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

Year: 2024

Type: article

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.

Source: Proceedings of the Design Society

DOI: 10.1017/pds.2024.220

Authors: Rafael Parzeller, Dominik Koziol, Tizian Dagner, Detlef Gerhard

Institutions: Siemens (Germany), Ruhr University Bochum

Language: English

Topic: Manufacturing Process and Optimization

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid:

OpenAlex ID: W4396956346

FWCI: 1.908

Cites: 17

Cited by: 9

Related to: 10