Intelligent Automation and AI-Driven Optimization in Advanced Manufacturing Systems

Dear Colleagues,

We cordially invite you to contribute to this Special Issue on "Intelligent Automation and AI-Driven Optimization in Advanced Manufacturing Systems", a rapidly evolving field that is transforming traditional reactive agents into autonomous, goal-driven systems capable of learning, adapting, and making independent decisions in complex manufacturing environments.

Artificial intelligence (AI), particularly through the integration of foundational models such as SLMs, LLMs, and VLMs, and combined with the power of GPUs and cloud computing, offers unprecedented generality, scalability, and applicability to a wide range of manufacturing tasks. These advances are reshaping how intelligent agents operate on the shop floor.

However, accomplishing the full potential of AI in manufacturing presents significant challenges, including the following:

• Data scarcity in unstructured or dynamic environments,
• High uncertainty arising from sensory variability,
• Security and safety risks in physical interactions,
• The need for real-time decision-making in mission-critical processes.
• Addressing these challenges is key to enabling the shift from reactive automation to truly autonomous manufacturing systems.

This Special Issue seeks to explore the convergence of AI, control systems, robotics, and data analytics to foster intelligent, adaptive, and efficient manufacturing environments. We welcome interdisciplinary contributions from machine learning, industrial engineering, control theory, robotics, and computer science, with a strong emphasis on practical applications and real-world impact.

Suggested Topics (including but not limited to):

• Autonomous Robots: AI-powered robots that work flexibly and collaborate with humans.
• Cyber-Physical Systems (CPS): Combining AI with physical systems for real-time control and optimization.
• Machine Vision and Perception: AI-based computer vision for quality checks and defect detection.
• Digital Twins: Virtual models of physical systems for simulation and optimization.
• AI-Driven Optimization: Using AI to adjust manufacturing settings in real-time.
• Predictive Maintenance: Using data to predict and prevent equipment breakdowns.
• Supply Chain and Production Planning: AI for managing scheduling, demand, and inventory.
• Quality Control: Real-time AI systems to ensure product quality.
• Industry 4.0 Technologies: Using IoT, cloud computing, and big data to improve manufacturing.
• Human-Machine Collaboration: AI helping humans with decision-making and control.
• Sustainable and Resilient Manufacturing: AI for reducing waste, saving energy, and adapting to disruptions.
• Emerging soft robotics applications: Embedded sensing systems are unlocking innovative applications in areas such as human–machine interfaces, industrial automation, and more. These advancements demonstrate the transformative potential of AI-driven soft robotics across multiple domains.

We look forward to your contributions that advance the field of intelligent, agentic AI in manufacturing. 

Dr. Ismael Lopez-Juarez
Prof. Dr. Alejandro A. Castillo Atoche
Guest Editors

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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Technologies 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 1600 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.

• agentic AI
• AI-driven optimization
• collaborative robots (Cobots)
• cyber-physical systems (CPS)
• deep learning
• digital twins
• foundational models (SLMs, LLMs, VLMs)
• Industry 4.0
• machine vision
• predictive maintenance
• quality control
• real-time decision making
• reinforcement learning (RL)
• soft robotics
• supply chain optimization
• sustainable manufacturing