Identified research directions for using manufacturing knowledge earlier in the product life cycle

Abstract

Design for manufacturing (DFM), especially the use of manufacturing knowledge to support design decisions, has received attention in the academic domain. However, industry practice has not been studied enough to provide solutions that are mature for industry. The current state of the art for DFM is often rule-based functionality within computer-aided design (CAD) systems that enforce specific design requirements. That rule-based functionality may or may not dynamically affect geometry definition. And, if rule-based functionality exists in the CAD system, it is typically a customisation on a case-by-case basis. Manufacturing knowledge is a phrase with vast meanings, which may include knowledge on the effects of material properties decisions, machine and process capabilities or understanding the unintended consequences of design decisions on manufacturing. One of the DFM questions to answer is: How can manufacturing knowledge, depending on its definition, be used earlier in the product life cycle to enable a more collaborative development environment? This paper will discuss the results of a workshop on manufacturing knowledge that highlights several research questions needing more study. This paper proposes recommendations for investigating the relationship of manufacturing knowledge with shape, behaviour and context characteristics of a product to produce a better understanding of what knowledge is most important. In addition, the proposal includes recommendations for investigating the system-level barriers to reusing manufacturing knowledge and how model-based manufacturing may ease the burden of knowledge sharing. Lastly, the proposal addresses the direction of future research for holistic solutions of using manufacturing knowledge earlier in the product life cycle.

Keywords:

• knowledge management
• multi-criteria decision-making
• design for manufacturing
• collaborative engineering
• model-based manufacturing

Acknowledgements

We wish to thank PDES, Inc. and its membership for the support and time dedicated to the workshop. We also wish to thank Allison Barnard Feeney, Albert Jones, Vijay Srinivasan and the peer reviewers for their review and comments.

Notes

The work presented in this paper is an official contribution of the National Institute of Standards and Technology (NIST) and not subject to copyright in the United States. Certain commercial systems may be identified in this paper. Such identification does not imply recommendation or endorsement by NIST. Nor does it imply that the products identified are necessarily the best available for the purpose.

1 http://www.pdesinc.org

2 Socio-technical refers to the interaction between human behaviours and infrastructure.