Automated generation of engineering rationale, knowledge and intent representations during the product life cycle

One of the biggest challenges in engineering design and manufacturing environments is the effective capture of and decoding of tacit knowledge. Fundamental to Life Cycle Engineering is the capture of engineering information and knowledge created at all stages of the product development process, from conceptual design through to product support and disposal. Consider this — the amount of vital information and knowledge lost when key design personnel retire — hence the need to capture meta-cognitive task-related strategies, particularly to support knowledge reuse and training. Many methods have been tried and tested with the successful few found to be very time consuming and expensive to implement and carry out; consequently, there is a need to investigate alternative paradigms for knowledge and information capture. This paper reports on a current industrial case study on knowledge capture methods employed by industrial partners in the design and manufacture of a variety of electro-mechanical products. The results suggest the need for new kinds and forms of knowledge capture methods and representation, particularly those associated with individual design engineering tasks. Following the findings, the paper presents a knowledge capture methodology for automatic real-time logging, capture and post-processing of design data from a virtual reality design system. Task-based design experiments were carried out with industrial partners to demonstrate the effective, unobtrusive and automatic capture and representation of various forms of design knowledge and information. Qualitative and quantitative evaluation of knowledge representations were also performed to determine which method was most effective at conveying design knowledge and information for other engineers.