Data-based identification of throughput time potentials in production departments

verfasst von
Lasse Härtel, Peter Nyhuis
Abstract

Logistics performance becomes an ever more important strategic factor for manufacturing companies to obtain a competitive advantage. Yet, numerous companies fail to meet their own corporate goals or customer requirements. One of the most important objectives in logistics is speed in terms of short delivery times which are mainly determined by the production throughput times. Derivation of effective improvement measures requires a profound understanding of logistic cause-effect relationships. At a time of increasing digitalization, an increasing amount of feedback data is available that offers great potentials to discover novel insights. Yet, the vast amount of data can also be overwhelming and result in unsystematic and ineffective analysis of less meaningful data. Therefore, in this paper a systematic procedure is presented that allows data-based identification of throughput time potentials in production departments. The quantitative analysis framework is based on a generic driver tree structuring the influencing factors on throughput time. The approach will boost the understanding about logistics relations and will particularly help SMEs to focus on the most relevant influencing factors and data. Furthermore, it provides a basis for future more advanced information systems that will help companies to continuously improve their logistics performance and adapt their supply chains to ever-changing conditions.

Organisationseinheit(en)
Institut für Fabrikanlagen und Logistik
Typ
Konferenzaufsatz in Fachzeitschrift
Journal
Proceedings of the Conference on Production Systems and Logistics
Seiten
239-248
Anzahl der Seiten
10
Publikationsdatum
2020
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
ASJC Scopus Sachgebiete
Wirtschaftsingenieurwesen und Fertigungstechnik, Maschinenbau, Technologie- und Innovationsmanagement, Strategie und Management
Ziele für nachhaltige Entwicklung
SDG 9 – Industrie, Innovation und Infrastruktur
Elektronische Version(en)
https://doi.org/10.15488/9665 (Zugang: Offen)