A new approach to scheduling in manufacturing for power consumption and carbon footprint reduction

Manufacturing scheduling strategies have historically emphasized cycle time; in almost all cases, energy and environmental factors have not been considered in scheduling. This paper presents a new mathematical programming model of the flow shop scheduling problem that considers peak power load, energy consumption, and associated carbon footprint in addition to cycle time. The new model is demonstrated using a simple case study: a flow shop where two machines are employed to produce a variety of parts. In addition to the processing order of the jobs, the proposed scheduling problem considers the operation speed as an independent variable, which can be changed to affect the peak load and energy consumption. Even with a single objective, finding an optimal schedule is notoriously difficult, so directly applying commercial software to this multi-objective scheduling problem requires significant computation time. This paper calls for the development of more specialized algorithms for this new scheduling problem and examines computationally tractable approaches for finding near-optimal schedules.