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Modeling and optimization of direct metal laser sintering process

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Abstract

Direct metal laser sintering (DMLS) is a novel class of rapid manufacturing process that can fabricate functional parts of any complexity. However, the DMLS process takes almost 6–12 h to build parts of even small-moderate size. Reducing the build time of the parts is the key to success of the DMLS process at commercial level. A common solution to reduce the part build time is to sinter the parts with maximum allowable layer thickness. However, doing so will make staircase effect more prominent and lead to the poor surface accuracy of the part. In this paper, a bi-criteria-based optimization approach is presented to address this issue. The sub-processes, namely, part orientation, layer thickness identification, and laser scanning directions, are optimized with an aim to build the parts with: (a) minimum amount of time and (b) minimum surface inaccuracy. In addition, the material shrinkage is also incorporated in the proposed model. Parts with varying complexities are analyzed to elucidate the applicability of proposed approach. Comparisons with traditional slicing approaches are also made.

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References

  1. 1.

    Beaman JJ (1996) Solid freeform fabrication—a new direction in manufacturing. Kluwer, Norwell

  2. 2.

    Lan PT, Chou SY, Chen LL, Douglas G (1997) Determining fabrication orientations for rapid prototyping with stereo lithography apparatus. Comput Aided Des 29:53–62

  3. 3.

    Masood SH, Rattanwong W, Iovenitti P (2003) A genetic algorithm for a best part orientation system for complex parts in rapid prototyping. J Mater Process Technol 139:110–116

  4. 4.

    Rock SJ, Wozny MJ (1992) In: Marcus HL et al (eds) Generating topological information from a ‘bucket of facets’, solid freeform fabrication symposium. University of Texas, Austin, pp 251–259

  5. 5.

    Kirschman CF, Jara-Almonte CC, Bagchi A, Dooley RL, Ogale AA (1991) Computer aided design of support structures for stereo lithographic components. Proceedings of the 1991 ASME Computers in Engineering Conference, Santa Clara, pp 443–448

  6. 6.

    Rajagopalan M, Aziz NM, Huey CO (1995) A model for interfacing geometric modeling data with rapid prototyping systems. Adv Eng Softw 23:889–896

  7. 7.

    Farouki RT, Konig T (1996) Computational methods for rapid prototyping of analytic solid models. Rapid Prototyp J 2(3):41–49

  8. 8.

    Guduri S, Crawford RH, Beaman JJ (1991) In: Marcus HL et al (eds) A method to generate exact contour files for solid freeform fabrication. In proceedings of solid freeform fabrication symposium. University of Texas at Austin, Austin, pp 95–101

  9. 9.

    Dolenc A, Mäkelä I (1994) Slicing procedures for layered manufacturing techniques. Comput Aided Des 26(2):119–126

  10. 10.

    Brown S (1993) Simulation of solid freeform fabrication. In: Marcus HL et al (eds) Solid freeform fabrication symposium. University of Texas, Austin, pp 143–149

  11. 11.

    Sabourin E, Houser SA, Bohn JH (1997) Accurate exterior, fast interior layered manufacturing. Rapid Prototyp J 3(2):44–52

  12. 12.

    Thomas CL, Gaffney TM, Kaza S, Lee CH (1996) Rapid prototyping of large scale aerospace structures. IEEE aerospace applications conference, Profet, R., chair, Aspen, Colorado, USA, February 4–11, Vol. 4, pp. 219–230

  13. 13.

    Tyberg JT (1998) Local adaptive slicing for layered manufacturing. Master’s thesis, University of Virginia

  14. 14.

    Sabourin E, Houser SA, Bohn JH (1996) Adaptive slicing using stepwise uniform refinement. Rapid Prototyp J 2(4):20–26

  15. 15.

    Tyberg JT, Bohn JH (1998) Local adaptive slicing. Rapid Prototyp J 4(3):118–127

  16. 16.

    Tata K, Fadel G, Bagchi A, Aziz N (1998) Efficient slicing for layered manufacturing. Rapid Prototyp J 4(4):151–167

  17. 17.

    Kai CC, Fai KL (2003) Rapid prototyping principles and applications. World Scientific press, 2003

  18. 18.

    Marsan AL, Kumar V, Dutta D, Prat MJ (1998) An assessment of data requirements and data transfer formats for layered manufacturing. NIST, US Department of Commerce

  19. 19.

    Chen K, Crawford RH, Beaman JJ (1996) In: Bourell DL et al (eds) Parametric representation of part contours in SLS process. Solid freeform fabrication symposium 1996. University of Texas, Austin, pp 597–608

  20. 20.

    Crawford RH (1993) In: Marcus HL et al (eds) Computer aspects of solid freeform fabrication: geometry process control, and design, solid freeform fabrication symposium. University of Texas, Austin, pp 102–112

  21. 21.

    Chari JK, Hall JL (1993) In: Marcus HL et al (eds) Robust prototyping. Solid freeform fabrication symposium. University of Texas, Austin, pp 135–142

  22. 22.

    Ning Y, Wong YS, Fuh JYH, Loh HT (2006) An approach to minimize build errors in direct metal laser sintering. IEEE Trans Autom Sci Eng 3(1):73–80

  23. 23.

    Padhye N, Deb K (2010) Evolutionary multi-objective optimization and decision making for selective laser sintering. GECCO’10

  24. 24.

    Byun HS, Lee KH (2005) Determination of the optimal build direction in layered manufacturing using a genetic algorithm. Int J Prod Res 43(13):2709–2724

  25. 25.

    Padhye N, Kalia S (2009) Rapid prototyping using evolutionary algorithms: Part 1 and Part II. GECCO’09

  26. 26.

    Paul R, Anand S (2012) Process energy analysis and optimization in selective laser sintering. J Manuf Syst 31(4):429–437

  27. 27.

    Tyagi S, Ghorpade A, Karunakaran KP, Tiwari MK (2007) Optimal part orientation in layered manufacturing using evolutionary stickers-based DNA algorithm. Virtual Phys Prototyp 2(1):3–19

  28. 28.

    Dwivedi SN, Tyagi SK, Tiwari MK (2007) Optimal part orientation in fused deposition modeling: an approach based on continuous domain ant colony optimization. Int J Adv Manuf Syst 10(2):95–110

  29. 29.

    Lu K, Jing M, Zhang X, Liu H (2013) Optimization of sequential subdivision of depth of cut in turning operations using dynamic programming. Int J Adv Manuf Technol 68(5–8):1733–1744

  30. 30.

    Verma A, Tiwari MK (2009) Role of corporate memory in global supply chain environment. Int J Prod Res 27(1):5311–5342

  31. 31.

    Choi SH, Samavedam S (2001) Visualization of rapid prototyping. Rapid Prototyp J 7(2):99–114

  32. 32.

    Tyagi SK, Yang K, Verma A (2007) Non-discrete ant colony optimisation (NdACO) to optimise the development cycle time and cost in overlapped product development. Int J Prod Res 51(2):346–361

  33. 33.

    Goldberg DE (1989) Genetic algorithm in search, optimization and machine learning. Addison-Wesley, Reading

  34. 34.

    Tyagi SK, Yang K, Tyagi A, Dwivedi SN (2011) Development of a fuzzy goal programming model for optimization of lead time and cost in an overlapped product development project using a Gaussian adaptive particle swarm optimization-based approach. Eng Appl Artif Intell 24(5):866–879

  35. 35.

    Tyagi SK, Yang K, Tyagi A, Verma A (2012) A fuzzy goal programming approach for optimal product family design of mobile phones and multiple-platform architecture. IEEE Trans Syst Man Cybern Part C Appl Rev 42(6):1519–1530

  36. 36.

    Verma A, Shukla N, Tyagi S, Mishra N (2014) Stochastic modelling and optimisation of multi-plant capacity planning problem. Int. J. Intelligent Engineering Informatics, X(Y), 00–00

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Correspondence to Anoop Verma.

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Verma, A., Tyagi, S. & Yang, K. Modeling and optimization of direct metal laser sintering process. Int J Adv Manuf Technol 77, 847–860 (2015). https://doi.org/10.1007/s00170-014-6443-x

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Keywords

  • Volumetric error
  • Build time
  • Optimization
  • Adaptive slicing
  • Genetic algorithm