Skip to main content

Advertisement

SpringerLink
Log in

A finishing cutter selection algorithm for additive/subtractive rapid pattern manufacturing

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

The additive/subtractive rapid pattern manufacturing (RPM) process sequentially deposits thick material slabs and then machines them into desired geometries in a layer-by-layer manner. Although most rapid manufacturing systems mainly intend to increase flexibility in manufacturing rather than to reduce processing speed, it is still practical to choose the optimized sets of cutters and machining parameters specifically for each layer to improve both the machining quality and efficiency. This paper presents an algorithm to automatically select finishing cutter geometry, diameter, and calculate machining parameters for the RPM process. Inputs to this algorithm are StereoLithography file from a computer-aided design model and a cutter library. Finishing cutter selection is based on geometry accessibility and machining process efficiency analysis. The algorithm has been implemented in RPM automatic process planning software and the experimental result on a sample part is presented to show the efficacy of this algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Luo XM, Frank MC (2010) A layer thickness algorithm for additive/subtractive rapid pattern manufacturing. Rapid Prototyping J 16(2):100–115

    Article  Google Scholar 

  2. Frank MC, Wysk RA, Joshi SB (2004) Rapid planning for CNC milling—a new approach for rapid prototyping. J Manuf Syst 23(3):242–255

    Article  Google Scholar 

  3. Ribeiro MV, Coppini NL (1999) An applied database system for the optimization of cutting conditions and cutter selection. J Mater Process Technol 92–93:371–374

    Article  Google Scholar 

  4. Arezoo B, Ridgway K, Al-Ahmari AMA (2000) Selection of cutting cutters and conditions of machining operations using an expert system. Comp Ind 42(1):43–58

    Article  Google Scholar 

  5. Lee YS, Chang TC (1994) Using virtual boundaries for the planning and machining of protrusion freeform features. Comput Ind 25(2):173–187

    Article  Google Scholar 

  6. Lee YS, Chang TC (1995) Application of computational geometry in optimizing 2.5D and 3D NC surface machining. Comput Ind 26(1):41–59

    Article  Google Scholar 

  7. Yao ZY, Gupta SK, Nau DS (2001) A geometric algorithm for finding the largest milling cutter. J Manuf Process 3(1):1–16

    Article  Google Scholar 

  8. Bala M, Chang TC (1991) Automatic cutter selection and optimal cutter path generation for prismatic parts. Int J Prod Res 29(11):2163–2176

    Article  MATH  Google Scholar 

  9. Chen YH, Lee YS, Fang SC (1998) Optimal cutter selection and machine plane determination for process planning and NC machining of complex surfaces. J Mach Syst 17(5):371–388

    Article  Google Scholar 

  10. Arya S, Cheng SW, Mount DM (1998) Approximation algorithms for multiple cutter milling. Proceedings of the Fourteenth Annual Symposium on Computational Geometry, pp. 297–306

  11. Veeramani D, Gau YS (1997) Selection of an optimal set of cutting-cutter sizes for 2½ D pocket machining. Comput Aided Des 29(12):869–877

    Article  Google Scholar 

  12. Veeramani D, Gau YS (2000) Cutter-path generation using multiple cutting-cutter sizes for 2½ D pocket machining. IIE Trans 32(7):661–675

    Google Scholar 

  13. Nadjakova I, Mcmains S (2004) Finding an optimal set of cutter radii for 2D pocket machining. Proceedings of International Mechanical Engineering Congress and RD&D Expo, 1–8

  14. Yao ZY, Gupta SK, Nau DS (2003) Algorithm for selecting cutters in multi-part milling problems. Comput Aided Des 35(9):825–839

    Article  Google Scholar 

  15. Wang Y, Ma HJ, Gao CH, Xu HG, Zhou XH (2005) A computer aided cutter selection system for 3D die/mould-cavity NC machining using both a heuristic and analytical approach. Int J Comput Integr Manuf 18(8):686–701

    Article  Google Scholar 

  16. D'Souza RM (2006) One setup level cutter selection for 2.5-D pocket milling. Robot Comput Integ Manuf 22(3):256–266

    Article  Google Scholar 

  17. Lim T, Corney J, Clark DER (2000) Exact cutter sizing for feature accessibility. Int J Adv Manuf Technol 16(11):791–802

    Article  Google Scholar 

  18. Lee YS, Choi BK, Chang TC (1992) Cut distribution and cutter selection for sculptured surface cavity machining. Int J Prod Res 30(6):1447–1470

    Article  Google Scholar 

  19. Yang DCH, Han Z (1999) Interference detection and optimal cutter selection in 3-axis NC machining of free-form surfaces. Comput Aided Des 31(5):303–315

    Article  MATH  Google Scholar 

  20. Lin AC, Gian R (1999) A multiple-cutter approach to rough machining of sculptured surfaces. Int J Adv Manuf Technol 15(6):387–398

    Article  Google Scholar 

  21. Sun GP, Sequin CH, Wright PK (2001) Operation decomposition for freeform surface features in process planning. Comput Aided Des 33(9):621–636

    Article  Google Scholar 

  22. Balasubramanima M, Joshi Y, Engels D, Sarma S, Shaikh Z (2001) Cutter selection in three-axis rough machining. Int J Prod Res 39(18):4215–4238

    Article  Google Scholar 

  23. Joo J, Cho H, Yun W (1997) Efficient feature-based process planning for sculptured pocket machining. Comput Ind Eng 33(3–4):493–496

    Google Scholar 

  24. Perng DB, Cheng CT (1994) Feature based process plan generation from 3D DSG inputs. Comput Ind Eng 26(3):423–435

    Article  Google Scholar 

  25. Chamberlain MA, Joneja A, Chang TC (1993) Protrusion features handling in design and manufacturing planning. Comput Aided Des 25(1):19–28

    Article  MATH  Google Scholar 

  26. Chua MS, Rahman M, Wong YS, Loh HT (1993) Determination of optimal cutting conditions using design of experiments and optimization techniques. Int J Mach Cut Manuf 33(2):297–305

    Article  Google Scholar 

  27. Yazar Z, Koch KF, Merrick T, Altan T (1994) Feed rate optimization based on cutting force calculations in 3-axis milling of dies and moulds with sculptures surfaces. Int J Mach Cut Manuf 34(3):365–377

    Article  Google Scholar 

  28. Wang J, Armarego EJA (1995) Optimisation strategies and CAM software for multiple constraint face milling operations. Proceedings of the 6th International Conference on Manufacturing Engineering, 535–540

  29. Rad MT, Bidhendi IM (1997) On the optimization of machining parameters for milling operations. Int J Mach Cut Manuf 37(1):1–16

    Article  Google Scholar 

  30. Bae SH, Ko K, Kim BH, Choi BK (2003) Automatic feedrate adjustment for pocket machining. Comput Aided Des 35(5):495–500

    Article  Google Scholar 

  31. AFS (1970) Pattern maker's manual. American Foundrymen's Society, Schaumburg, IL

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, IA, 50011, USA

    Xiaoming Luo & Matthew C. Frank

  2. Department of Industrial and Manufacturing Engineering and Technology, Bradley University, Peoria, IL, 61625, USA

    Ye Li

Authors
  1. Xiaoming Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ye Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Matthew C. Frank
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiaoming Luo.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Luo, X., Li, Y. & Frank, M.C. A finishing cutter selection algorithm for additive/subtractive rapid pattern manufacturing. Int J Adv Manuf Technol 69, 2041–2053 (2013). https://doi.org/10.1007/s00170-013-5182-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-013-5182-8

Keywords

Search

Navigation