59562 - Knowledge-Based Self-Adaption of Product and Process Design in Turbomachinery Manufacturing
Early and efficient harmonization between product design and manufacturing represents one of the most challenging tasks in engineering. Concepts such as simultaneous engineering aim for a product creation process, which addresses both, functional requirements as well as requirements from production. However, existing concepts mostly focus on organizational tasks and heavily rely on the human factor for the exchange of complex information across different domains, organizations or systems.
Nowadays product and process design make use of advanced software tools such as computer-aided design or manufacturing systems (CAD/CAM). Modern systems already provide a seamless integration of both worlds in a single digital environment to ensure a continuous workflow. Yet, for the holistic harmonization between product and process design, the following aspects are missing:
· The virtual environment does not provide a complete and evaluated digital twin of the component; this applies especially to the manufacturing environment
· Due to the lag of process and part information (digital twin) in the virtual environment a self-adaption of product and process design based on suitable assessment and optimization approaches is hindered
· Systematic long-term data analytics across different product and process designs with the ultimate goal to transfer knowledge from one product to the next is not considered
This paper presents a simulation approach which couples product design (CAD), process design (CAM), process simulation (digital twin), and optimization (self-adaption) in a single virtual environment. The approach provides insights into correlations and dependencies between input parameters of product/process design and the process output. The insights allow for a knowledge-based self-adaption, tackling well-known optimization issues such as parameter choice or operation sequencing. First results are demonstrated using the example of a blade integrated disk (blisk).
Knowledge-Based Self-Adaption of Product and Process Design in Turbomachinery Manufacturing
Paper Type
Technical Paper Publication
Description
Session: 18-05 Digitization, Testing and Validation
Paper Number: 59562
Start Time: June 11th, 2021, 02:15 PM
Presenting Author: Philipp Ganser
Authors: Philipp Ganser Fraunhofer Institute for Production Technology IPT
Markus Landwehr Fraunhofer Institute for Production Technology IPT
Sven Schiller Fraunhofer Institute for Production Technology IPT
Christopher Vahl Fraunhofer Institute for Algorithms and Scientific Computing SCAI
Sebastian MayerFraunhofer Institute for Algorithms and Scientific Computing SCAI
Thomas Bergs Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University