Digital Twin and AI for Adaptive and Dynamic Planning and Operation in Smart Manufacturing Systems
A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Advanced Manufacturing".
Deadline for manuscript submissions: 31 October 2026 | Viewed by 87
Special Issue Editor
Interests: manufacturing systems; modeling and simulation; smart manufacturing; digital twins; industrial AI
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The transition toward smart manufacturing has reshaped the manufacturing industry. Production environments are no longer static; they are characterized by high volatility, customized demands, and frequent unforeseen disruptions such as machine breakdowns, urgent orders, or supply chain fluctuations. Digital twins and AI are at the center of these changes. While traditional planning and operation relied on static models, smart manufacturing maintains efficiency in these "living" manufacturing systems. Therefore, adaptive and dynamic planning and operation has emerged as critical issues in smart manufacturing systems. Based on real-time information and data from the shop floor, and advanced computational intelligence, these approaches enhance not only productivity, quality, lead time, and flexibility, but also systemic resilience, energy efficiency, and many other benefits in smart manufacturing.
The aim of this Special Issue is to gather cutting-edge research that addresses the challenges of intelligence-integrated planning and operation. We focus on how digital twins can be integrated with AI to realize practical, scalable, self-optimizing applications in smart manufacturing systems.
This Special Issue supports the scope of Machines by bridging the gap between planning and execution, showing how digital twins and AI act as the intelligent operating system for autonomous manufacturing.
- Intelligent Algorithms: meta-heuristics, deep reinforcement learning and multi-agent systems for adaptive and dynamic planning and operation.
- Autonomous Manufacturing: proactive and reactive planning and operation strategies for predictive, intelligent and autonomous manufacturing.
- AI-Enhanced Digital Twin-Driven Planning and Operation: digital twins with modeling and simulation, real-time synchronization and AI for smart manufacturing systems.
- Distributed Planning and Operation: strategies and architectures in decentralized smart manufacturing systems.
Prof. Dr. Sang Do Noh
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- digital twins
- AI
- planning and operation
- smart manufacturing
- autonomous manufacturing
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