科研之友
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摘要
The selection of machining parameters directly affects the production time, quality, cost, and other process performance measures for multi-pass milling. Optimization of machining parameters is of great significance. However, it is a nonlinear constrained optimization problem, which is very difficult to obtain satisfactory solutions by traditional optimization methods. A new optimization technique combined chaotic operator and imperialist competitive algorithm (ICA) is proposed to solve this problem. The ICA simulates the competition between the empires. It is a population-based meta-heuristic algorithm for unconstrained optimization problems. Imperialist development operator based on chaotic sequence is introduced to improve the local search of ICA, while constraints handling mechanism is introduced and an imperialist-colony transformation policy is established. The improved ICA is called chaotic imperialist competitive algorithm (CICA). A case study of optimizing machining parameters for multi-pass face milling operations is presented to verify the effectiveness of the proposed method. The case is to optimize parameters such as speed, feed, and depth of cut in each pass have yielded a minimum total product ion cost. The depth of cut of optimal strategy obtained by CICA are 4 mm, 3 mm, 1 mm for rough cutting pass 1, rough cutting pass 1 and finish cutting pass, respectively. The cost for each pass are $0.5366 US, $0.4473 US and $0.3738 US. The optimal solution of CICA for various strategies with a(t)=8 mm is $1.3576 US. The results obtained with the proposed schemes are better than those of previous work. This shows the superior performance of CICA in solving such problems. Finally, optimization of cutting strategy when the width of workpiece no smaller than the diameter of cutter is discussed. Conclusion can be drawn that larger tool diameter and row spacing should be chosen to increase cutting efficiency.
- 出版日期2018-9
- 单位华中农业大学
