Optimal Usage of Robot Manipulators

Book chapter, 2010

Robot-based automation has gained increasing deployment in industry. Typical application examples of industrial robots are material handling, machine tending, arc welding, spot welding, cutting, painting, and gluing. A robot task normally consists of a sequence of the robot tool center point (TCP) movements. The time duration during which the sequence of the TCP movements is completed is referred to as cycle time. Minimizing cycle time implies increasing the productivity, improving machine utilization, and thus making automation affordable in applications for which throughput and cost effectiveness is of major concern. Considering the high number of task runs within a specific time span, for instance one year, the importance of reducing cycle time in a small amount such as a few percent will be more understandable. Robot manipulators can be expected to achieve a variety of optimum objectives. While the cycle time optimization is among the areas which have probably received the most attention so far, the other application aspects such as energy efficiency, lifetime of the manipulator, and even the environment aspect have also gained increasing focus. Also, in recent era virtual product development technology has been inevitably and enormously deployed toward achieving optimal solutions. For example, off-line programming of robotic workcells has become a valuable means for work-cell designers to investigate the manipulator’s workspace to achieve optimality in cycle time, energy consumption and manipulator lifetime. This chapter is devoted to introduce new approaches for optimal usage of robots. Section 2 is dedicated to the approaches resulted from translational and rotational repositioning of a robot path in its workspace based on response surface method to achieve optimal cycle time. Section 3 covers another proposed approach that uses a multi-objective optimization methodology, in which the position of task and the settings of drive-train components of a robot manipulator are optimized simultaneously to understand the trade-off among cycle time, lifetime of critical drive-train components, and energy efficiency. In both section 2 and 3, results of different case studies comprising several industrial robots performing different tasks are presented to evaluate the developed methodologies and algorithms. The chapter is concluded with evaluation of the current results and an outlook on future research topics on optimal usage of robot manipulators.