International Journal of Production Research, 2024 (SCI-Expanded)
As the robots take over more logistics tasks in factories, the energy consumption of material handling robots becomes a significant concern. This study considers a robotic cell with two parallel machines and a material-handling robot transporting parts between the machines and buffer locations. A set of parts is to be scheduled on the machines. Also, the robot's moves, activities, and speed have to be planned. While programming a robot, its speed can be easily adjusted. Speeding up a robot can reduce the makespan of a schedule while increasing the robot's energy consumption. A holistic scheduling approach is required to coordinate machines' and robot activities. We first present a mathematical formulation and reformulate it via second-order cone programming inequalities. Then, we develop heuristic search algorithms: a greedy search algorithm and two versions of the simulated annealing algorithm. We test the proposed solution methods' computational performance and demonstrate that the robot speed control strategy can achieve significant energy savings.