An energy-aware scheduling problem in a job shop floor with moulding machines: a manufacturing industry case

The energy-intensive nature of moulding machine operations highlights the growing need for more efficient production and scheduling strategies. This paper examines an energy-aware flexible job shop scheduling problem in which consecutive operations of the same job can partially overlap, starting before the preceding operation has been completed. The problem incorporates both sequence-dependent and sequence-independent setup types in a production system with moulding machines, a novel problem that, to the best of our knowledge, has not been investigated before. To minimize electricity costs under real-time tariffs, the study develops a mixed-integer linear programming (MILP) model and a constraint programming (CP) model. Computational experiments involve 60 real-based random instances, designed to reflect realistic industrial settings. Throughout these instances, CP outperforms MILP in both speed and objective value, especially as instance size increases. In fact, MILP fails to find a feasible solution in one-third of the instances, while CP remains effective. Finally, the study validates the CP model’s practical applicability through a real-world manufacturing industry case study of an Italian fin producer that uses moulding machines.