Modelling the Make Process of the Mineral Supply Chain Upstream Segment

Raúl Castillo-Villagra (), Gabriel Icarte and Klaus-Dieter Thoben
Additional contact information
Raúl Castillo-Villagra: Faculty of Production Engineering, Universität Bremen, 28359 Bremen, Germany
Gabriel Icarte: Faculty of Engineering and Architecture, Universidad Arturo Prat, Iquique 1110939, Chile
Klaus-Dieter Thoben: BIBA-Bremer Institut für Produktion und Logistik GmbH, 28259 Bremen, Germany

Resources, 2023, vol. 12, issue 11, 1-31

Abstract: The upstream segment of the minerals supply chain (MiSC) is the backbone for achieving the transition to clean energy by securing the supply of minerals. Recently, the MiSC has been disrupted, affecting mineral supply and generating uncertainty among clean energy producers. Supply chain (SC) mapping addresses this uncertainty, providing a holistic end-to-end view. However, MiSC mapping studies mainly focus on the downstream segment, leaving aside the upstream segment. In this context, the fundamental gap is the lack of standardized modelling frameworks that can accurately represent the upstream segment dynamics and, at the same time, seamlessly integrate with the downstream segment. This paper bridges this gap, designing a model for the MiSC upstream segment (MiSCOR). Framed within design science research methodology, MiSCOR is built by adapting two reference models, the Exploration and Mining Business Reference Model (EM) and the Supply Chain Operations Reference Model (SCOR), focusing on the commodity-making process. The MiSCOR demonstrates its applicability and robustness in real operational scenarios of one of the largest copper producers. MiSCOR provides a management tool for practitioners and decision-makers in the MISC’s upstream segment, offering blueprints to throw functional silos, foster collaboration, and a standardized framework that integrates seamlessly with the downstream segment.

Keywords: supply chain modelling; mineral supply chain; copper mining; design science research; business process modelling; SCOR (search for similar items in EconPapers)
JEL-codes: Q1 Q2 Q3 Q4 Q5 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2079-9276/12/11/132/pdf (application/pdf)
https://www.mdpi.com/2079-9276/12/11/132/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jresou:v:12:y:2023:i:11:p:132-:d:1276177

Access Statistics for this article

Resources is currently edited by Ms. Donchian Ma

More articles in Resources from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().