GA-AHP Method to support robotic polishing process planning

Wang, Ke; Ding, Lian; Dailami, Farid; Matthews, Jason

Abstract

The finishing stage of mould manufacturing is generally completed via mechanical polishing, manual conducted. Not only is this the most expensive phase of the process but also is currently struggling with a deficit of skilled workers. To address these issues, and support the wider needs of Industry 4.0, the manufacturing community has investigated robotic technologies to support the polishing process. The work reported here, investigating the polishing process planning and optimisation for mould manufacture is part of a larger project aiming to automate 80% of the current manual process. Presented in this article is an optimization strategy for robotic polishing process sequencing aiming at satisfying polishing sequence rules and shortest polishing time simultaneously. A hybrid approach combining both genetic algorithm (GA) and analytical hierarchical process (AHP) is proposed based on the specific characterises of polishing process sequencing. A multi-objective fitness function is defined using AHP including the calculation of polishing time and evaluation of polishing process rules. The proposed GA-based process sequencing has been successfully demonstrated on test piece examples.

Citation

Wang, K., Ding, L., Dailami, F., & Matthews, J. (2022). GA-AHP Method to support robotic polishing process planning. Digital Manufacturing Technology, 2(2), 23-44. https://doi.org/10.37256/dmt.2220221513

• Journal Article Type: Article
• Acceptance Date: Jul 5, 2022
• Online Publication Date: Aug 8, 2022
• Publication Date: Aug 8, 2022
• Deposit Date: Dec 7, 2022
• Publicly Available Date: Dec 8, 2022
• Journal: Digital Manufacturing Technology
• Print ISSN: 2810-9309
• Electronic ISSN: 2810-9309
• Peer Reviewed: Peer Reviewed
• Volume: 2
• Issue: 2
• Pages: 23-44
• Series ISSN: 2810-9317
• DOI: https://doi.org/10.37256/dmt.2220221513
• Keywords: Computer-aided process planning; polishing rules; genetic algorithm; robotic; AHP
• Public URL: https://uwe-repository.worktribe.com/output/10226929
• Publisher URL: https://ojs.wiserpub.com/index.php/DMT/article/view/dmt.v2i22022.23-44