Building a collaborative manufacturing system’s network resilience through an adaptability potential analysis

Selma Ferhat (), Raphaël Oger (), Eric Ballot () and Matthieu Lauras ()
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Selma Ferhat: CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique, CGI - Centre Génie Industriel - IMT Mines Albi - IMT École nationale supérieure des Mines d'Albi-Carmaux - IMT - Institut Mines-Télécom [Paris]
Raphaël Oger: CGI - Centre Génie Industriel - IMT Mines Albi - IMT École nationale supérieure des Mines d'Albi-Carmaux - IMT - Institut Mines-Télécom [Paris]
Eric Ballot: CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique
Matthieu Lauras: CGI - Centre Génie Industriel - IMT Mines Albi - IMT École nationale supérieure des Mines d'Albi-Carmaux - IMT - Institut Mines-Télécom [Paris]

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Abstract: Purpose This research aims to investigate how adaptability potential analysis in collaborative manufacturing networks can be used to enhance resilience when addressing innovative production challenges that require change initiatives. Design/methodology/approach A literature review on collaborative adaptive systems showed a lack of solutions to adapt production to an unpredicted product within a network. A framework is proposed for evaluating the adaptability of collaborative networks and providing inter-system adaptation recommendations. We demonstrate the applicability of this approach through an illustrative experimentation involving a cosmetic company seeking to produce a new product, hydroalcoholic gels in the context of collaborative networks. Findings The experimentation demonstrates that the adaptability analysis based on ontology can help different manufacturing systems make decisions based on their state and limits of capabilities. Also, our adaptation recommendations may help understand the economic impacts of collaboration for different scenarios before launching. Research limitations/implications The research scope does not extend to the consideration of quantity and operational aspects. Additionally, the reconfigurability aspects within each manufacturing system, such as the reordering of layout sequences, have not been addressed yet. Practical implications The results allow organizations to compare resilience states from an individual and collaborative perspective, enabling them to make informed decisions about new production opportunities and effectively navigate the changing manufacturing landscape. Originality/value This research combines capability-based analysis and a collaborative network perspective to streamline decision-making for systems facing new production demands. It provides new insights into effectual decision-making, empowering organizations to skilfully manage unexpected challenges and identify suitable partners accordingly.

Keywords: Collaborative networks; Resilience; Manufacturing systems; Adaptability; Ontology; Innovative production (search for similar items in EconPapers)
Date: 2024
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Published in European Journal of Innovation Management, inPress, ⟨10.1108/EJIM-12-2023-1144⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04834992

DOI: 10.1108/EJIM-12-2023-1144

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