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Process planning and scheduling optimisation with alternative recipes

Optimierung der Prozessplanung und -vorbereitung durch alternative Rezepte
Piotr Dziurzanski, Shuai Zhao, Sebastian Scholze, Albert Zilverberg, Karl Krone and Leandro Soares Indrusiak

Abstract

This paper considers an application of a new variant of a multi-objective flexible job-shop scheduling problem, featuring multisubset selection of manufactured recipes, to a real-world chemical plant. The problem is optimised using a multi-objective genetic algorithm with customised mutation and elitism operators that minimises both the total production time and the produced commodity surplus. The algorithm evaluation is performed with both random and historic manufacturing orders. The latter demonstrated that the proposed system can lead to more than 10 % makespan improvements in comparison with human operators.

Zusammenfassung

Dieser Artikel beschreibt die Anwendung einer neuen Variante eines mehrdimensionalen Optimierungsproblems in der flexiblen Fertigungsplanung mit mehreren Teilmengen von Fertigungsrezepten in einer realen Fabrik zur Herstellung von Farben. Das Problem wird mithilfe eines mehrdimensionalen genetischen Algorithmus mit angepassten Mutations- und Elitismus-Operatoren optimiert. Dieser Algorithmus minimiert sowohl die Gesamtproduktionszeit als auch den produzierten Warenüberschuss. Die Bewertung des Algorithmus wird sowohl mit zufällig generierten als auch mit realen historischen Fertigungsaufträgen durchgeführt. Letztere haben gezeigt, dass das vorgeschlagene System im Vergleich zum menschlichen Bediener zu einer Verbesserung der Produktionsdauer um mehr als 10 % führen kann.

Funding source: Horizon 2020 Framework Programme

Award Identifier / Grant number: 723634

Funding statement: The authors acknowledge the support of the EU H2020 SAFIRE project (Ref. 723634).

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Received: 2019-08-27
Accepted: 2019-12-05
Published Online: 2020-01-22
Published in Print: 2020-02-25

© 2020 Walter de Gruyter GmbH, Berlin/Boston