Assembly sequence planning based on structure cells in open design. (August 2022)

• Record Type: Journal Article
• Authors: Li, Shipei; Tang, Dunbing; Xue, Deyi; Wang, Qi; Zhu, Haihua
• Is Part Of: Advanced engineering informatics. Volume 53(2022)
• Publication Date: 2022-08
• Subjects: Assembly sequence planning -- Open design -- Assembly feature -- Match rule -- Particle swarm optimization; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2022.101685
• Languages: English
• ISSNs: 1474-0346

Abstract

Highlights: The assembly features of the structure cells (SCs) and their match rule are described to utilize the external resources in open design (OD). An approach for calculating the match intensity between SCs is proposed for identifying the assembly relationships among SCs. The base part and the disassembly sequence of the design scheme are derived to obtain the feasible assembly sequence. A method for generating the optimal assembly sequence is presented. Abstract: Advances in computer network technologies have enabled firms to increasingly utilize external resources to remain competitive. Based on the function-behavior-structure cell (FBSC) modeling and computer network technologies, consumers with design knowledge and experience, called co-designers in this research, can involve in the process of open design (OD) to share their requirements, experiences and knowledge. The structure cells (SCs) provided by the co-designers in OD and the relationships among them are critical for generating the optimal design scheme and assembly sequence planning. However, the existing assembly sequence planning (ASP) approaches mainly focus on identification of the assembly plan based on precedence relations of operations from the predefined parts in the design scheme without considering the utilization of resources available in OD. In this study, a new approach for ASP based on SCs in OD is proposed to tackle this problem. First, the assembly features of the SCs and their matching rules are described in OD, and an approach for calculating the matching intensity between SCs is developed for identifying the assembly relationships between SCs. The design scheme is generated according to the SCs and their assembly relationships. Second, the base part of the design scheme is determined by its correlation degree with other parts. The feasible assembly sequences are derived by reversing the disassembly sequences. As the increase of the number of parts in design scheme will result in the combinatorial explosion of feasible assembly sequences, a particle swarm optimization algorithm is presented to achieve the optimal assembly sequence. A case study is provided to demonstrate the feasibility and effectiveness of the proposed approach.