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An approach and decision support tool for forming Industry 4.0 supply chain collaborations

An approach and decision support tool for forming Industry 4.0 supply chain collaborations
An approach and decision support tool for forming Industry 4.0 supply chain collaborations

Industry 4.0 technologies, process digitalisation and automation can be applied to support the formation of supply chain collaborations in manufacturing. Underpinned by information and communication technologies, collaborations of independent companies can dynamically pool production capacities and capabilities to jointly react to new business opportunities. These collaborations may involve a wide range of enterprises with different sizes and scope that individually would not be able to tender for such new business opportunities. To form these collaborative teams, assistive processes and technologies can underpin the effort towards exploring the tender requirements, unbundling the tender into smaller tasks and finding a suitable supplier for each task. In this paper, we present an approach and a tool to support decision making concerning forming supply chain collaborations in Industry 4.0. The approach proposed is unique in integrating industry domain ontologies, assistive human-computer interaction tools and multi-criteria decision support techniques to form team compositions speeding-up the collaboration process whilst maximising the chances of forming a viable team to fulfil the tender requirements. We also show evaluation results involving stakeholders from the supply chain function pointing to the effectiveness of the proposed solution, available online as a demo1.

Decision support systems, Digitalization, Industry 4.0, Interoperability, Ontology, Supply chain collaboration
0166-3615
Cisneros-Cabrera, Sonia
e4e92f36-f215-4e25-9b77-7892d2fab186
Pishchulov, Grigory
ed08563f-5d58-42f7-9b02-b807947fad93
Sampaio, Pedro
10e329f8-6256-4805-9732-a4c178646194
Mehandjiev, Nikolay
a8559f54-9ca9-4821-91de-dd8751f6fd9f
Liu, Zixu
1b07df56-a07b-4e78-bebc-38657ca80f76
Kununka, Sophia
0fc12305-3e78-46d3-b7cb-eb1c460efccd
Cisneros-Cabrera, Sonia
e4e92f36-f215-4e25-9b77-7892d2fab186
Pishchulov, Grigory
ed08563f-5d58-42f7-9b02-b807947fad93
Sampaio, Pedro
10e329f8-6256-4805-9732-a4c178646194
Mehandjiev, Nikolay
a8559f54-9ca9-4821-91de-dd8751f6fd9f
Liu, Zixu
1b07df56-a07b-4e78-bebc-38657ca80f76
Kununka, Sophia
0fc12305-3e78-46d3-b7cb-eb1c460efccd

Cisneros-Cabrera, Sonia, Pishchulov, Grigory, Sampaio, Pedro, Mehandjiev, Nikolay, Liu, Zixu and Kununka, Sophia (2021) An approach and decision support tool for forming Industry 4.0 supply chain collaborations. Computers in Industry, 125, [103391]. (doi:10.1016/j.compind.2020.103391).

Record type: Article

Abstract

Industry 4.0 technologies, process digitalisation and automation can be applied to support the formation of supply chain collaborations in manufacturing. Underpinned by information and communication technologies, collaborations of independent companies can dynamically pool production capacities and capabilities to jointly react to new business opportunities. These collaborations may involve a wide range of enterprises with different sizes and scope that individually would not be able to tender for such new business opportunities. To form these collaborative teams, assistive processes and technologies can underpin the effort towards exploring the tender requirements, unbundling the tender into smaller tasks and finding a suitable supplier for each task. In this paper, we present an approach and a tool to support decision making concerning forming supply chain collaborations in Industry 4.0. The approach proposed is unique in integrating industry domain ontologies, assistive human-computer interaction tools and multi-criteria decision support techniques to form team compositions speeding-up the collaboration process whilst maximising the chances of forming a viable team to fulfil the tender requirements. We also show evaluation results involving stakeholders from the supply chain function pointing to the effectiveness of the proposed solution, available online as a demo1.

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Accepted/In Press date: 21 December 2020
e-pub ahead of print date: 14 January 2021
Published date: 1 February 2021
Additional Information: Funding Information: The work presented has received funding from the European Commission under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 723336). Financial support has been provided by the National Council of Science and Technology (abbreviated CONACyT) to Sonia Cisneros-Cabrera (agreement no. 461338). We are grateful to the Guest Editor Professor Shenle Pan and five anonymous reviewers for constructive and insightful comments on the paper. We wish to thank Arturo Jimenez, Qudamah Quboa, Tomas Grubhoffer, Jan Rada, and Jan Dyrczyk for their contribution to implementing the TDMS, and Carolyn Langen and Menno Guldemond for their work on providing the risk scores. Also, we thank the DIGICOR project team members for their invaluable input which shaped our work, and Nikolai Kazantsev for his suggestions and discussions. Publisher Copyright: © 2020 Elsevier B.V.
Keywords: Decision support systems, Digitalization, Industry 4.0, Interoperability, Ontology, Supply chain collaboration

Identifiers

Local EPrints ID: 471824
URI: http://eprints.soton.ac.uk/id/eprint/471824
ISSN: 0166-3615
PURE UUID: d28a33ac-45f4-4396-b1bb-603993d42f8a
ORCID for Zixu Liu: ORCID iD orcid.org/0000-0002-4806-5482

Catalogue record

Date deposited: 21 Nov 2022 17:45
Last modified: 22 Nov 2022 03:00

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Contributors

Author: Sonia Cisneros-Cabrera
Author: Grigory Pishchulov
Author: Pedro Sampaio
Author: Nikolay Mehandjiev
Author: Zixu Liu ORCID iD
Author: Sophia Kununka

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