Production planning in 3DPrinting factories

Fuente: arXiv
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Auteurs principaux: De Anton, Juan, Senovilla, Juan J, Gonzalez-Varona, Jose M, Acebes, Fernando
Format: Preprint
Publié: 2024
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author De Anton, Juan
Senovilla, Juan J
Gonzalez-Varona, Jose M
Acebes, Fernando
author_facet De Anton, Juan
Senovilla, Juan J
Gonzalez-Varona, Jose M
Acebes, Fernando
contents Production planning in 3D printing factories brings new challenges among which the scheduling of parts to be produced stands out. A main issue is to increase the efficiency of the plant and 3D printers productivity. Planning, scheduling, and nesting in 3D printing are recurrent problems in the search for new techniques to promote the development of this technology. In this work, we address the problem for the suppliers that have to schedule their daily production. This problem is part of the LONJA3D model, a managed 3D printing market where the parts ordered by the customers are reorganized into new batches so that suppliers can optimize their production capacity. In this paper, we propose a method derived from the design of combinatorial auctions to solve the nesting problem in 3D printing. First, we propose the use of a heuristic to create potential manufacturing batches. Then, we compute the expected return for each batch. The selected batch should generate the highest income. Several experiments have been tested to validate the process. This method is a first approach to the planning problem in 3D printing and further research is proposed to improve the procedure
format Preprint
id arxiv_https___arxiv_org_abs_2406_02588
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Production planning in 3DPrinting factories
De Anton, Juan
Senovilla, Juan J
Gonzalez-Varona, Jose M
Acebes, Fernando
General Economics
Economics
Production planning in 3D printing factories brings new challenges among which the scheduling of parts to be produced stands out. A main issue is to increase the efficiency of the plant and 3D printers productivity. Planning, scheduling, and nesting in 3D printing are recurrent problems in the search for new techniques to promote the development of this technology. In this work, we address the problem for the suppliers that have to schedule their daily production. This problem is part of the LONJA3D model, a managed 3D printing market where the parts ordered by the customers are reorganized into new batches so that suppliers can optimize their production capacity. In this paper, we propose a method derived from the design of combinatorial auctions to solve the nesting problem in 3D printing. First, we propose the use of a heuristic to create potential manufacturing batches. Then, we compute the expected return for each batch. The selected batch should generate the highest income. Several experiments have been tested to validate the process. This method is a first approach to the planning problem in 3D printing and further research is proposed to improve the procedure
title Production planning in 3DPrinting factories
topic General Economics
Economics
url https://arxiv.org/abs/2406.02588