Design Optimization of a Wearable Chair Using the Bees Algorithm

Abstract

A wearable chair is designed to reduce musculoskeletal disorders in workers. Two-staged optimization process using The Bees Algorithm is conducted to determine the lowest operable height of the chair and minimize the maximum force among the three supports. Geometric, dimensional, and rotational angle constraints are defined accordingly. A CAD model of the chair is imported into ADAMS software for simulation. The simulation results identified the most stressed rod in the chair. A spring is selected and implemented in ADAMS to counteract the applied force on this rod. A comparison between the force on the most stressed support and the spring force through a defined motion revealed minimal differences, indicating that the spring effectively counteracted the applied force. The results demonstrated the successful application of The Bees Algorithm to wearable chairs and the successful implementation of a spring to counteract applied force, thereby achieving the objectives of this study.