Work

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

Year: 2021

Type: article

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.

Source: Procedia CIRP

DOI: 10.1016/j.procir.2021.03.112

Authors: Simon Cramer, Max Hoffmann, Peter Schlegel, Marco Kemmerling, Robert H. Schmitt

Institution: RWTH Aachen University

Language: English

Topic: Digital Transformation in Industry

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funders: Deutsche Forschungsgemeinschaft, Allianz Industrie Forschung