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Cost-driven build orientation and bin packing of parts in Selective Laser Melting (SLM)

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  • Griffiths, Valeriya
  • Scanlan, James P.
  • Eres, Murat H.
  • Martinez-Sykora, Antonio
  • Chinchapatnam, Phani

Abstract

Selective Laser Melting (SLM) is an additive manufacturing process capable of producing mixed batches of parts simultaneously within a single build. The build orientation of a part in SLM is a key process parameter, affecting the build cost, time and quality, as well as batch size. Choosing an optimal arrangement of multiple heterogeneous parts inside the SLM machine also presents a challenging irregular bin packing problem. Since the two problems are interdependent, this paper addresses the combined problem of finding an optimal build orientation and two-dimensional irregular bin packing solution of a mixed batch of parts across identical SLM machines. We address this problem specifically in the context of low-volume high-variety (LVHV) production in the aerospace sector, using total build cost as the objective function. To solve this problem, we present an Iterative Tabu Search Procedure (ITSP), which consists of six distinct stages. We test each stage in the ITSP on 27 manually generated instances, based on 68 unique geometries ranging in convexity and size, including six real-life components from the aerospace industry. Two of the six stages, which are driven by support structure volume, returned the highest improvement in cost. Overall, the results showed an average cost improvement of 16.2% over the initial solution. The initial solution of the procedure was benchmarked against a commercial software, showing comparable results.

Suggested Citation

  • Griffiths, Valeriya & Scanlan, James P. & Eres, Murat H. & Martinez-Sykora, Antonio & Chinchapatnam, Phani, 2019. "Cost-driven build orientation and bin packing of parts in Selective Laser Melting (SLM)," European Journal of Operational Research, Elsevier, vol. 273(1), pages 334-352.
    • Handle: RePEc:eee:ejores:v:273:y:2019:i:1:p:334-352
    DOI: 10.1016/j.ejor.2018.07.053
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    References listed on IDEAS

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    1. Martinez-Sykora, A. & Alvarez-Valdes, R. & Bennell, J.A. & Ruiz, R. & Tamarit, J.M., 2017. "Matheuristics for the irregular bin packing problem with free rotations," European Journal of Operational Research, Elsevier, vol. 258(2), pages 440-455.
    2. Baumers, Martin & Dickens, Phill & Tuck, Chris & Hague, Richard, 2016. "The cost of additive manufacturing: machine productivity, economies of scale and technology-push," Technological Forecasting and Social Change, Elsevier, vol. 102(C), pages 193-201.
    3. A. S. Gogate & S. S. Pande, 2008. "Intelligent layout planning for rapid prototyping," International Journal of Production Research, Taylor & Francis Journals, vol. 46(20), pages 5607-5631, January.
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    Cited by:

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    2. Gahm, Christian & Uzunoglu, Aykut & Wahl, Stefan & Ganschinietz, Chantal & Tuma, Axel, 2022. "Applying machine learning for the anticipation of complex nesting solutions in hierarchical production planning," European Journal of Operational Research, Elsevier, vol. 296(3), pages 819-836.
    3. Carlos Alegría & David Orden & Carlos Seara & Jorge Urrutia, 2021. "Efficient computation of minimum-area rectilinear convex hull under rotation and generalizations," Journal of Global Optimization, Springer, vol. 79(3), pages 687-714, March.
    4. Marić, Josip & Opazo-Basáez, Marco & Vlačić, Božidar & Dabić, Marina, 2023. "Innovation management of three-dimensional printing (3DP) technology: Disclosing insights from existing literature and determining future research streams," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    5. Jose M. Framinan & Paz Perez-Gonzalez & Victor Fernandez-Viagas, 2023. "An overview on the use of operations research in additive manufacturing," Annals of Operations Research, Springer, vol. 322(1), pages 5-40, March.

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