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Automated Derivation of Optimal Production Sequences from Product Data

Schäfer, Louis 1; Frank, Antonia 1; May, Marvin Carl ORCID iD icon 1; Lanza, Gisela 1
1 Institut für Produktionstechnik (WBK), Karlsruher Institut für Technologie (KIT)


Customer specific, individual products nowadays lead to larger product variance and shorter time to market. This requires efficient production system planning. In addition, due to a larger system complexity, each iteration of the planning process itself gets soaringly complex. Time constraints and complexity, therefore, emphasize the necessity of supporting humans in planning modern production systems.

Especially the determination of the production sequence holds immense potential and tends to get even more complex within specific production technologies. Exemplarily, this article focuses on welding sequences. Here, domain knowledge from product development and production planning needs to be holistically integrated. Furthermore, implicit, historic knowledge needs to be formalized and used in today’s planning tasks.

This article introduces a methodical approach and a corresponding toolchain to derive optimal production sequences from customer product data which is validated using welding processes. For this, firstly, a reference system is build up consisting of historic product data (e.g. part list, CAD data) and corresponding production system characteristics (e.g. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000149287
Veröffentlicht am 03.08.2022
DOI: 10.1016/j.procir.2022.05.010
Zitationen: 5
Zitationen: 5
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Produktionstechnik (WBK)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 2212-8271
KITopen-ID: 1000149287
Erschienen in Procedia CIRP
Verlag Elsevier
Band 107
Seiten 469–474
Bemerkung zur Veröffentlichung 55th CIRP Conference on Manufacturing Systems : Leading Manufacturing Systems Transformation, Lugano, Switzerland, 29.06 - 01.07.2022
Vorab online veröffentlicht am 26.05.2022
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