii) What roles can quality researchers usefully play in relationship to Industry 4.0 and IIOT? The results suggest a growing consensus that the body of knowledge for quality engineers is rapidly changing to emphasize most notably machine learning. Another conclusion is that the topics identified by ASQ in the body of knowledge are relatively unexplored by research authors. These include methods to shift attention from variation reduction in operators to automatic process design for quality, the monitoring and design of self-managing machines, and an increased emphasis on methods for big data analytics. Also, topics relating to dashboards and software for IIOT such as PTC Thingworx, Siemens Mindsphere, and Power BI are conspicuously absent.
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Keywords
Quality Engineering, Industry 4.0, Internet of Things, Smart Manufacturing, Industrial Internet of Things(IIOT)