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Data-Based Supply Chain Collaboration - Improving Product Quality in Global Production Networks by Sharing Information

Silbernagel, Rainer ORCID iD icon; Wagner, Christian; Albers, Alexander; Trapp, Thies-Uwe; Lanza, Gisela

Abstract:

In times of globalization and digitalization, silo mentality and protectionism lead to competitive disadvantages for all partners of a production network. High scrap rates and low supplier margins in the production of high-precision products can be identified as resulting inefficiencies. Supply chain collaboration can contribute to significantly increase product quality by simultaneously reducing the associated costs, globally. We introduce batch allocation as a data-driven method for cross-company quality control of differing component batches based on both, supplier data and internal data. The industrial application is demonstrated within a global production network for manufacturing high-precision products.


Verlagsausgabe §
DOI: 10.5445/IR/1000141781
Veröffentlicht am 11.01.2022
Originalveröffentlichung
DOI: 10.1016/j.procir.2021.11.079
Scopus
Zitationen: 3
Dimensions
Zitationen: 4
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Produktionstechnik (WBK)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2021
Sprache Englisch
Identifikator ISSN: 2212-8271
KITopen-ID: 1000141781
Erschienen in 54th CIRP CMS 2021 - Towards Digitalized Manufacturing 4.0. Ed.: D. Mourtzis
Veranstaltung 54th CIRP Conference on Manufacturing Systems (CMS 2021), Online, 22.09.2021 – 24.09.2021
Verlag Elsevier
Seiten 470-475
Serie Procedia CIRP ; 104
Schlagwörter Global Production; Supply Chain Collaboration; Quality Assurance; Industry 4.0; Closed-Loop
Nachgewiesen in Scopus
Dimensions
Globale Ziele für nachhaltige Entwicklung Ziel 9 – Industrie, Innovation und Infrastruktur
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