A decision support methodology for embodiment design and process chain selection for hybrid manufacturing platforms

Gleadal, Andrew; Vladov, Nikola; Segal, Joel; Ratchev, Svetan; Plasch, Matthias; Kimmig, Daniel; Dickerhof, Markus

Abstract

This paper presents a methodology for the transformation of a product concept into a detailed design and manufacturing process chain for hybrid manufacturing platforms. Hybrid platforms offer new capabilities and opportunities for product design. However, they require high levels of process expertise for effective design and effective process selection. Design for hybrid manufacture is challenging as there is a requirement to understand a number of technologies, which may be highly varied. To address this challenge, a knowledge-based decision support system developed in this paper enables manufacturing expertise to be integrated into procedures for product design and process chain selection. This formalised numerical methodology is able to consider a wider range of varied manufacturing processes than any previous study. A feature-based design method is developed, which guides the designer towards an optimised product design during the embodiment design phase, and a process chain selection program is utilised to enable the effective analysis of a product design based on product evaluation criteria. The methodology has been successfully applied to the design of an LED product with internal geometries and electronics.

Citation

Gleadal, A., Vladov, N., Segal, J., Ratchev, S., Plasch, M., Kimmig, D., & Dickerhof, M. (2016). A decision support methodology for embodiment design and process chain selection for hybrid manufacturing platforms. International Journal of Advanced Manufacturing Technology, 87(1-4), 553-569. https://doi.org/10.1007/s00170-016-8514-7

• Journal Article Type: Article
• Acceptance Date: Feb 12, 2016
• Online Publication Date: Feb 24, 2016
• Publication Date: Oct 1, 2016
• Deposit Date: Aug 29, 2018
• Electronic ISSN: 0268-3768
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 87
• Issue: 1-4
• Pages: 553-569
• DOI: https://doi.org/10.1007/s00170-016-8514-7
• Public URL: https://nottingham-repository.worktribe.com/output/1108816
• Publisher URL: https://link.springer.com/article/10.1007%2Fs00170-016-8514-7
• Related Public URLs: http://www.scopus.com/inward/record.url?eid=2-s2.0-84959129067&partnerID=40&md5=edef53f6caaacc3a593c5a102af532a0