Advanced Manufacturing Launches New Special Issue: Adaptive Scheduling in IoT-Enabled Smart Manufacturing Networks
Advanced Manufacturing (AM) is pleased to announce the launch of a new Special Issue entitled “Adaptive Scheduling in IoT-Enabled Smart Manufacturing Networks.” This Special Issue aims to highlight recent advances in intelligent scheduling technologies and their applications in smart manufacturing, providing a global platform for researchers and practitioners to exchange innovative ideas and solutions toward the development of flexible, efficient, and resilient manufacturing systems.The rapid evolution of Internet of Things (IoT) technologies, artificial intelligence, and distributed computing has transformed traditional manufacturing systems into intelligent, interconnected networks. IoT-enabled smart manufacturing networks enable real-time data collection and processing from connected devices, allowing adaptive scheduling systems to respond dynamically to changes in production demands, machine conditions, and resource availability. By integrating advanced approaches such as edge and fog computing, reinforcement learning, Q-learning, and evolutionary optimization algorithms, adaptive scheduling offers new opportunities to enhance operational efficiency, flexibility, and autonomy in Industry 4.0.This Special Issue focuses on methodological, empirical, and theoretical research addressing the challenges and opportunities in adaptive scheduling for IoT-enabled smart manufacturing networks. It explores how real-time data analytics, intelligent algorithms, and emerging computing architectures can support autonomous decision-making and optimize complex manufacturing processes.Topics of interest include, but are not limited to:Advances and opportunities in IoT-enabled smart manufacturing networksReal-time adaptive scheduling methods and optimization techniquesIoT sensor-based data collection and intelligent manufacturing systemsEdge and fog computing technologies for smart manufacturing applicationsArtificial intelligence and machine learning approaches for adaptive schedulingChallenges and solutions for agile, resilient, and autonomous manufacturingPrivacy, trust, and security in IoT-enabled smart manufacturing networksData-driven approaches for Industry 4.0 and circular economy applicationsAdvanced architectures for efficient data processing and resource managementCollaborative technologies and disruptive innovations in smart manufacturingThis Special Issue is edited by Dr. Jianming Zhang (Case Western Reserve University, USA), Prof. Yu Xue (Nanjing University of Information Science and Technology, China), and Prof. Sunil Kumar Jha (Adani University, India), who bring extensive expertise in smart manufacturing, intelligent systems, and advanced computing technologies. Researchers worldwide are warmly invited to submit original research articles and high-quality review papers.Submission deadline: 31 January 2027Article Processing Charges (APCs): APCs are fully waived for all manuscripts submitted by 31 December 2026. Beginning 1 January 2027, an APC of USD 800 (excluding VAT) will apply to each accepted manuscript.All submissions will undergo the journal’s standard rigorous peer-review process.For more information and submission guidelines, please visit the Special Issue webpage or contact the editorial office at advmanufact@elspub.com
Published Date:
21 Jul 2026
