Determination of part orientation to minimize post-machining in laminated object manufacturing using genetic algorithm

  • Authors:

  • Dae Keon Ahn;Seok Hee Lee;Jeong Il Song;Soon Man Kwon

  • Affiliations:

  • School of Mechatronics Engineering, Changwon National University, Changwon, Republic of Korea;School of Mechatronics Engineering, Changwon National University, Changwon, Republic of Korea;School of Mechatronics Engineering, Changwon National University, Changwon, Republic of Korea;School of Mechatronics Engineering, Changwon National University, Changwon, Republic of Korea

  • Venue:
  • AIKED'09 Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
  • Year:
  • 2009

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Abstract

Laminated object manufacturing (LOM) is a rapid prototyping (RP) technology which can rapidly fabricate 3D physical model using layered manufacturing (LM) process. Hence, the RP such as LOM has been widely applied in manufacturing fields. However, the surface of the RP processed part is excessively rough to use industrial purpose due to the LM process itself. In order to improve the surface quality, additional post-machining such as coating and grinding process is required. These machining, however, are also detrimental to the original geometry of the part and is time consuming. In this paper, an intelligent methodology is proposed to minimize the machining area (PMA). An expression of the distribution of surface roughness is presented and the PMA is defined as an objective. Also, a genetic algorithm is applied to obtain reliable solution for complicated 3D CAD models which represent general industrial part. By implementing several applications, validity of the proposed methodology is demonstrated.