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Edge computing-based virtual measuring machine for process-parallel prediction of workpiece quality in metal cutting

Procedia CIRP, vol. 107, pp. 363–368

Abstract

Digital process twins enable in-line quality inspection and root cause analysis, thus sustainably optimizing the production ramp-up and quality control cycle. Current approaches reply on expensive computing units or platforms to perform material removal simulations followed by virtual metrology. This raises deployment costs and conflicts with industrial edge devices. In this paper, a novel analytical approach is proposed to build an edge computing-based digital twin of machining processes for the process-parallel prediction of workpiece tolerances by leveraging machine internal signals and contextualizing metadata sources along the digital process chain, i.e., the digital thread. This concept is validated with the results of a state-of-the-art digital process twin and conventional measurement data from a coordinate measuring machine.

Authors 4

  1. RWTH Aachen University

    Affiliation as printed

    Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University, Steinbachstraße 19, 52074, Aachen, Germany

  2. RWTH Aachen University

    Affiliation as printed

    Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University, Steinbachstraße 19, 52074, Aachen, Germany

  3. RWTH Aachen University

    Affiliation as printed

    Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University, Steinbachstraße 19, 52074, Aachen, Germany

  4. RWTH Aachen University · Fraunhofer Institute for Production Technology IPT

    Affiliation as printed

    Fraunhofer Institute for Production Technology IPT, Steinbachstraße 17, 52074, Aachen, Germany

    Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University, Steinbachstraße 19, 52074, Aachen, Germany

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