Multi-objective optimization design of a carbon fiber reinforced composite upper arm

During the process, operated mostly by robots, the large mass and the low fundamental frequency (FF) of industrial robot exert negative impact upon energy-consumption and operation accuracy, respectively. Hence, in this work carbon fiber reinforced composite (CFRP) is selected as the raw materials to machine a upper arm of the robotic arm. Besides, a multi-objective technique, Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II), is used to design the upper arm to obtain the trade-off solutions between robots mass and FF. In the process of optimization, ply numbers, ply angles and stacking sequences can be simultaneously optimized through integrating the finite element software with the optimizing software by running a written Python script. Finally, a upper arm optimized in composite is compared with a aluminum alloy counterpart, and its first fundamental frequency was improved 128% while weight merely increased by in contrast with the aluminum alloy.