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Knowledge Base Repository

In addition to research papers, the Design Society is developing several valuable resources for those interested in the study of design. These include a repository of PhD theses, a library of case studies and transcripts of design activities, and an archive of our newsletters. Please note that these resources are accessible exclusively to Design Society members.

Automating the assembly planning process to enable design for assembly using reinforcement learning

Rafael Parzeller (1,2), Dominik Koziol (1), Tizian Dagner (1), Detlef Gerhard (2)

Type:
Papers
DS 129: Proceedings of the DESIGN2024 18th International Design Conference
Year:
2024
Editor:
Mario Štorga, Stanko Škec, Tomislav Martinec, Dorian Marjanović, Neven Pavković, Marija Majda Škec
Author:
Rafael Parzeller (1,2), Dominik Koziol (1), Tizian Dagner (1), Detlef Gerhard (2)
Series:
DESIGN
Institution:
1: Siemens AG, Germany; 2: Ruhr-Universität Bochum, Germany
Section:
Artificial Intelligence and Data-Driven Design
Page(s):
2179-2186
DOI number:
10.1017/pds.2024.220
ISSN:
2732-527X (Online)
Abstract:
This paper introduces a new concept for the automation of the assembly planning process, to enable Design for Assembly (DfA). The approach involves the application of reinforcement learning (RL) to assembly sequence planning (ASP) based on a 3D-CAD model. The ASP algorithm determines assembly sequences through assembly by disassembly. The assembly sequence is then used for the generation of subassemblies by considering the product contact information. The approach aims to support the creation of the manufacturing bill of materials (MBOM) by automating the assembly planning process.
Keywords:
design for x (DfX), artificial intelligence (AI), assembly sequence planning, subassembly identification
18th International Design Conference (DESIGN 2024)
Conferences

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