In a ship assembly process, a large number of compliant parts are involved. The ratio of the part thickness to the length or the width is typically 0.001–0.012. Fixture design is a critical task in the ship assembly process due to its impact on the deformation and dimensional variation of the compliant parts. In current practice, fixtures are typically uniformly distributed under the part to be assembled, which is non-optimal, and large dimensional gaps may occur during assembly. This paper proposed a methodology for the optimal design of the fixture layout in the ship assembly process by systematically integrating direct stiffness method and simulated annealing algorithm, which aims to minimize dimensional gaps along the assembly interface to further improve the quality and efficiency of seam welding. The case study shows that the proposed method significantly reduced the dimensional gaps of the compliant curved panel parts in a ship assembly process.

In the construction process of large cruise ships, there are numerous cabin components, and the number of assembly sequences will experience a “combinatorial explosion”, which will become a complex NP hard problem. This article proposes an assembly sequence planning method based on practical engineering problems in the construction process of large cruise ships. The cabin components are modularized, and an optimization algorithm is designed for multi-objective problem solving to obtain the optimal assembly sequence of cabin components. This article analyzes the impact of six constraint conditions on the assembly plan, including geometric constraints, sequence constraints, number of assembly reversals, number of tool replacements, stable connection relationships, and selection of reference components. A fitness function is designed and a mathematical model is established. On this basis, a genetic greedy combination algorithm is proposed to solve the optimal assembly sequence. Compared with traditional genetic algorithms, this improves computational efficiency and solves complex problems in a better manner. Multiple unique optimal solutions can be obtained in one solution process. The feasibility and effectiveness of this method were verified through examples.

The utilization of PMCUs (Prefabricated Modular Cabin Units) is a key strategy for enhancing the efficiency and reducing the costs of large cruise ship construction. Effective transportation planning for multiple PMCU cabins, including the paths and sequence, is vital to ensure smooth and timely installation. However, traditional A-Star algorithms for path planning face limitations when it comes to accounting for boundary obstacles, and existing routine sequence planning methods can hardly tackle multi-cabin coupled blocking effects. To address these challenges, an enhanced A-Star algorithm is introduced and designed to handle both grid-based and boundary obstacles in the path planning process for cabin transportation onboard. Additionally, a novel reverse planning strategy is further proposed that addresses the coupling effects arising from inter-cabin mutual blocking by determining the optimal collision-free installation sequence. Integrated with the enhanced A-Star algorithm, this reverse planning strategy effectively eliminates interference between cabin transportation sequences and transportation paths, significantly improving operational efficiency. A comparative analysis across various scenarios further substantiates the practicality and effectiveness of the proposed method, highlighting its potential for real-world application in large-scale cruise ship construction.