Nontraditional machining processes selection using evaluation of mixed data method

作者：Chatterjee Prasenjit; Chakraborty Shankar^*

来源：International Journal of Advanced Manufacturing Technology, 2013, 68(5-8): 1613-1626.

DOI：10.1007/s00170-013-4958-1

• Nontraditional machining process
• Evaluation of mixed data method
• Cardinal data
• Ordinal data

Traditional edged cutting tool-based machining processes are now being continuously replaced by nontraditional machining (NTM) processes so as to generate complex and intricate shapes on advanced and harder materials, like titanium, stainless steel, high-strength temperature-resistant alloys, fiber-reinforced composites, and engineering ceramics. These NTM processes, while using energy in its direct form for removing materials from the workpiece surfaces, have the capabilities of meeting some higher level requirements, such as low tolerance, high surface finish, higher production rate, automated data transmission, miniaturization, etc., and are also quite suitable in the areas of micro- and nano-machining. Selection of the most appropriate NTM process to generate a desired shape feature on a given work material is often a challenging task as it involves consideration of diverse machining characteristics and performance of the NTM processes. This paper explores in details the applicability, suitability, and potentiality of evaluation of mixed data method for solving the NTM process selection problems. Three illustrative examples are presented, which validate the usefulness of this method. The observed results exactly corroborate with those obtained by the past researchers.

• 出版日期2013-9