DOI QR코드

DOI QR Code

Automatic Generation of Machining Sequence for Machined Parts Using Machining Features

특징형상을 이용한 절삭가공부품의 가공순서 자동생성

  • Woo, Yoonhwan (Department of Mechanical Systems Engineering, Hansung University) ;
  • Kang, Sangwook (Department of Mechanical Systems Engineering, Hansung University)
  • 우윤환 (한성대학교 기계시스템공학과) ;
  • 강상욱 (한성대학교 기계시스템공학과)
  • Received : 2015.10.30
  • Accepted : 2016.02.04
  • Published : 2016.02.29

Abstract

As 3D solid modeling prevails, a range of applications have become possible and intensive research on the integration of CAD/CAM has been conducted. As a consequence, methods to recognize the machining features from CAD models have been developed. On the other hand, generating a machining sequence using the machining features is still a problem due to a combinatorial problem with a large number of machining features. This paper proposes a new method that utilizes the precedence constraints through which the number of the combinations is reduced drastically. This method can automatically generate machining sequences requiring the lowest amount of machining time. An airplane part was used to test the usefulness of the proposed method.

3차원 솔리드모델링이 일반화되면서 이를 이용한 여러 응용이 가능해졌으며, 가장 대표적인 응용분야인 CAM과의 통합을 위한 다양한 연구가 진행되어왔다. 그 결과 설계된 부품의 CAD모델로부터 실제가공에 필요한 특징형상을 자동으로 인식하는 기술들이 개발되었다. 하지만 이러한 방법으로 인식된 특징형상들을 이용하여 절삭가공순서 등을 자동으로 생성하기 위해서는 고려하여야 할 가공순서의 조합의 수가 너무 많아 이를 구현하기에는 현실적으로 문제가 발생한다. 이에 본 연구에서는 절삭가공에 관련된 규칙을 수집하고 이를 이용하여 특징형상 간 가공우선순위를 적용함으로써 고려하여할 조합의 수를 대폭 감소시키고, 이들 조합으로부터 효율성을 최대화 하는 가공순서를 결정하는 방법을 제안하였다. 또한 항공기 부품에 대한 테스트를 통하여 20개의 특징형상으로부터 가공시간이 적은 가공순서를 자동으로 생성할 수 있었다.

Keywords

References

  1. H. Sakurai, P. Dave, "Volume decomposition and feature recognition: Part I-polyhedral objects", Computer Aided Design, Vol. 27, No. 11, pp. 833-843, 1995. DOI: http://dx.doi.org/10.1016/0010-4485(95)00007-0
  2. H. Sakurai, P. Dave, "Volume decomposition and feature recognition: Part II-curved objects", Computer Aided Design, Vol. 28, pp. 519-537, 1996. DOI: http://dx.doi.org/10.1016/0010-4485(95)00067-4
  3. Y. Woo, "Fast cell-based decomoposition and applications to solid modeling", Computer Aided Design, Vol. 35, pp. 969-977, 2003. DOI: http://dx.doi.org/10.1016/S0010-4485(02)00144-6
  4. M. R. Henderson, "Extraction of feature information from three dimensional CAD data", PhD Thesis, Purdue University, USA, 1984.
  5. S. Joshi, T. C. Chang, "Graph-based heuristics for recognition of machined features from a 3D solid model", Computer Aided Design, Vol. 20, No. 2, pp. 58-66, 1988. DOI: http://dx.doi.org/10.1016/0010-4485(88)90050-4
  6. W. C. Regli, S. K. Gupta, D. S. Nau, "Extracting alternative machining features: An algorithmic approach", Research in engineering design, Vol. 7, No. 3, pp. 173-192, 1995. DOI: http://dx.doi.org/10.1007/BF01638098
  7. I. Han, A. G. Requicha, "Integration of feature-based design and feature recognition", Proceeding of the computers in engineering conference and engineering database symposium ASME, pp. 569-578, 1995.
  8. M. Bala, T. C. Chang, "Automatic cutter selection and optimal cutter path generation for prismatic parts", International Journal of Production Research, Vol. 29, No. 11, pp. 2163-2176, 1991. DOI: http://dx.doi.org/10.1080/00207549108948076
  9. D. Veeramani, Y. Gau, "Selection of an optimal set of cutting-tool size for 2.5D pocket machining", Computer Aided Design, Vol. 29, No. 12, pp. 869-877, 1997. DOI: http://dx.doi.org/10.1016/S0010-4485(97)00042-0
  10. ACIS 3D modeling kernal, Spatial Corp, USA, http://www.spatial.com

Cited by

  1. Dynamic machining process planning incorporating in-process workpiece deformation data for large-size aircraft structural parts pp.1362-3052, 2018, https://doi.org/10.1080/0951192X.2018.1529431