Assembly sequence planning based on structure cells in open design

Li, Shipei; Tang, Dunbing; Xue, Deyi; Wang, Qi; Zhu, Haihua

doi:10.1016/j.aei.2022.101685

Cited by 11 publications

(4 citation statements)

References 44 publications

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“…In Equation (1), Ci represents the contact relationship between two parts in the i direction. If Ci = 1, it indicates that part q is in contact with part p in the i direction of p. Otherwise, if Ci = 0, it signifies that there is no contact between the two parts in that direction.…”

Section: Design Of Constraint Matrixmentioning

confidence: 99%

“…It aims to determine the optimal assembly sequence, seeking to minimize the time required for the assembly process. Thoughtful ASP can effectively reduce production cycles and enhance productivity, consequently lowering costs and increasing production capacity [1]. Rational ASP contributes to optimized resource utilization, ensuring the efficient scheduling and utilization of parts and tools during the assembly process [2].…”

Section: Introductionmentioning

confidence: 99%

“…This method also seeks to reduce product construction costs and improve construction quality and efficiency. The objectives of this study are as follows: (1) The MOSGA is proposed to improve the computational efficiency of solving complex assembly problems, increase the search space, avoid falling into the local optimum, and determine the global optimum of the assembly sequence. (2) In the assembly sequence planning process, we aim to obtain multiple unique optimal assembly sequences in a single solving process.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Assembly Sequence Planning Method Based on Multiple Optimal Solutions Genetic Algorithm

Wan,

Liu,

Qiu

et al. 2024

Mathematics

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Assembly sequence planning (ASP) is an indispensable and important step in the intelligent assembly process, and aims to solve the optimal assembly sequence with the shortest assembly time as its optimization goal. This paper focuses on modular cabin construction for large cruise ships, tackling the complexities and challenges of part assembly during the process, based on real engineering problems. It introduces the multiple optimal solutions genetic algorithm (MOSGA). The MOSGA analyzes product constraints and establishes a mathematical model. Firstly, the traditional genetic algorithm (GA) is improved in the case of falling into the local optimum when facing complex problems, so that it can jump out of the local optimum under the condition of satisfying the processing constraints and achieve the global search effect. Secondly, the problem whereby the traditional search algorithm converges to the unique optimal solution is solved, and multiple unique optimal solutions that are more suitable for the actual assembly problem are solved. Thirdly, for a variety of restrictions and emergencies that may occur during the assembly process, the assembly sequence flexible planning (ASFP) method is introduced so that each assembly can be flexibly adjusted. Finally, an example is used to verify the feasibility and effectiveness of the method. This method improves the assembly efficiency and the diversity of assembly sequence selection, and can flexibly adjust the assembly sequence, which has important guiding significance for the ASP problem.

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Section: Design Of Constraint Matrixmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Assembly Sequence Planning Method Based on Multiple Optimal Solutions Genetic Algorithm

Wan,

Liu,

Qiu

et al. 2024

Mathematics

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“…The connection relationship, defined as the contact and mating form between a pair of parts, is considered the main factor in determining the assembly priorities of parts. Different from other mechanical products, the integrity of the hull structure is ensured by permanent joints-welds [31]. The connection types will directly affect the contact stability between parts [32].…”

Section: Connection Tightnessmentioning

confidence: 99%

Subassembly Partition of Hull Block Based on Two-Dimensional PSO Algorithm

Lundbäck

et al. 2023

JMSE

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Subassembly partition is an important process in hull block building as it greatly affects the efficiency and quality of the assembly work. Recently, an experience-based method has been widely applied to the subassembly partition process, which consumes much design time and manpower, thus causing more challenges toward a more highly automated and efficient stage in this process. To shorten the gap, an automated subassembly partition method is presented in this study. First, the assembly information model is defined with essential attributes and topological relations of the parts. Second, an optimization model is established with consideration of a trade-off between the intra-cluster cohesion and cluster number on the premise of satisfying certain constraints. After that, considering the fuzziness and diversity of the subassembly partition problem, a two-dimensional coding discrete particle swarm optimization (PSO) algorithm is developed. Finally, two blocks are demonstrated as instances to verify the proposed method, and the results show that the proposed method is feasible and applicable to the block with a flat structure.

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