High Efficiency Manufacturing With a Smart Carbon Fiber End Effector

Abstract

Abstract Advanced industrial assembly lines often utilize large-scale robotic arms such as the Fanuc S 420-F. Such arms, and their end-effectors, are typically constructed from high-strength steel, which gives the systems superior rigidity at the cost of being very heavy. A new cutting-edge composite material, carbon fiber, offers the strength of steel at a fraction of the weight. To improve energy efficiency, this research project analyzed the feasibility of replacing the steel structure in an end-effector with a carbon-fiber composite, in addition to equipping the end effector with revolutionary ‘Smart’ technologies. Simulations performed in Siemens’ Process Simulate Tecnomatix module helped to inform mechanical energy computations for an arbitrary pick and place task and energy cost estimations were analyzed with the end-effector constructed from both steel and carbon fiber. The projected change in energy consumption for performing the pick and place task was then compared to determine the potential benefit of the carbon fiber substitution. In addition to the advanced material use, this research project also investigated the possibility of implementing ‘Smart’ technologies in the custom end effector design to further improve energy efficiency. The proposed smart technology would utilize machine vision to actively direct vacuum pressure to only the necessary suction cups in a pneumatic gripper array. Possible energy savings associated with the smart end effector design were analyzed. Simulation results for a simple pick and place operation showed that the Smart Carbon Fiber End Effector required only 2.22 Kilojoules of energy, compared to the 3.92 Kilojoules of energy needed for a Passive Steel Framed End Effector. Through creation and simulation with Digital Design Tools, the feasibility of combining advanced new structural materials with integrated intelligence was explored to create a revolutionary new end effector design that could reduce the energy consumption for a pick and place task.