Abstract
Identification of the most appropriate non-traditional machining (NTM) process to generate a shape feature with the desired dimensional accuracy and surface finish in a work material for a given end application is a complex decision making task. It involves consideration and analysis of the machining capabilities and characteristics of each of the NTM processes. In order to evaluate the performance of the NTM processes with respect to their various characteristics, the opinions of the concerned process engineers are often sought which are usually expressed in terms of ambiguous/subjective data. Rough numbers are utilized to aggregate the judgments of those process engineers and express their observations while dealing with the impreciseness in the data. In this paper, an endeavour is put forward to solve two real time NTM process selection problems, i.e. generation of standard through holes in glass and deep through cavities in titanium while integrating rough numbers with multi-attributive border approximation area comparison (MABAC) method. The relative importance of various NTM process characteristics is determined using rough entropy technique. Rough set theory acts as an information aggregation procedure, while MABAC helps in ranking of the candidate NTM processes for a specified machining application. Ultrasonic machining emerges out as the best suited NTM process for generation of standard through holes in glass, while deep through cavities in titanium can be most efficiently generated using plasma arc machining process.
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