Optimization techniques applied to single point incremental forming process for biomedical application

Single point incremental forming (SPIF) process has the potential to replace conventional sheet forming process in industrial applications. For this, its major defects, especially poor geometrical accuracy, should be overcome. This process is influenced by many factors such as step size, tool diameter, and friction coefficient. The optimum selection of these process parameters plays a significant role to ensure the quality of the product. This paper presents the optimization aspects of SPIF parameters for titanium denture plate. The optimization strategy is determined by numerical simulation based on Box–Behnken design of experiments and response surface methodology. The Multi-Objective Genetic Algorithm and the Global Optimum Determination by Linking and Interchanging Kindred Evaluators algorithm have been proposed for application to find the optimum solutions. Minimizing the sheet thickness, the final achieved depth and the maximum forming force were considered as objectives. For results evaluation, the denture plate was manufactured using SPIF with the optimum process parameters. The comparison of the final geometry with the target geometry was conducted using an optical measurement system. It is shown that the applied method provides a robust way for the selection of optimum parameters in SPIF.