Optimization of hole making processes considering machining time and machining accuracy

Eric H. GUIOTOKO, Hideki AOYAMA, Noriaki SANO
2017 Journal of Advanced Mechanical Design, Systems, and Manufacturing  
In machining, hole-making process takes up large part of the manufacturing processes. In previous hole-making processes optimization researches, researcher considered machine tools to have movement control on 3-axis. Thus, it is difficult to apply the result of the researches to 5-axis machining. In addition, in these studies, it is assumed that tool needed to make a hole are always available or only a single tool is needed to make a hole. However in a real working environment, number of the
more » ... ls available are limited and also single tool cannot make a required hole diameter and tolerance in the most cases. Thus, the result of past researches is difficult to apply in real working environment. This research investigated hole-making optimization that can be applied to 5-axis machining, and considering the tool movement, tool switching, and limitation in the tool. Also tolerances of the holes were considered as a machining accuracy. Optimization can be done using brute-force approach and method solving traveling salesman problem (TSP). However, brute-force approach will be difficult to apply due to the longer time for calculation, when number of the hole pattern increases. For optimization, Genetic Algorithm (GA) was used to create optimization system. System was compared against the brute-force approach to check its validity by comparing the result and calculation time. After validity check, system was applied to the engine block model to obtain optimized hole-making processes. restricted or not. For future work, system needs to consider the effect of the drill material and the work material. Since a few drills can make a hole with only a single operation, and this could reduce machining time and change the hole-making process. Also, another future work that needs to be considered is to shorten the computational time for future work. This can be done by optimizing the program by using efficient functions and reducing the number of the loops in the program. Since this program requires large number of loops for calculation, resulting computational time will be large that it may not be suitable for actual workshop.
doi:10.1299/jamdsm.2017jamdsm0048 fatcat:36x3cifhibastkreqaeyacqoxm