Open AccessTime Optimization Analysis Using Hybrid Simulated Annealing and Genetics Algorithm For CNC Punching Machine
Author(s) -
Selvi Lukman,
Endra Joelianto,
Edi Leksono
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1230/1/012089
Subject(s) - punching , simulated annealing , machining , travelling salesman problem , computer science , algorithm , energy consumption , process (computing) , graph , mathematical optimization , engineering , mechanical engineering , mathematics , electrical engineering , theoretical computer science , operating system
This research describes the method of manufacturing process planning of hole manufacturing, which in every machining process consists of several individual operations with various types of punching blades. The process of setting the trajectory is one of the problems of holes manufacturing process because this process takes a long machining time and often it obtains undirected sequence path that sometimes causes stress material and the damaged of punching blades. The aim of optimization process is to minimize the processing time of holes manufacturing so the time function which is obtained can be converted in the form of energy consumption that helps manufacturers to predict the machining time. Dynamic Directed Graph is applied where each node represents a machining operation. The time function is obtained by studying the shortest path of a directed graph where the structure of objectivity studied is similar to the Traveling Salesman Problem (TSP). The mathematical model is used to solve the hole optimization problem of the graph structure by proposing the combination of both to solve the optimization problem. The Algorithm realization will be applied in real time CAD / CAM programming by using TOPS300 which is used for TRUMPF TC200 Punching Machine. There are 2 kinds of blade operations in this research which are single stroke operation and multi strokes operation. Both produce different time function. By a. Finally, some conclusions are given from examples that show the hybrid algorithm of Simulated Annealing and Genetic Algorithms is effective in reaching higher optimization performance and less energy consumption, which 26.02 seconds for single stroke operation and 126.02 seconds for multi strokes operation with the acquisition of logical path results with the absence of intersecting trajectories.