Cyber-physical assembly system-based optimization for robotic assembly sequence planning. (January 2021)

• Record Type: Journal Article
• Authors: Ying, Kuo-Ching; Pourhejazy, Pourya; Cheng, Chen-Yang; Wang, Chi-Hsin
• Is Part Of: Journal of manufacturing systems. Volume 58(2021)Part A
• Page Start: 452
• Page End: 466
• Publication Date: 2021-01
• Subjects: Cyber-physical assembly system -- Robotic assembly -- Assembly sequence planning -- Interactions -- Metaheuristic; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2021.01.004
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: A Cyber-Physical Assembly System (CPAS)-based metaheuristic is proposed for fully-automated assembly sequence planning. CPAS considers the assembly direction and stability for a single robotic arm to perform assembly operation. Dual-projection approach reduces the collisions when compared to the existing single-projection methods in the literature. Abstract: Robotic assembly plays a principal role in intelligent manufacturing and Industry 4.0. Well-informed coordination between the robotic arms and the control modules is of paramount importance in the design and planning of automated systems. Given the time-extensive nature of assembly sequence planning and the need for labor-intensive coding and coordination, knowledge-based automated systems are much-needed tools to help facilitate the development of intelligent manufacturing systems. This research puts forward a Cyber-Physical Assembly System (CPAS)-based metaheuristic for fully-automated assembly sequence planning taking into account the physical characteristics of robotic arms. Illustrative case examples are provided to evaluate the practicability of the proposed approach. It is shown that the proposed approach generates better assembly sequences compared to the traditional methods and that the single-arms robots can execute the resulting assembly plans effectively. The numerical analysis confirmed that the CPAS is more efficient than the existing interactive method most commonly applied for assembly sequence planning. Overall, the proposed framework sets the stage for more effective and fully automated planner-robot interaction in the assembly sequence planning context.