Exploring and exploiting path based design optimization of a constant force mechanism. (October 2022)

• Record Type: Journal Article
• Authors: Rehman, Tanzeel Ur; Qaiser, Zeeshan; Ou, Haihua; Yi, Haiping; Johnson, Shane
• Is Part Of: Mechanism and machine theory. Volume 176(2022)
• Publication Date: 2022-10
• Subjects: Constant force mechanisms -- Compliant mechanisms -- Path based optimization; Machine theory -- Periodicals; Machinery -- Periodicals; Machines -- Périodiques; Génie mécanique -- Périodiques; Machine theory; Machinery; Periodicals; 621.81
• DOI: 10.1016/j.mechmachtheory.2022.104976
• Languages: English
• ISSNs: 0094-114X

Abstract

Highlights: CFM design that better explores and exploits the design space using an optimization. Higher percentage displacement compared with similar CFMs with reduced friction. Parent-child pairing of paths from a graph-based method to cut computational cost. More compact design compared with similar CFMs. Abstract: Compliant constant force mechanisms reduce wear and friction while providing precision in control, reduction in impact forces, and quasi zero stiffness. Current design techniques may result in high computational cost, significant stress concentrations, or design space inefficiencies. This study aims to give a low computational cost design strategy that more fully exploits the design space and reduces stress concentrations. A new design approach for these mechanisms is proposed that: (1) generates and describes paths from graph methods to avoid significant stress concentrations, (2) explores these paths to reduce the computational cost, and (3) more fully exploits the design space using design optimization. The optimized mechanism is then validated experimentally. The proposed method provides designs that exhibit a higher percentage of constant force-displacement (90% compared with 70.5%) compared with similar mechanisms of reduced friction in the literature. The design approach proposes five parent paths that can be optimized to design constant force mechanisms with arbitrary design requirements. This reduces the number of design variables and related computational costs required compared with similar methods in the literature.