Energy conscious scheduling of dual gripper material handling robots in robotic manufacturing cells

Robotic cells are serial production systems that consist of a number of machines and a material handling robot that transfers parts between the machines. At the same time, the robots in the system function to load/unload the machines. In the academic literature and the business world, minimization of the cycle time is the dominant objective for the optimization of production schedules. In parallel to this objective, robot movements are assumed to be at their maximum speeds and the energy savings that can be attained with the dynamic adjustment of the speeds is not taken into account. Within the scope of this study, considering the controllability of the move speeds of the dual-gripper robot, it is aimed to determine the optimal robot move sequence and the operation parameters of the robot. In other words, we considered the energy consumption and throughput rate objectives simultaneously as a bi-criteria optimization model. In order to solve this bi-criteria model we used the epsilon-constraint approach, one of the objectives is written as a constraint. For the problem, a mixed integer non-linear mathemetical model (MINLP) is developed. In order to increase the solution efficiency, the problem is reformulated as a mixed integer second order constrained mathematical model (MISOCP). Computational tests revealed that the MINLP model cannot guarantee the optimal solution in reasonable times for systems with two or more machines. Since it is also observed that the MISOCP model is not efficient for the systems with six or more machines, a heuristic solution method called Efficient Solution Generation algorithm (ETA) is developed. By using the created data sets, these three solution approaches are investigated through a computational study. Additionally, as a result of these tests, it is observed that an average energy savings of 17.7\% can be attained by considering controllability of robot move speeds.