Knowledge modelling for the laser beam welding process in the aircraft industry

The Laser Beam Welding (LBW) process offers the possibility of manufacturing joints from most light metals and their combinations, as well as simplifying and integrating the fuselage structure to reduce weight and cost, which are the main concerns of the modern aircraft industry. However, there has been little published knowledge detailed on the LBW process in the aircraft industry yet, which has limited its dissemination. Hence, there is a need to capture knowledge about the LBW process in the aircraft industry for its wider and more effective usage. This research aims to develop a knowledge model of the LBW process in the aircraft industry to improve structure design and process planning. The main objectives are to: (i) identify the methods and tools for knowledge capture and representation; (ii) identify the considerations of structure design and process planning for LBW; (iii) capture the knowledge about structure design and process planning in the form of rules and recommendations, and represent them with Unified Modelling Language (UML); (iv) apply the captured knowledge to a fuselage panel of a commercial aircraft; (v) validate the developed model through case study and expert judgement. These objectives were achieved through the adoption of a four-phase research methodology: understanding the context, data collection and analysis, knowledge model development and validation. The captured knowledge in the form of rules and recommendations has developed an understanding of the LBW process in the aircraft industry and improved the structure design and process planning. The handbook developed based on skin-stringer connection guides designers and engineers directly to developing Laser Beam Welded fuselage panels. This research project has contributed to a wider and more effective use of LBW in the aircraft industry. The procedure of knowledge modelling which includes knowledge identification, capturing and representation, as well as the methods and tools adopted for these stages can be applied to other process knowledge modelling.