Ruoqi Geng, Cardiff University

Di Li, University of Warwick

Yang Cheng, Aalborg University

This special issue seeks empirical research demonstrating how artificial intelligence is embedded within and enhances digital production technologies in real operational contexts. The focus is on understanding implementation pipelines and socio-technical conditions that enable AI-enabled solutions to function effectively as operational workflows. Purely conceptual, literature-based, or modelling studies without empirical validation are excluded.

Acceptable empirical research uses real-world operational evidence such as production logs, IoT sensors, machine telemetry, or industrial case studies, potentially employing machine learning or optimization when grounded in real data and validated in industrial settings with measurable outcomes. Studies must address the full AI implementation pipeline, from translating production decisions into AI use cases, to ensuring data readiness, to embedding AI outputs into human-AI workflows linked to measurable production outcomes.

Appel publié par Production Planning & Control. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI-Augmented Production Planning and Control
• Business–AI Alignment and AI Readiness Pipeline for Production Systems
• AI-enabled Quality and Process Control
• Agentic and Workflow-Oriented Deployment in Production
• AI-Enabled Cyber–Physical Production Systems and Digital Twins
• AI and Additive Manufacturing
• AI and Blockchain for Production Systems
• Human–AI Interaction and Organisational Transformation
• Empirical Innovations in Data, Measurement, and Evaluation
• Extended Production Contexts (Production-Adjacent Physical Operations)

Timeline

• September 1, 2026: Call for Papers released
• June 30, 2027: Manuscript submission deadline
• September 1, 2027: First-round decisions
• December 1, 2027: Revised manuscripts due
• June 1, 2028: Final decisions