Knowledge graphs for the enhancement of process planning in manufacturing
Year: 2024
Type: article
Abstract: The increasing complexity of modern manufacturing systems, driven by demands for sustainability, shorter product life cycles, and greater customization, necessitates frequent reconfiguration and redesign of production processes. In this context, knowledge about parameter interdependencies is crucial. Additionally, simulations play a vital role by enabling virtual testing of various parameter configurations to optimize key performance indicators such as energy consumption, emissions, processing time, and costs. This project report presents an integrated approach to enhance process planning by incorporating semantic models that describe process parameter interdependencies. Furthermore, we describe a concept for automating the generation of simulation sequences, thereby reducing the complexity and effort involved in manual planning. The combination of these approaches is demonstrated using a web-based application, showcasing the potential to support efficient and sustainable manufacturing practices.
Source: OpenHSU
DOI: 10.24405/16792
Authors: Reif, Jonathan Tobias, Jeleniewski, Tom Robin, Gehlhoff, Felix, Fay, Alexander, Hildebrandt, Constantin
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6907376824
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