Non-traditional machining processes selection using data envelopment analysis (DEA)

摘要

The generic term ‘non-traditional machining’ (NTM) refers to a variety of thermal, chemical, electrical and mechanical material removal processes which have been developed due to lack of efficiency of the traditional machining processes to generate complex and intricate shapes in materials with ‘high strength-to-weight’ ratio. For effective utilization of the capabilities of different NTM processes, utmost care is needed for the selection of the most suitable process for a given machining application. Due to the lack of experienced experts in the domain of NTM processes, there is a need for a simple scientific/mathematical tool for selecting the most suitable NTM process when a particular shape feature is to be generated on a given work material. This paper focuses on the development of a two-phase decision model in this aspect. In the first phase, the most efficient NTM processes are selected for a given shape feature and work material combination having the best combination of performance parameters with the help of input-minimized-based Charnes, Cooper and Rhodes (CCR) model of data envelopment analysis (DEA). In the second phase, those efficient NTM processes are ranked in descending order of priority using the weighted-overall efficiency ranking method of multi-attribute decision-making (MADM) theory. Two real time machining applications are cited which prove the applicability, versatility and adaptability of this two-phase NTM process selection decision-making model as the results are quite consistent with those as derived by the past researches.