Development of a decision support app for short term production control to improve the adherence to delivery dates

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dc.identifier.uri http://dx.doi.org/10.15488/9686
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/9742
dc.contributor.author Steinlein, Felix
dc.contributor.author Liu, Yuan
dc.contributor.author Stich, Volker
dc.date.accessioned 2020-03-16T15:21:42Z
dc.date.issued 2020
dc.identifier.citation Steinlein, Felix; Liu, Yuan; Stich, Volker: Development of a decision support app for short term production control to improve the adherence to delivery dates. In: Nyhuis, P.; Herberger, D.; Hübner, M. (Eds.): Proceedings of the Conference on Production Systems and Logistics : CPSL 2020. Hannover : publish-Ing., 2020, S. 438-447. DOI: https://doi.org/10.15488/9686 ger
dc.description.abstract In manufacturing, adherence to delivery dates is one of the main logistic goals. The production control department has to cope with short-term deviations from the planned route sheets. Because of unforeseen disruptions, e.g. machine breakdowns or shortage of material or personnel, in some situations, the promised delivery date to the customer is at stake. In practice, a fast and reasonable decision on how to deal with the delayed order is required. This decision process is often based on a qualitative analysis relying on the planner’s subjective assessment of a complex situation. To improve the quality of possible countermeasures this paper presents an application, which supports the decision process through a quantified analysis using real-time data from business application systems in combination with a simulation of the value stream. The developed app is part of the decision process and estimates the effect of selected countermeasures to accelerate a delayed order. Performance indicators illustrate the effect of the countermeasures on the specific order as well as the whole system. This approach empowers the planner to assess unforeseen situations and aims to improve the quality of the decision-making process. This paper describes the architecture of the application, its simulation ecosystem, the relevant data and the decision process to select the most effective countermeasures. eng
dc.language.iso eng
dc.publisher Hannover : publish-Ing.
dc.relation.ispartof https://doi.org/10.15488/9640
dc.relation.ispartof Proceedings of the Conference on Production Systems and Logistics : CPSL 2020
dc.rights CC BY 3.0 DE
dc.rights.uri https://creativecommons.org/licenses/by/3.0/de/
dc.subject Production Control eng
dc.subject Decision Support eng
dc.subject Discrete Event Simulation eng
dc.subject Adherence To Delivery Dates eng
dc.subject Disturbance Management eng
dc.subject.classification Konferenzschrift ger
dc.subject.ddc 620 | Ingenieurwissenschaften und Maschinenbau ger
dc.title Development of a decision support app for short term production control to improve the adherence to delivery dates
dc.type BookPart
dc.type Text
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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