Abstract
This paper investigates the customer order scheduling problem on unrelated parallel additive manufacturing machines. The discussed problem comprises the splitting of orders into jobs, the allocation of those jobs to builds and finally the sequencing of builds on 3D printers. A mixed-integer programming model is presented that integrates practical requirements, such as printing profiles and different materials, and minimises total weighted tardiness. Using the Gurobi solver computational results are then given for a comprehensive test bed. It is shown, that medium sized problems can be solved using the proposed model, and that the consideration of printing profiles has a relevant impact on the scheduling task in additive manufacturing.
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Zipfel, B., Neufeld, J.S., Buscher, U. (2021). Customer Order Scheduling in an Additive Manufacturing Environment. In: Dolgui, A., Bernard, A., Lemoine, D., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 633. Springer, Cham. https://doi.org/10.1007/978-3-030-85910-7_11
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DOI: https://doi.org/10.1007/978-3-030-85910-7_11
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