6. Conclusions and future works
Green and sustainable manufacturing are the main directions of the future manufacturing industry. Enhancing the intelligence of product design and manufacturing processes, and realising intelligent manufacturing have received increasing attention in many national manufacturing strategic plans. However, the main aim of intelligent manufacturing is to improve energy efficiency and reduce pollutant emissions. Therefore, enhancing intelligent ECEA and reducing energy consumption in product life cycle is one of the key problems faced by the modern manufacturing industry. In order to address this issue, an IoT and cloud-based ECEA method is proposed in this paper. In the proposed method, energy flow and data management of the ECEA of a product is analysed, a six-layered architecture (i.e. service collection layer, ECEA Cloud layer, service manager layer, user layer, IoT layer, and physical manufacturing life cycle layer) ECEA system based on IoT and cloud is proposed. IoTbased ECEA data collection and the related experimental bench have been designed and the ECEA model for product and ECEA Cloud is established. A prototype system is developed to validate the proposed method. Finally, a case study is provided to test and validate the effectiveness of the proposed approach in the design and manufacturing processes of a product.
