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An adaptive, repeatable and rapid auto-reconfiguration process in a smart manufacturing system for small box assembly

Zi Wang, P.C. Kendall, Kevin Gumma, Alison Turner, Svetan Ratchev

发表年份
2022
引用次数
4

摘要

With increasing demand for productivity, flexibility, and sustainability, there is the need for a flexible manufacturing system that is auto-reconfigurable for variations in product types and assembly processes. However, the repeatability of reconfigurable components needs to be controlled and quantified in order to achieve the critical product tolerances required. High levels of repeatability for reconfigurable components are often achieved by a lengthy calibration. Besides, automated processes would rely on the precise tool and part positioning or an adaptive process approach. In this paper, an adaptive, highly repeatable and rapid auto-reconfiguration process in a smart manufacturing environment is proposed for small box product assembly, such as rudders, elevators and winglets. The process involves a reconfigurable tooling system for physically supporting different products, robots and end effectors to perform automated processes, programmable logic controllers to orchestrate cell safety and robotic tasks, an autonomous guided vehicle (AGV) to provide jig mobility, and a metrology system to realise cell-level positional layout. The rapid reconfigurable tooling system was tested and quantified for repeatability and configuration time, and the adaptive auto-reconfiguration process was validated by moving the jig frame in a lab environment simulating inaccurate AGV parking. The repeatability of profile board positioning can achieve a value smaller than +/-0.04mm, with an estimated between-product changeover time less than 10 minutes. With an external metrology system, the positional layout of the cell was captured and used to adapt robot programs. Successful engagement was observed, proving the feasibility of the adaptive process.

关键词

Control reconfigurationProcess (computing)Computer scienceFlexibility (engineering)RobotEmbedded systemEngineeringSimulationArtificial intelligence

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