@inproceedings{b4f29d7ff9c54aeaab83ff469e6e8abc,
title = "Fuzzy-TOPSIS Hybrid Technique for Multi-response Optimization in Nonconventional Machining of Gears",
abstract = "An optimum combination of process parameters is essential to attain the desired product quality and process productivity in manufacturing. Advanced or nonconventional machining of gears is in trend these days. This paper reports the optimization of wire-EDM parameters by Fuzzy-TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) integrated hybrid multi-criteria decision making technique. Gear manufacturing by wire-EDM involves conflicting interests such as gear quality and process productivity. For a better gear quality, lower values of surface roughness and micro-geometry errors are desirable, whereas for higher productivity, higher values of gear cutting rate is desirable. This multi-criteria problem has been solved in this work. After cutting gears from wire-EDM via a set of twenty-nine experiments, Fuzzy-TOPSIS has been used to optimize its process parameters. An optimum combination of Voltage – 10 V, Pulse-on Time – 0.8 µs, Pulse-off Time – 170 µs and Wire Feed Rate – 15 m/min has been obtained for simultaneous improvement of gear quality and wire-EDM productivity has been achieved. The outcome of this work provides a set of wire-EDM parameters for ready industrial use to manufacture quality gears with good productivity. Further, it is hoped that the scholars and researchers will utilized the Fuzzy-TOPSIS to solve MCDM problems for other manufacturing processes.",
keywords = "Fuzzy, Gear, Productivity, Quality, TOPSIS, Wire-EDM",
author = "Phokane, {Thobadingoe Craven} and Kapil Gupta",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference on Smart Technologies in Urban Engineering, STUE 2022 ; Conference date: 09-06-2022 Through 11-06-2022",
year = "2023",
doi = "10.1007/978-3-031-20141-7_45",
language = "English",
isbn = "9783031201400",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "489--501",
editor = "Olga Arsenyeva and Tatiana Romanova and Maria Sukhonos and Yevgen Tsegelnyk",
booktitle = "Smart Technologies in Urban Engineering - Proceedings of STUE-2022",
address = "Germany",
}