The reduction of energy consumption is today addressed with great effort in manufacturing industry. A previously presented method for robotic system scheduling, which exploits variable execution time for the individual robot operations, has shown promising results for energy optimization. The method introduces linear time scaling of the trajectories to slow down the manipulators movements. This paper improves the scheduling method by generating energy optimal trajectories using dynamic time scaling. Dynamic programming can be applied to an existing trajectory and generate a new energy optimal trajectory that follows the same path but in a different execution time frame. With the new method, it is possible to solve the optimization problem for a range of execution times for the individual operations, based on one simulation only. A case study of a cell comprised of four six-link manipulators is presented, in which energy optimal dynamic time scaling is compared to linear time scaling. The results show that a significant decrease in energy consumption can be achieved for any given cycle time. Note to Practitioners-In robotic manufacturing systems, much energy is wasted due to an adopted minimum time policy for robot operations. This paper presents a method for producing energy efficient operations as well as an optimization model for scheduling these operations in robot cell. Implementation requires a flexible robot controller which allows manipulation of speed and acceleration profiles. The results are also of interest to industrial robot manufacturers, whom have full control over the robot controller and would like to offer energy efficient solutions to their customers.

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