Integrating manufacturing knowledge with design process to improve quality in aerospace industry

There had been research efforts in the knowledge management and related disciplines devoted to integrating data and knowledge generated from manufacturing activities into the design process. Such efforts focused on approaches for enhancing engineering specifications and supplier related decision making in order to improve manufacturing quality through reducing defects. However, rarely did previous researchers address the ‘Integration’ aspect as part of a centrally-driven systematic workflow that enables collaborative knowledge capture between the internal design teams and manufacturing engineering teams firstly, and also with dispersed supplier teams. The industrial context of this research is discussed in this paper reflecting on the nature of the aerospace industry, which involves heavy reliance on information exchange to optimise designs on a day-to-day basis. This aspect had already been identified by many researchers to be under-addressed and a very significant challenge of collaborative design. The main aim of describing the context is to address the complexity involved in integrating manufacturing data generated internally first, and from suppliers second, within workflow context in order to to design a collaborative framework using knowledge management principles. The complexity also features aspects of product design and manufacturing specifically related to the the aerospace industry which tend to have exceptional functional specifications than other products from other industries. The implications of the proposed approach in the light of high value, low volume and high product lifecycle management challenges is also discussed. This paper also reports findings of an empirical investigation carried out with a leading UK based manufacturer of avionic systems with regards to manufacturing knowledge integration challenges related to improving the design of complex avionic systems, in order to enhance the design process for the business and improve the adaptation of a generic product design knowledge base. The purpose of it is to enable more rich data towards information driven design to improve manufacturing quality through defect reduction strategies and techniques