| Title | Optimization of parallel turnings using particle swarm intelligence |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Xie, S., Wang, G. |
| Conference Name | 2018 Tenth International Conference on Advanced Computational Intelligence (ICACI) |
| Date Published | mar |
| Keywords | composability, Computational Intelligence, divide-and-conquer idea, Hafnium, Handheld computers, machining cost factor, machining fields, machining parameters, machining process parameters optimization, optimal machining parameters, optimal results, Optimization, optimization approaches, optimization problem, parallel turning, parallel turning operations, parallel turnings, Particle swarm intelligence, particle swarm optimisation, particle swarm optimization, PSO-based approaches, pubcrawl, swarm intelligence, turning (machining) |
| Abstract | Machining process parameters optimization is of concern in machining fields considering machining cost factor. In order to solve the optimization problem of machining process parameters in parallel turning operations, which aims to reduce the machining cost, two PSO-based optimization approaches are proposed in this paper. According to the divide-and-conquer idea, the problem is divided into some similar sub-problems. A particle swarm optimization then is derived to conquer each sub-problem to find the optimal results. Simulations show that, comparing to other optimization approaches proposed previously, the proposed two PSO-based approaches can get optimal machining parameters to reduce both the machining cost (UC) and the computation time. |
| DOI | 10.1109/ICACI.2018.8377611 |
| Citation Key | xie_optimization_2018 |
Optimization of parallel turnings using particle swarm intelligence