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Towards a flexible process-independent meta-model for production data

Procedia CIRP, vol. 99, pp. 586–591

Abstract

Data integration is a considerable challenge when investigating information sources from a multi-step manufacturing process. The interpretation of the process data profoundly depends on the incurred meta-data. However, during most data aggregating processes along the production chain, accompanying meta-information of vital importance is lost. To address this shortcoming, we propose a flexible and process-independent meta-model for efficient data integration for multi-step manufacturing processes. The product-oriented model unites process- and meta-data to reflect their mutual relationships within the manufacturing process. The context provided by the meta-information enables automatic data analysis for Predictive Quality applications in a cross-company setting.

Authors 5

  1. RWTH Aachen University

    Affiliation as printed

    RWTH Aachen University, Laboratory for Machine Tools and Production Engineering, Campus-Boulevard 30, 52074 Aachen, Germany

  2. RWTH Aachen University

    Affiliation as printed

    RWTH Aachen University, Institute of Information Management in Mechanical Engineering (IMA), Dennewartstr. 27, 52068 Aachen, Germany

  3. RWTH Aachen University

    Affiliation as printed

    RWTH Aachen University, Laboratory for Machine Tools and Production Engineering, Campus-Boulevard 30, 52074 Aachen, Germany

  4. RWTH Aachen University

    Affiliation as printed

    RWTH Aachen University, Institute of Information Management in Mechanical Engineering (IMA), Dennewartstr. 27, 52068 Aachen, Germany

  5. RWTH Aachen University

    Affiliation as printed

    RWTH Aachen University, Laboratory for Machine Tools and Production Engineering, Campus-Boulevard 30, 52074 Aachen, Germany

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References 21