Customer Order Scheduling in an Additive Manufacturing Environment

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

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.

Details

OriginalspracheEnglisch
TitelAdvances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems
Redakteure/-innenAlexandre Dolgui, Alain Bernard, David Lemoine, Gregor von Cieminski, David Romero
Herausgeber (Verlag)Springer Science and Business Media B.V.
Seiten101-109
Seitenumfang9
ISBN (elektronisch)978-3-030-85910-7
ISBN (Print)978-3-030-85909-1, 978-3-030-85912-1
PublikationsstatusVeröffentlicht - 2021
Peer-Review-StatusJa

Publikationsreihe

ReiheIFIP Advances in Information and Communication Technology
Band633
ISSN1868-4238

Konferenz

Titel2021 International Conference on Advances in Production Management Systems
UntertitelArtificial Intelligence for Sustainable and Resilient Production Systems
KurztitelAPMS 2021
Dauer5 - 9 September 2021
Webseite
OrtOnline
StadtNantes
LandFrankreich

Externe IDs

ORCID /0000-0003-4711-2184/work/115248261
ORCID /0000-0003-0753-0517/work/142255241

Schlagworte

Schlagwörter

  • Additive manufacturing, Customer order scheduling, Unrelated parallel machines