A model predictive control approach for energy saving optimization of an electronic assembly line.

The energy-saving potential of original equipment manufacturers (OEMs) for electronic products is substantial owing to the huge market size of assembling industry in China. A semi-automatic electronic assembly line (SAEAL) for smart-phones is introduced, and its digital twin (DT) enabled energy-saving platform is developed as the hardware foundation. We propose a stochastic dynamics model via max-plus algebra to characterize the spatio-temporal nature of state transition, which provides dynamical opportunity windows for further energy-saving control strategy. Accordingly, model linearization is conducted to obtain linear state and output equations. Then, a model predictive control (MPC) approach for energy saving optimization is provided to determine the optimal start-stop control signal. The dynamics modeling and MPC approach have been applied and verified in the case of assembly line. The results show that the optimization approach could reach a proportion of 49% for the equipment sleep time of total running time and save a considerable amount of energy for normal production of OEMs. [Display omitted] • A digital twin prototype system of smart-phone assembly line is developed as the testing platform for energy-saving control. • The assembling behaviors of assembly line are depicted by linear state equations via max-plus semiring algebra. • A spatio-temporal dynamics model is provided to evaluate the system performance based on max-plus semiring algebra. • An energy-saving MPC approach is proposed to determine the start-stop control sequences of automatic machines. • The equipment's sleeping time can reach a proportion of 49% of total running time without production efficiency loss. [ABSTRACT FROM AUTHOR]