Journal of Engineering Design

Traditional manufacturing systems around the world are undergoing a digital transformation fueled by exponentially growing technologies. The fourth industrial revolution is approaching and seeking ways to enhance production measures and management systems. Industry 4.0-driven digital transformation creates opportunities for complex and intelligent industrial information systems to manage and optimize productivity and specialization levels previously unattainable. The effective utilization of data obtained from the Industrial Internet of Things (IIoT) and big data analytics provides new potential to smart factories in terms of predictive maintenance and improved service quality. These new potentials significantly reinvent business organizations' operations and help recognize patterns to optimize performance by predicting failures and product quality issues before they occur.

The complex and intelligent industrial information system is one of the key initiatives for enhancing performance in smart factories and industrial automation. The primary objective is to develop web-based centralized tools for efficiently monitoring and managing complex industrial processes and acting as a decision support system for various stakeholders in effectively planning and developing industrial infrastructures. The system's purpose is to provide the right information at the right time for the right people, driving automated value-based workflows with reduced human intervention to perform higher-level manufacturing and production tasks. Most importantly, smart factories can integrate external contextual information sources with data and effectively implement them for real-time decision-making with intelligent information systems. This results in benefits such as improved preventive maintenance measures, operational efficiency, service quality, proactive decision-making capabilities, and enhanced productivity measures. Effective implementation of this technique provides a detailed virtual data-driven integrated view of all the operations associated with smart factories, ranging from supply chain management to equipment monitoring, finding efficient management practices, product testing, and customer satisfaction.

Towards this end, information systems are becoming an integral part of modern life, including the industrial sector. The trend is moving toward smart factories with requirements for more advanced tools to save time, cost, labor, maintenance, and upkeep. With intelligent information systems and smart manufacturing converging, the complex and intelligent industrial information system is emerging as a new innovative methodology for smart manufacturing using artificial intelligence-based technologies, including big data analytics and cognitive manufacturing. With more advanced research and development in this regard, it will spur a new surge of productivity.

The special issue on aims to explore the application of artificial intelligence (AI) in the design, management, and optimization of complex industrial information systems within the context of smart factories and Industry 4.0. Further, this special issue also aims to promote the exchange of knowledge and ideas between researchers, academicians, and industry experts on the use of AI in smart factories and Industry 4.0, and how it can lead to significant advancements in the field of industrial automation and digital transformation.

The following is a non-comprehensive list of representative topics within scope of this Special Issue.

• Advances in complex intelligent industrial information systems for management and optimization of smart manufacturing
• Challenges and solutions for digital transformation and the exponential use of smart manufacturing systems using intelligent information systems
• Advances in machine learning for quality management in smart factories
• Seamless integration of complex intelligent industrial information systems across smart factories for optimization of the performance and enhanced productivity
• Digital twins for optimization and predictive maintenance in the design and operation of smart manufacturing
• Optimization of IoT and big data with intelligent information systems for optimization of smart factories
• Developing a framework for evaluating the performance of AI and intelligent systems in smart manufacturing processes.
• AI and intelligent systems on supply chain management in smart manufacturing.
• Exploring the challenges of integrating AI and intelligent systems with legacy equipment and software systems in smart manufacturing.
• Developing a machine learning-based design optimization system for smart manufacturing
• Investigating the potential of deep learning algorithms for improving product quality in smart manufacturing
• Impact of AI and intelligent systems on the design and operation of flexible manufacturing systems
• Developing an AI-based quality control system for real-time detection of defects in smart manufacturing processes
• Investigating the use of edge computing in smart manufacturing and its impact on data processing and real-time decision-making
• Collaborative robots in smart manufacturing and their impact on human operators and productivity
• AI and intelligent systems for decision-making in design automation for smart manufacturing, and evaluating their impact on production quality and innovation

Authors should submit their manuscripts via the journal submission site:  https://www.tandfonline.com/journals/cjen20. Please visit the Instructions for Authors page for information on preparing your manuscript.

- Select "special issue title: AI-Driven Industrial Information Systems” when submitting your paper to ScholarOne

- Submissions can take the form of original research contributions, technical notes or perspectives/editorials, as well as the-state-of-the-art review and positioning papers.

- Expected publication date: January 31, 2024.

Instructions for AuthorsSubmit an Article