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ABSTRACTEnergy management effectively reduces energy consumption, improves material utilisation, minimises emissions and maximises product output during manufacturing. Thus, enterprises are implementing an energy management strategy and improving sustainable competitive advantage. With the rapid development of the Internet of Things, Cyber-Physical Systems and Big Data, sustainable smart manufacturing provides a new strategy for energy management by applying advanced information technologies. In practice, energy management is an enormous opportunity given the lack of such implementation. This paper presents a case-practice-theory-based (CPTB) method of implementing energy management in the manufacturing factory for energy saving and emission reduction. The closed-loop structure of the proposed CPTB method is designed and implemented. Then, an application of six hot-blast stoves in moulding workshops of a partner company is presented to demonstrate the proposed method. Results showed that after employing the method, the unit energy consumption of production reduced by approximately 3%, and saved energy costs reached 4%. Finally, a discussion analyses the managerial implications for ceramic and other energy-intensive manufacturing industries.

ABSTRACTOwing to the lack of effective energy consumption models of ball mills in the ceramic industry, a calculation model to forecast energy consumption of ceramic ball mills during the grinding process was developed based on power feature deployment. The energy consumption of the working process was defined by different combinations of power of components involved in tasks. The total energy consumption was divided into three parts: power lost in the electrical motor, power lost in mechanical transmission and power used for grinding materials. These three components were described separately by taking the principle of an electrical motor, mechanical transmission and grinding process into account. Measurement results of two ball mills in a real ceramic manufacturing plant showed that the proposed calculation models could achieve an accuracy of more than 96% for predicting the ball mill energy consumption during which the power fluctuates periodically to complete one rotation cycle of the ball mills.

Owing to the lack of effective energy consumption models of ball mills in the ceramic industry, a calculation model to forecast energy consumption of ceramic ball mills during the grinding process was developed based on power feature deployment. The energy consumption of the working process was defined by different combinations of power of components involved in tasks. The total energy consumption was divided into three parts: power lost in the electrical motor, power lost in mechanical transmission and power used for grinding materials. These three components were described separately by taking the principle of an electrical motor, mechanical transmission and grinding process into account. Measurement results of two ball mills in a real ceramic manufacturing plant showed that the proposed calculation models could achieve an accuracy of more than 96% for predicting the ball mill energy consumption during which the power fluctuates periodically to complete one rotation cycle of the ball mills.