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A process planning framework and virtual representation for bead-based additive manufacturing processes

Abstract

CNC-based hybrid manufacturing systems capable of additive manufacturing (AM) and machining have been developed for metal and large thermoplastic components. Currently, there are no CAD/CAM systems that seamlessly integrate additive and machining tool paths and simulation, as required for a complete hybrid manufacturing solution. Tool paths for bead-based AM cannot be generated by simply reversing the Z processing order of waterline machining tool paths. AM process planning modules are significantly different than those for machining. Unique AM process planning challenges related to geometry, establishing relevant process-specific settings, thermodynamics, tool path planning and realistic virtual process simulation are discussed. To support hybrid manufacturing, the output from the additive manufacturing simulation must be employed as a stock model for subsequent machining. This paper discusses the architecture, process and data flows for a bead-based AM processes, with results being presented primarily for laser cladding.

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References

  1. 1.

    Hedrick R, Urbanic RJ, Burford C (2015) Development considerations for an additive manufacturing CAM systems. In: IFAC INCOM 2015. pp 2414–2419

  2. 2.

    Gibson I, Rosen DW, Stucker B (2009) Additive manufacturing technologies: rapid prototyping to direct digital manufacturing. Springer, New York

    Google Scholar 

  3. 3.

    Townsend V, Urbanic RJ (2012) Relating additive and subtractive processes in a teleological and modular approach. Rapid Prototyping J 18(4):324–338

    Article  Google Scholar 

  4. 4.

    Levy GN, Schindel R, Kruth JP (2003) Rapid manufacturing and rapid tooling with layer manufacturing (LM) technologies, state of the art and future perspectives, keynote paper. Annuals of the CIRP 52(2)

  5. 5.

    Raja B, Baskar N (2010) Optimization techniques for machining operations: a retrospective research based on various mathematical models. Int J Adv Manuf Technol 48(9):1075–1090

    Article  Google Scholar 

  6. 6.

    Zain AM, Haron H, Sharif S (2010) Application of GA to optimize cutting conditions for minimizing surface roughness in end milling machining process. Expert Syst Appl 37(6):4650–4659

    Article  Google Scholar 

  7. 7.

    Oktem H (2009) An integrated study of surface roughness for modelling and optimization of cutting parameters during end milling operation. Int J Adv Manuf Technol 43(9):852–861

    Article  Google Scholar 

  8. 8.

    Janakiraman V, Saravanan R (2010) Concurrent optimization of machining process parameters and tolerance allocation. Int J Adv Manuf Technol 51(1–4):357–369

    Article  Google Scholar 

  9. 9.

    Chen ZC, Gang L (2009) An intelligent approach to multiple cutters of maximum sizes for three-axis milling of sculptured surface parts. J Manuf Sci Eng 131(1):014501

    Article  Google Scholar 

  10. 10.

    Jain NK, Jain V, Deb K (2007) Optimization of process parameters of mechanical type advanced machining processes using genetic algorithms. Int J Mach Tool Manuf 47(6):900–919

    Article  Google Scholar 

  11. 11.

    Chen T, Ye P, Wang J (2005) Local interference detection and avoidance in five axis NC machining of sculptured surfaces. Int J Adv Manuf Technol 25(3–4):343–349

    Article  Google Scholar 

  12. 12.

    Hur J, Lee K, Zhu H, Kim J (2002) Hybrid rapid prototyping system using machining and deposition. Comput Aided Des 34(10):741–754

    Article  Google Scholar 

  13. 13.

    Ahn D, Kim H, Lee S (2007) Fabrication direction optimization to minimize post-machining in layered manufacturing. Int J Mach Tool Manuf 4(3-4):593–606

    Article  Google Scholar 

  14. 14.

    Pandey PM, Venkata Reddy N, Dhande SG (2003) Improvement of surface finish by staircase machining in fused deposition modeling. J Mater Process Technol 132(1-3):323–331

    Article  Google Scholar 

  15. 15.

    Ippolito R, Luliano L, Gatto A (1995) Benchmarking of rapid prototyping techniques in terms of dimensional accuracy and surface finish. Ann CIRP 44(1):157–160

    Article  Google Scholar 

  16. 16.

    Perez CJL (2002) Analysis of the surface roughness and dimensional accuracy capability of fused deposition modelling processes. Int J Prod Res 40(12):2865–2881

    Article  Google Scholar 

  17. 17.

    Pennington RC, Hoekstra NL, Newcomer JL (2005) Significant factors in the dimensional accuracy of fused deposition modelling. J Process Mech Eng 219(1):89–92

    Article  Google Scholar 

  18. 18.

    Saqib S, Urbanic RJ (2011) An experimental study to determine geometric and dimensional accuracy impact factors for fused deposition modelled parts, 4th International Conference on Changeable. Reconfigurable and Virtual Production, Agile, pp 293–298

    Google Scholar 

  19. 19.

    Liou F, Slattery K, Kinsella M, Newkirk J, Chou H, Landers R (2007) Applications of a hybrid manufacturing process for fabrication of metallic structures. Rapid Prototyping J 13(4):236–244

    Article  Google Scholar 

  20. 20.

    Han L, Liou F, Phatak K (2004) Modeling of laser cladding with powder injection. Metall Mater Trans B 35B:1139–1150

    Article  Google Scholar 

  21. 21.

    Lalas C, Tsirbas K, Salonitis K, Chryssolouris G (2007) An analytical model of the laser clad geometry. Int J Adv Manuf Technol 32:34–41

    Article  Google Scholar 

  22. 22.

    Zhang YM, Li P, Chen Y, Male A (2002) Automated system for welding-based rapid prototyping. Mechatronics 12:37–53

    Article  Google Scholar 

  23. 23.

    Langrana N, Qiu D, Bossett E, Danforth S, Jafari M, Safari A (2000) Virtual simulation and video microscopy for fused deposition methods. Mater Des 21:75–82

    Article  Google Scholar 

  24. 24.

    Choi SH, Samavedam S (2002) Modelling and optimization of rapid prototyping. Comput Ind 1:39–53

    Article  Google Scholar 

  25. 25.

    Choi SH, Chan A (2003) A layer-based virtual prototyping system for product development. Comput Ind 51:237–256

    Article  Google Scholar 

  26. 26.

    Reddy B, Reddy N, Ghosh (2007) Fused deposition modelling using direct extrusion. Virtual Phys Prototyping 2(1):51–60

    Article  Google Scholar 

  27. 27.

    Suryakumar S, Karunakaran KP, Bernard A, Chandrasekhar U, Raghavender N, Sharma D (2011) Weld bead modeling and process optimization in hybrid layered manufacturing. Comput Aided Des 43(3):331–344

    Article  Google Scholar 

  28. 28.

    Salonitis K, D’Alvise L, Schoinochoritis B, Chantzis D (2016) Additive manufacturing and post-processing simulation: laser cladding followed by high speed machining. Int J Adv Manuf Technol 85(9-12):2401–2411

    Article  Google Scholar 

  29. 29.

    Hedrick R, Urbanic RJ (2012) Integration of additive manufacturing and virtual verification strategies within a commercial CAM system. Comput Aided Des Appl 10(4):567–583

    Google Scholar 

  30. 30.

    Aggarwal K (2014) Investigation of laser clad bead geometry to process parameter settings for effective parameter selection, simulation, and optimization. MASc. thesis. University of Windsor, Windsor

  31. 31.

    Aggarwal K, Urbanic RJ, Aggarwal L (2014) Methodology for investigating and modelling laser clad bead geometry and process parameter relationships. SAE Int J Mater Manuf 7(2):269–279

    Article  Google Scholar 

  32. 32.

    Eiliat H, Urbanic RJ (2016) Minimizing voids with using an optimal raster orientation and bead width for a material extrusion process. Proceedings of IMECE 2016 ASME International Mechanical Engineering Congress and Exposition, IMECE 2016-67708

  33. 33.

    Alam M, Urbanic J, Saqib S, Edrisy A (2015) Effect of process parameters on the microstructural evolutions of laser cladded 420 martensitic stainless steel. In: Materials Science and Technology, p 22

  34. 34.

    Aiyiti W, Zhao W, Lu B, Tang Y (2006) Investigation of the overlapping parameters of MPAW-based rapid prototyping. Rapid Prototyping J 12(3):165–172

    Article  Google Scholar 

  35. 35.

    Jendrzejewski R, Śliwiński G, Krawczuk M, Ostachowicz W (2006) Temperature and stress during laser cladding of double-layer coatings. Surf Coatings Technol 201:3328–3334

    Article  Google Scholar 

  36. 36.

    Farahmand P, Kovacevic R (2014) An experimental–numerical investigation of heat distribution and stress field in single and multi-track laser cladding by a high-power direct diode laser. Opt Laser Technol 63:154–168

    Article  Google Scholar 

  37. 37.

    Saqib S, Urbanic RJ, Aggarwal K (2014) Analysis of laser cladding bead morphology for developing additive manufacturing travel paths. In: Variety management in manufacturing. Proceedings of the 47th CIRP Conference on Manufacturing Systems, Windsor, ON, Canada. Procedia CIRP, pp 824–829

  38. 38.

    Ocelík V, Eekma M, Hemmati I, De Hosson JTM (2012) Elimination of start/stop defects in laser cladding. Surf Coatings Technol 206:2403–2409

    Article  Google Scholar 

  39. 39.

    Sun Q, Rizvi G, Bellehumeur C, Gu P (2008) Effect of processing conditions on the bonding quality of FDM polymer filaments. Rapid Prototyping J 14(2):72–80

    Article  Google Scholar 

  40. 40.

    Song M, Lin X, Yang G, Cui X, Yang H, Huang W (2014) Influence of forming atmosphere on the deposition characteristics of Influence of forming atmosphere on the deposition characteristics of 2Cr13 stainless steel during laser solid forming. J Mater Process Technol 214(3):701–709

    Article  Google Scholar 

  41. 41.

    Bruckner F, Lepski D, Beyer E (2007) Modeling the influence of process parameters and additional heat sources on residual stresses in laser cladding. J Therm Spray Technol 16(3):355–373

    Article  Google Scholar 

  42. 42.

    Ahn S-H, Montero M, Odell D, Roundy S, Wright P (2002) Ansiotropic material properties of fused deposition modeling ABS. Rapid Prototyping J 8(4):248–257

    Article  Google Scholar 

  43. 43.

    Galantucci LM, Lavecchia F, Percoco G (2008) Study of compression properties of topologically optimized FDM made structured part. CIRP Ann Manuf Technol 57(1):243–246

    Article  Google Scholar 

  44. 44.

    Villalpando L, Eiliat H, Urbanic RJ (2014) An optimization approach for components built by fused deposition, vol 17, Proceedings of the 47th Conference on Manufacturing Systems (CMS)., pp 800–805

    Google Scholar 

  45. 45.

    Ma W, But W-C, He P (2004) NURBS-based adaptive slicing for efficient rapid prototyping. Comput Aided Des 36(13):1309–1325

    Article  Google Scholar 

  46. 46.

    Pandey PM, Reddy NV, Dhande SG (2003) Real time adaptive slicing for fused deposition modelling. Int J Mach Tool Manufact 43(1):61–71

    Article  Google Scholar 

  47. 47.

    Calleja A, Tabernero I, Fernandez A, Celaya A, Lamikiz A, de Lacalle Lopez LN (2014) Improvement of strategies and parameters for multi-axis laser cladding operations. Opt Lasers Eng 56:113–120

    Article  Google Scholar 

  48. 48.

    Saqib S (2016) Experimental investigation of laser cladding bead morphology and process parameter relationship for additive manufacturing process characterization, PhD dissertation, thesis. University of Windsor, Windsor

  49. 49.

    Wenbiao H, Jafari MA, Seyed K (2003) Process speeding up via deposition planning in fused deposition-based layered manufacturing processes. Rapid Prototyping J 9(4):212–218

    Article  Google Scholar 

  50. 50.

    Yu-an J, Yong H, Guang-huai X, Jian-zhong F (2015) A parallel-based path generation method for fused deposition modeling. Int J Adv Manuf Technol 77(5-8):927–937

    Article  Google Scholar 

  51. 51.

    Wenbiao H, Jafari MA, Danforth SC, Safari A (2002) Tool path-based deposition planning in fused deposition processes. J Manuf Sci Eng 124(2):462–472

    Article  Google Scholar 

  52. 52.

    Yu’An J, Yong H, Jianzhong F (2013) An adaptive tool path generation for fused deposition modeling. Adv Mater Res 819:7–12

    Article  Google Scholar 

  53. 53.

    Xiaomao H, Chunsheng Y, Yongjun H (2011) Tool path planning based on endpoint build-in optimization in rapid prototyping. J Mech Eng Sci 225(12):2919–2926

    Article  Google Scholar 

  54. 54.

    Jin GQ, Li W, Tsai CF, Wang L (2011) Adaptive tool-path generation of rapid prototyping for complex product models. J Manuf Syst 30(3):154–164

    Article  Google Scholar 

  55. 55.

    Brooks HL, Rennie TN, Abram AEW, McGovern J, Caron F (2011) Variable fused deposition modelling—analysis of benefits, concept design and tool path generation, Innovative developments in virtual and physical prototyping., pp 511–517

    Google Scholar 

  56. 56.

    Chakraborty D, Reddy BA, Choudhury AR (2008) Extruder path generation for curved layer fused deposition modeling. Comput Aided Des 40(2):235–243

    Article  Google Scholar 

  57. 57.

    Kulkarni P, Dutta D (2000) On the integration of layered manufacturing and material removal processes. J Manuf Sci Eng 122(1):100–108

    Article  Google Scholar 

  58. 58.

    Qiu D, Langrana NA (2002) Void eliminating toolpath for extrusion based multi-material layered manufacturing. Rapid Prototyping J 8(1):38–45

    Article  Google Scholar 

  59. 59.

    LASERTEC 65 3D (2014) Copyright © 2016 DMG MORI. url: http://dmgmori.com/products/lasertec/lasertec-additivemanufacturing/lasertec-65-3d

  60. 60.

    INTEGREX i-400AM (2014) Copyright © 2016 Mazak Corporation. url: https://www.mazakusa.com/fr/machines/integrex-i-400am/

  61. 61.

    LSAM (2016) Copyright © 2016 Thermwood Corporation. url: http://www.thermwood.com/lsam_development_main.htm

  62. 62.

    Urbanic J, Hedrick R (2009) Developing a virtual model for the fused deposition rapid prototyping process, Proceedings of the Life Cycle Engineering Conference., pp 131–137

    Google Scholar 

  63. 63.

    Jang D, Kim K, Jung J (2000) Voxel-based virtual multi-axis machining. Int J Adv Manuf Technol 16(10):709–713

    Article  Google Scholar 

  64. 64.

    Lee SW, Nestler A (2012) Virtual workpiece: workpiece representation for material removal process. Int J Adv Manuf Technol 58(5-8):443–463

    Article  Google Scholar 

  65. 65.

    Web3D Consortium (2012) Open standards for real-time 3D communication, Copyright © 1999-2016, Web3D Consortiumurl: url: http://www.web3d.org/

  66. 66.

    various WR- (2016) 3D printing and additive manufacturing, Annual Worldwide Progress Report. Wohlers Associates

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Correspondence to R. J. Urbanic.

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Urbanic, R.J., Hedrick, R.W. & Burford, C.G. A process planning framework and virtual representation for bead-based additive manufacturing processes. Int J Adv Manuf Technol 90, 361–376 (2017). https://doi.org/10.1007/s00170-016-9392-8

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Keywords

  • Additive manufacturing
  • Bead-based deposition processes
  • Process planning
  • Simulations
  • Hybrid manufacturing