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Combined Compromise Solution for Machining Performance Optimization of Modified Polymer Composite

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Advances in Forming, Machining and Automation

Abstract

This paper presents the machining efficiency evaluation of the glass fiber reinforced polymer (GFRP) composites modified by multiwall carbon nanotube (MWCNT). The milling experimentations were performed according to Taguchi-based experimental design. The three distinct machining constraints, such as spindle speed (S), feed rate (F), depth of cut (D), and wt% of MWCNT, are controlled to achieve the desired machining performances. A comparatively new multi-criteria decision-making technique (MCDM) is used by the combined compromise solution (CoCoSo) module for optimal parametric conditions. Analysis of variance (ANOVA) technique on CoCoSo assessment score is applied to determine the variance and adequacy level of variables used during machining of the nanocomposite. The experimental result shows that the depth of cut (D) and MWCNT wt% are found to be the most significant input parametric constraints, while spindle speed (S) and feed (F) obtained to be insignificant. The experimentation also revealed that the proposed CoCoSo optimization approach is a very effective tool for multi-objective optimization of milling parameters.

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Acknowledgements

The authors would also like to thank o/O DC (Handicrafts), Ministry of Textiles, Government of India, New Delhi, INDIA, for their kind assistance to perform this study.

Funding

This research work is financially supported by o/O DC (Handicrafts), Ministry of Textiles, Govt. of INDIA, Under Project ID: K-12012/4/19/2020–21/R and D/ST.

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Correspondence to Rajesh Kumar Verma .

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Kumar, K., Verma, R.K. (2023). Combined Compromise Solution for Machining Performance Optimization of Modified Polymer Composite. In: Dixit, U.S., Kanthababu, M., Ramesh Babu, A., Udhayakumar, S. (eds) Advances in Forming, Machining and Automation. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-19-3866-5_17

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  • DOI: https://doi.org/10.1007/978-981-19-3866-5_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-3865-8

  • Online ISBN: 978-981-19-3866-5

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