Multi-response optimization in laser processing technologies by applying desirability function approach and response surface methodology based on grey relation analysis

Laser processing technologies are among the leading industry technologies for efficient and economical processing of a wide spectrum of engineering materials. The determination of optimal parameter settings with respect to multiple and opposite process performances is of great practical importance in laser processing technologies. This paper discusses, analyzes, and compares two main approaches for multi-response optimization (MRO) in engineering, that is, desirability function approach (DFA) and grey relation analysis (GRA), while solving five case studies, covering different laser processing technologies, such as cutting, drilling, welding, micro-channeling, and cladding. In each case study the MRO solutions obtained with two competitive approaches were assessed using the relative target deviation (RTD) criterion. Analysis of the obtained MRO solutions and comparative analysis with results from previous studies indicate that the integrated RSM-GRA provide similar and comparable solutions with the hybrid Taguchi method and GRA, while DFA proved to be a better and more promising approach for solving MRO in laser processing technologies. Some specific features, limitations, and possibilities of MRO approaches were also discussed.