AI Summary & Key Takeaways
AI InsightAs a consequence, it should be noted that theproposed solution approach for the tool path optimization is capable of providingconsiderable time reductions on the CNC internal operations for the company.
📌 3 Key Takeaways
Abstract
In this study, a tool path optimization problem in Computer Numerical Control(CNC) milling machines is considered to increase the operational efficiency ratesof a company. In this context, tool path optimization problem of the company isformulated based on the precedence constrained travelling salesman problem(PCTSP), where the general form of the TSP model is extended by taking theprecedence of the tool operations into account. The objective of the model is tominimize total idle and unnecessary times of the tools for internal operations. Tosolve the considered problem, a recent optimization algorithm, called SatinBowerbird Optimizer (SBO), is used. Since the SBO is first introduced for theglobal optimization problems, the original version of the SBO is modified for thePCTSP with discretization and local search procedures. In computational studies,first, the performance of the proposed algorithm is tested on a well-known PCTSPbenchmark problems by comparing the proposed algorithm against two recentlyproposed meta-heuristic approaches. Results of the comparisons show that theproposed algorithm outperforms the other two competitive algorithms by findingbetter results. Then, the proposed algorithm is carried out to optimize the holedrilling processes of three different products produced by the company. For thiscase, with up to 4.05% improvement on the operational times was provided for thereal-life problem of the company. As a consequence, it should be noted that theproposed solution approach for the tool path optimization is capable of providingconsiderable time reductions on the CNC internal operations for the company.