Cost-effective industrial internet of things network planning for sustainable manufacturing systems

The industrial Internet of Things (IoT) has been gaining significant momentum and is considered a promising technology for establishing a foundation for energy and carbon management in the manufacturing sector. Existing management studies commonly assume the availability of IoT data for all manufacturing equipment, yet connecting every single piece of equipment requires enormous investments without necessarily yielding significant improvements in management effectiveness. In practice, the value derived from IoT data collected from diverse manufacturing equipment varies based on the unique features of the equipment and its role within the manufacturing system. Therefore, this study proposes a planning method for cost-effective industrial IoT networks in the context of sustainable manufacturing. The proposed approach jointly considers the quality-of-service requirements of the IoT network and the characteristics of the manufacturing system. It aims to balance the trade-offs between industrial IoT investments and the effectiveness of IoT data-enabled carbon management in manufacturing systems. In addition, an efficient algorithm is developed to solve the network planning problem and identify cost-effective solutions. Case studies on automobile assembly lines indicate the effectiveness of the proposed method in generating economically favorable industrial IoT networks, leading to a 38.9% reduction in industrial IoT implementation costs while maintaining satisfactory carbon emission reduction effects for manufacturing systems.