Resiliency and Adaptability for Future Manufacturing: AI Driven Recovery and Response Mechanisms

SCOPE AND DETAILS

The manufacturing sector is undergoing a transformative shift driven by rapid advancements in artificial intelligence (AI) and digital technologies. In the wake of unprecedented global challenges—such as the pandemic, supply chain disruptions, geopolitical uncertainties, climate change, and increasing environmental concerns—there is an urgent need for manufacturing systems that not only withstand shocks but also demonstrate remarkable resilience and adaptability. In this special issue, resiliency means the capacity of manufacturing systems to withstand disruptions, recover quickly, and maintain essential functions under adverse conditions, ensuring operational continuity and minimal downtime. Adaptability, on the other hand, refers to a manufacturing system's ability to quickly adjust to changing market conditions, product designs, or production processes. Traditional manufacturing infrastructures, designed for stability in predictable environments, are proving inadequate in today's fast-evolving landscape, where disruption is the norm rather than the exception. To navigate these uncertainties, manufacturers must adopt forward-thinking strategies that enable them to respond swiftly to changing conditions. AI-driven solutions offer a pathway to building future-proof manufacturing systems by facilitating real-time monitoring, predictive maintenance, and dynamic decision-making. These technologies allow manufacturing operations to quickly recover from disruptions, optimize production processes in real-time, and adapt to new constraints, ensuring continued efficiency and competitiveness in an unpredictable global market. This necessity has spotlighted the critical role of AI in revolutionizing traditional manufacturing paradigms, making the investigation of AI-driven recovery and response mechanisms more important than ever.

This special issue, titled “Resiliency and Adaptability for Future Manufacturing: AI-driven Recovery and Response Mechanisms,” aims to explore the critical role AI technologies play in developing resilient and adaptable manufacturing systems. We seek to investigate how AI-powered solutions—such as real-time data analytics, predictive maintenance, smart automation, and digital twins—can enhance a manufacturer’s ability to predict, adapt, and respond effectively to disruptions. This issue will serve as a comprehensive platform to discuss emerging strategies, frameworks, and technologies that enable manufacturers to become more responsive and flexible in a dynamic, uncertain world.

 

TOPICS

The special issue topics are categorized into three key areas: (1) Predictive AI Strategies for Disruption, Detection and Prevention, which focus on proactive forecasting and risk mitigation to enable swift recovery; (2) Adaptive AI Technologies for Real-time Response and Recovery, which emphasize dynamic tools for operational adjustment during and after disruptions; and (3) Integrated AI Frameworks for Long-term Adaptability and Resilience, which address holistic approaches including security, sustainability, and collaboration to build enduring response capabilities.

Predictive AI Strategies for Disruption Detection and Prevention

               ·        AI-enhanced Predictive Maintenance for Rapid Recovery in Resilient Manufacturing

               ·       AI-driven Supply Chain Resilience: Predicting and Mitigating Disruptions

               ·       Machine Learning Models for Proactive Risk Assessment and Response in Manufacturing Systems

Adaptive AI Technologies for Real-time Response and Recovery

               ·       Digital Twins and Virtual Simulation for AI-enabled Manufacturing Recovery Strategies

               ·       Smart Robotics and Autonomous Systems for Flexible Response in Disruptive Environments

               ·       Edge and Cloud Computing for Real-time Adaptability and AI-driven Disaster Recovery

               ·       AI-based Adaptive Production Scheduling in Post-disruption Manufacturing Scenarios

      Integrated AI Frameworks for Long-term Adaptability and Resilience

             ·       Cybersecurity Mechanisms Powered by AI for Protecting Resilient Manufacturing Responses

             ·       Human-AI Collaboration for Optimized Decision-making in Manufacturing Recovery and Response

      Important Dates

        Manuscript submission deadline: Friday, October 23, 2026
Notification of acceptance: Friday, November 21, 2025
Submission of final revised paper: Friday, January 28, 2028
Publication date (tentative): Friday, February 26, 2027

      Main Guest Editor

      Shengzong Zhou, Federation of Chinese Professional Associations in Europe; Gesellschaft Chinesischer Informatiker in Deutschland e.V. (GCI), sz.zhou.gci@gmail.com

      Guest Editors

      Robertas Damaševičius, Kaunas University of Technology, Lithuania, robertas.damasevicius@ktu.lt

      Sudan Jha, Kathmandu University, Nepal, sudan.jha@ku.edu.np