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AI-enabled evolution: unveiling the synergy between manufacturing and services through coordination and integration.

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Title: AI-enabled evolution: unveiling the synergy between manufacturing and services through coordination and integration.
Authors: Yin, Yunqiang1 (AUTHOR), Chu, Feng2 (AUTHOR), Dolgui, Alexandre3 (AUTHOR), Wang, Dujuan4 (AUTHOR) djwang@scu.edu.cn, Ignatius, Joshua5 (AUTHOR), Jayaram, Jayanth6 (AUTHOR)
Source: International Journal of Production Research. Jan2026, Vol. 64 Issue 2, p539-544. 6p.
Subjects: Artificial intelligence, Manufacturing industries, Supply chains, Organization, Process optimization, Dynamic capabilities, Operations management
Abstract: Coordination and integration are fundamental pillars of modern supply chains, within which manufacturing and service operations function as two core components. Recently, the growing availability of data, coupled with rapid advances in artificial intelligence (AI), has significantly accelerated the adoption of AI technologies across manufacturing and service domains. Against this backdrop, we completed a special issue titled "AI-Enabled Evolution: Unveiling the Synergy between Manufacturing and Services through Coordination and Integration" to showcase the latest developments in this domain. In this editorial, we first outline the background and review existing literature on AI applications in operations management. We then present the papers included in this issue, highlighting how various AI techniques are applied across manufacturing and service contexts, encompassing performance improvement and sustainability advancement, optimisation and decision-making framework development, as well as applications in logistics, scheduling, and risk management. Finally, we conclude by identifying promising avenues for future research. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: AI-enabled evolution: unveiling the synergy between manufacturing and services through coordination and integration.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Jan2026, Vol. 64 Issue 2, p539-544. 6p.
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  Data: <searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Manufacturing+industries%22">Manufacturing industries</searchLink><br /><searchLink fieldCode="DE" term="%22Supply+chains%22">Supply chains</searchLink><br /><searchLink fieldCode="DE" term="%22Organization%22">Organization</searchLink><br /><searchLink fieldCode="DE" term="%22Process+optimization%22">Process optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamic+capabilities%22">Dynamic capabilities</searchLink><br /><searchLink fieldCode="DE" term="%22Operations+management%22">Operations management</searchLink>
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  Data: Coordination and integration are fundamental pillars of modern supply chains, within which manufacturing and service operations function as two core components. Recently, the growing availability of data, coupled with rapid advances in artificial intelligence (AI), has significantly accelerated the adoption of AI technologies across manufacturing and service domains. Against this backdrop, we completed a special issue titled "AI-Enabled Evolution: Unveiling the Synergy between Manufacturing and Services through Coordination and Integration" to showcase the latest developments in this domain. In this editorial, we first outline the background and review existing literature on AI applications in operations management. We then present the papers included in this issue, highlighting how various AI techniques are applied across manufacturing and service contexts, encompassing performance improvement and sustainability advancement, optimisation and decision-making framework development, as well as applications in logistics, scheduling, and risk management. Finally, we conclude by identifying promising avenues for future research. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/00207543.2025.2592502
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        Text: English
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        Type: general
      – SubjectFull: Manufacturing industries
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      – SubjectFull: Supply chains
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              Text: Jan2026
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