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Adaptive model to increase resilience for emerging supply chains within the circular economy : "Zirkelmesser" an innovative case study

  • Variations in quantity, quality and time availability of input materials pose a major risk to circular supply chains (CSC) and require new models for creating and evaluating adaptive and resilient CSC in the circular economy (CE). This can be achieved through consistent modelling of the overarching relationship between resource input- and output streams, without neglecting the associated risks. The model proposed below consists of five components based on five resilience requirements for supply-chains (SCs). It provides a data-based recommended course of action for managers with a low entry-barrier. It consists of a CSC visualization, safety stock calculation, risk monitoring for each SC node, reporting logic, and a measurement catalogue.Variations in quantity, quality and time availability of input materials pose a major risk to circular supply chains (CSC) and require new models for creating and evaluating adaptive and resilient CSC in the circular economy (CE). This can be achieved through consistent modelling of the overarching relationship between resource input- and output streams, without neglecting the associated risks. The model proposed below consists of five components based on five resilience requirements for supply-chains (SCs). It provides a data-based recommended course of action for managers with a low entry-barrier. It consists of a CSC visualization, safety stock calculation, risk monitoring for each SC node, reporting logic, and a measurement catalogue. The inspiration for this model came from an innovative case study ("Zirkelmesser") in the metal processing industry, where secondary products and materials are used to produce new products. Here, the problem of maintaining the resource supply arose and led to resilience issues. The mentioned case study serves as an application example for the model application and contributes to making emerging circular supply chains predictable and more controllable, thus increasing their resilience.show moreshow less

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Metadaten
Document Type:Conference Object
Author:Jeff Mangers, Franz Wieck, Jana Nicolas, Peter Plapper, Manuel Löwer
URN (citable link):https://nbn-resolving.org/urn:nbn:de:bsz:wup4-opus-79886
DOI (citable link):https://doi.org/10.1016/j.procir.2022.05.063
Year of Publication:2022
Language:English
Source Title (English):Procedia CIRP
Volume:107
First Page:788
Last Page:793
Divisions:Kreislaufwirtschaft
Dewey Decimal Classification:600 Technik, Medizin, angewandte Wissenschaften
Licence:License LogoCreative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International