Research on assembly line balancing for large cruise ship cabin modules

In the construction of large cruise ships passenger cabins, assembly line balancing directly affects the operational efficiency and production cycle. This paper focuses on the multi-cabin modular assembly line balancing problem, emphasizing the development of an effective method to optimize production cycle times under fixed workstation constraints. By employing an improved genetic algorithm, key performance metrics such as production cycle time, balance rate, balance loss rate, and smoothness index were thoroughly analyzed, achieving an optimal balance state for the assembly line. Three case studies involving 1, 20, and 50 cabins validated the feasibility and practicality of the improved genetic algorithm in assembly line balancing for multi-cabin modules in shipyards. The results demonstrate that as the number of cabins increases, the balance state of the assembly line improves significantly, further proving the applicability and advantages of this method in complex production environments.

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Publication Details

Published
2025-07-18
DOI
https://doi.org/10.1117/12.3070465
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
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article

Research on assembly line balancing for large cruise ship cabin modules

Jianfeng Liu, Kun Liu, L. Ju, Xiaoyuan Wu et al.
Advanced Manufacturing and Logistics Optimization
article

Research on assembly line balancing for large cruise ship cabin modules

Jianfeng Liu, Kun Liu, L. Ju, Xiaoyuan Wu, Yixi Zhao
article en

Abstract

In the construction of large cruise ships passenger cabins, assembly line balancing directly affects the operational efficiency and production cycle. This paper focuses on the multi-cabin modular assembly line balancing problem, emphasizing the development of an effective method to optimize production cycle times under fixed workstation constraints. By employing an improved genetic algorithm, key performance metrics such as production cycle time, balance rate, balance loss rate, and smoothness index were thoroughly analyzed, achieving an optimal balance state for the assembly line. Three case studies involving 1, 20, and 50 cabins validated the feasibility and practicality of the improved genetic algorithm in assembly line balancing for multi-cabin modules in shipyards. The results demonstrate that as the number of cabins increases, the balance state of the assembly line improves significantly, further proving the applicability and advantages of this method in complex production environments.

Shanghai Jiao Tong University (CN), Shanghai Shipbuilding Technology Research Institute (CN), Jiangsu University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 73%
Advanced Manufacturing and Logistics Optimization
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