TY - JOUR
T1 - Optimization of hole making processes considering machining time and machining accuracy
AU - Guiotoko, Eric H.
AU - Aoyama, Hideki
AU - Sano, Noriaki
N1 - Publisher Copyright:
© 2017 The Japan Society of Mechanical Engineers.
PY - 2017
Y1 - 2017
N2 - 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 tools 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.
AB - 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 tools 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.
KW - Genetic algorithm
KW - Hole-making
KW - Process optimization
KW - Process planning
KW - TSP
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U2 - 10.1299/jamdsm.2017jamdsm0048
DO - 10.1299/jamdsm.2017jamdsm0048
M3 - Article
AN - SCOPUS:85030845308
SN - 1881-3054
VL - 11
JO - Journal of Advanced Mechanical Design, Systems and Manufacturing
JF - Journal of Advanced Mechanical Design, Systems and Manufacturing
IS - 4
M1 - JAMDSM0048
ER -