Modelling and multi-objective optimization of ultrasonic inserting parameters through fuzzy logic and genetic algorithm

As the usage of plastic components has increased in various industries, the methods for fastening have increased rapidly. When the plastic components are fastened by self-tapping screws or bolts, failure occurs because of stripped threads or plastic creep. In these circumstances, threaded metal inserts provide improved joint performance and ability to assemble and disassemble the components without degrading them. Even though many techniques such as insert moulding, thermal insertion and cold insertion are available for joining thermoplastic material with metal insert, ultrasonic insertion is one of the most preferred processes because of the shorter cycle time usually less than a second, possibility of simultaneous installation of the multiple inserts and large-scale automation possibilities for higher production operations. The technical problems faced by the industries in ultrasonic insertion process are poor insertion quality which affects the function of the product. These problems arise because of the improper selection of insertion parameters. The objective of this paper is to optimize the ultrasonic insertion parameters for improving the quality of joint through non-traditional optimization techniques. Response surface methodology (RSM) is used to design the experiments, and then pullout strength and stripping torque are measured. Data obtained from the measurement are utilized to develop a nonlinear equation between the responses and predictors, and optimal combinations of insertion parameters are found out by fuzzy logic and genetic algorithm (GA) approach. From the confirmatory test, it was observed that the fuzzy logic yields better output results than GA.