Vision–language model-enabled cyberphysical link: emerging possibilities for production and operations management
Journal article, 2026

We introduce vision–language model (VLM)-enabled cyberphysical linking in production and operations management (POM). Drawing on four implemented cases that combine robotics, digital twins, and computer vision (CV), we propose how novel VLMs, together with more conventional CV and Internet-of-Things (IoT) technologies, enable new vision-based forms of cyberphysical linking across production and operations, during the beginning-of-life component manufacturing and end-of-life waste handling. We explore and explain the possibilities that emerge as the digital and physical become perceptually and operationally connected through VLMs. The research identifies four key design dimensions: persistent versus ad hoc digital counterparts, symbolic naming versus spatiotemporal identification, pre-planned versus interactive resource use, and passive versus self-controlling physical objects. VLM-based solutions are found to be potentially most impactful when integrated with persistent digital counterparts, interactive resources, and active physical objects. Further, a layered solution architecture that incorporates these design dimensions is proposed that provides a practical pathway for extending manufacturing execution systems. The findings advance cyberphysical operations and point to new directions for theory and practice in POM.

physical material

smart manufacturing

beginning of life

end of life

Cyberphysical link

digital counterpart

Author

Siavash Khajavi

Aalto University

Alireza Jaribion

University of South Florida

Zixuan Liu

Tulane University

Thorsten Wuest

University of South Carolina

Tarun Agrawal

Chalmers, Technology Management and Economics, Supply and Operations Management 00

Vesa Tiitola

University of Tampere

Jan Holmström

Aalto University

International Journal of Production Research

0020-7543 (ISSN) 1366-588X (eISSN)

Vol. In Press

Subject Categories (SSIF 2025)

Computer graphics and computer vision

DOI

10.1080/00207543.2026.2693038

More information

Latest update

7/13/2026