Professor of Mechanical Engineering and Smart Structures, School of Computing Engineering and Mathematics, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
Abstract—Because of global competition, manufacturers are compelled to produce the products with high quality and short delivery times. In manufacturing, sheet metal industries has major role to play for cost effective solution. Pulley used for power transmission in automobile cooling application is a sheet metal product. An attempt has been made here to shorten the delivery time by developing a Knowledge-Based System (KBS) for sheet metal product. Different customers have different dimensional specification for the said pulley. Also frequent design changes make it difficult for the manufacturer to develop process plan, production schedules and in turn reduce delivery time. Some decision support system requires helping in development of process plan as well as for production scheduling. KBS is developed here keeping these requirements in mind. Data related to process sequence to produce the part has been gathered and stored in required format. An inference engine is developed to get the process sequence for the production of the pulley. It also gives parametric CAD models for each process sequence stage, which can be used for the development of production drawings. The CAD data generated can also be used for FEA analysis
Index Terms—Knowledge-based system, Decision support system, Process sequence design, Deep drawing
Cite: M K Chudasama and H K Raval, "Development of Knowledge-Based System for Process Sequence Design for Production of Pulley used in Automobile Cooling Applications," International Journal of Mechanical Engineering and Robotics Research, Vol.1, No. 1, pp. 63-75, April 2012.
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