A Knowledge-Enriched Problem Solving Methodology for the Design Phase of Manufacturing Equipment

During the design phase of large-scale industrial engineering projects, numerous problems usually arise, which are related to the project analysis and methods used in each phase. Such projects are undertaken by multi-disciplinary teams of expert designers and planning managers that often communicate these problems to the members of their team via emails and telephone calls. However, the alignment of efforts towards solving these problems cannot be achieved effectively though these inherently limited communication and collaboration means. In parallel, the operation of manufacturing systems is evolving towards structures that are similar to social networks. The trend is to automatically connect to web-based collaboration platforms in order to search for the appropriate experts to deal with the problem in question. Towards this end, the proposed research work focuses on the development of a knowledge-based method, which is developed into a mobile app, and focuses on providing a collaboration space for reporting, tracking, and solving project-related problems. The methodology adopts concepts from the Root Cause Analysis method, which is further enriched with knowledge reuse features. Already reported and potentially solved problems, as well as other historical data are retrieved from a knowledge repository through advanced indexing techniques in order to support the identification of solutions for newly experienced problems. Results from the interpretation of the natural language that is considered to be used in the problem reporting phase and the accuracy of retrieved solutions are further discussed. Finally, the methodology is validated through a real-life case study obtained from the die construction department of an automotive industry.