Abstract
With the introduction and increased use of newer and harder materials such as titanium, stainless steel, high-strength temperature-resistant (HSTR) alloys, fibre-reinforced composites, and ceramics in the aerospace, nuclear, missile, turbine, automobile, tool, and die-making industries, a different class of machining processes has emerged. Instead of employing the conventional cutting tools, these non-traditional machining (NTM) processes use energy in its direct form to remove materials from the workpiece. Selection of the most suitable NTM process for machining a shape feature on a given work material requires consideration of several factors. A combined method using the ‘technique for order preference by similarity to ideal solution’ (TOPSIS) and an analytical hierarchy process (AHP) is proposed to select the most appropriate NTM process for a specific work material and shape feature combination, while taking into account different attributes affecting the NTM process selection decision. This paper also includes the design and development of a TOPSIS-AHP-method-based expert system that can automate the decision-making process with the help of a graphical user interface and visual aids. The expert system not only segregates the acceptable NTM processes from the list of the available processes, but also ranks them in decreasing order of preference. It also helps the user as a responsible guide to select the best NTM process by incorporating all the possible error-trapping mechanisms.