Digitalization platform for data-driven quality management in multi-stage manufacturing systems

Marc-André Filz (), Jan Philipp Bosse and Christoph Herrmann
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Marc-André Filz: Technische Universität Braunschweig
Jan Philipp Bosse: Technische Universität Braunschweig
Christoph Herrmann: Technische Universität Braunschweig

Journal of Intelligent Manufacturing, 2024, vol. 35, issue 6, No 14, 2699-2718

Abstract: Abstract Digital transformation is driving the current technological trends in manufacturing. An integral constituent is a communication between machines, between machines and humans, or between machines and products. This extensive communication involves large volumes of data. Many manufacturers apply data analytics (e.g., for quality management or improvement purposes) to translate the data into a business value. However, isolated, rigid, and area-specific IT solutions often carry this out. Today’s complex manufacturing requires quality management approaches that constitute a holistic view of and understanding of process–product interactions along the process chain instead of focusing solely on single processes. A novel platform approach to support quality management in manufacturing systems is proposed in this paper to overcome this deficit. It integrates state-of-the-art concepts of IT with modeling approaches for planning and operation of quality management. A conceptual framework and the technical architecture for implementing a digitalization platform are presented in this regard. Moreover, the approach is validated and implemented within a web application based on a use case of data-driven quality management in electronics production.

Keywords: Quality management; Machine learning; Digital platform; Data analytics; Manufacturing system (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10845-023-02162-9

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