Fortschritte im Automobilbau
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Modeling in the Squeeze Casting Process – Current Status and Future Perspectives

Manjunath Patel GC, Krishna P and Parappagoudar MB

The growing demand in today's competitive manufacturing environment has encouraged the researchers to develop and apply modeling tools. The development and application of modeling tools help the casting industries to significantly increase productivity and casting quality. Till date there is no universal standard available to model and optimize any of the manufacturing processes. However the present work discusses the advantages and limitations of some conventional and non-conventional modeling tools applied for various casting processes. In addition the research effort made by various authors till date in modeling and optimization of the squeeze casting process has been reported. Furthermore the necessary steps for prediction and optimization are highly lightened by identifying the trends in the literature. Ultimately this research paper explores the scope for future research in online control of the process by automatically adjusting the squeeze cast process parameters through reverse prediction by utilizing the soft computing tools namely, Neural Network, Genetic Algorithms, Fuzzy-logic Controllers and their different combinations. The present work also proposed a detailed methodology, starting from the selection of process variables till the best process variable combinations for extreme values ​​of the outputs responsible for better product quality using experimental, prediction and optimization methodology.