Evolutionary Algorithms for Optimization of Drilling Variables for Reduced Thrust Force in Composite Material Drilling
Creators
- 1. Department of Computer Science, Mahatma Jyoti Rao Phoole University, Jaipur (R.J), India
Description
Abstract: This study aims to optimize drilling variables to reduce the thrust force required for drilling composite materials. The optimization process involves using evolutionary algorithms such as particle swarm optimization (PSO) and genetic algorithm (GA) to determine the best combination of drilling parameters, including drill speed, feed rate, and point angle. The objective is to minimize the thrust force required for drilling while maintaining the desired quality of the drilled holes. ANOVA and regression analysis is implemented to discuss the impact of drilling variable on the thrust force. The results demonstrate that the proposed approach is effective in reducing thrust force and improving drilling efficiency. The optimized drilling parameters obtained can be used to enhance the performance of composite material drilling processes. Performance output of both algorithms for optimization of problem is discussed in detail.
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- Journal article: 2231-2307 (ISSN)
References
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Subjects
- ISSN: 2231-2307 (Online)
- https://portal.issn.org/resource/ISSN/2231-2307#
- Retrieval Number: 100.1/ijsce.B36100513223
- https://www.ijsce.org/portfolio-item/b36100513223/
- Journal Website: www.ijsce.org
- https://www.ijsce.org/
- Publisher: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP)
- https://www.blueeyesintelligence.org/