Investigating Critical Process Parameters Using Fuzzy Analytical Hierarchical Process in Casting Process Failure

Abstract

Productivity enhancement of casting process by optimizing the casting process parameters has been a primary focus area of many researchers. It includes optimization of various process parameters in the design phase, through various DOE techniques and simulation software. There have been major shortcomings in these approaches, wherein the data for casting defects in real time were not considered. Real-time investigation of casting failure for several process parameters is a challenge for the foundry industry. Analytical hierarchical process is a decision support technique through which a hierarchical structural model could be generated. There is subjectivity in the retrieval decision because the primary input of the AHP approach was the opinion of industry experts or practitioners. Additionally, this approach considers the validity of the data with constraints on inconsistency. However, there would be an impact on the accuracy of the data and the results if there was a significant amount of uncertainty and doubt, while making a judgement. This has resulted in the development of fuzzy analytic hierarchy process, an analytic hierarchy process (AHP) approach created with fuzzy logic theory. In this context, this study used a hierarchical model that focuses on the casting failure in industries, and accordingly, the model was tested for various process parameters. The outcome of the study provided the priority ranking of the process parameters for various casting failure, in real time through which the critical process parameters were identified in the order.