Abstract
Approximately 45% of ship delivery delays are due to welding quality. To solve the problematic control of production tempo and process sequence optimization in the welding process, it is urgent to combine the characteristics of the digital twin for dynamic simulation and optimization. Therefore, the capacity evaluation and scheduling optimization for the ship welding production line (WPL) based on the digital twin is proposed. Firstly, to describe the construction method of the digital twin model and digital twin data, a strategy is proposed for the construction of a digital twin ship component WPL model. Based on the fusion mapping of model and data, the construction of the digital twin model for WPL (DTM-WPL) is achieved. Secondly, by using equipment failure rate, processing time and buffer capacity as evaluation indicators, an WPL optimization model based on digital twins is constructed to solve the WPL production sequencing problem. Thirdly, to illustrate the welding quality traceability and prediction process, a DTM-WPL synchronous mapping for quality prediction and adjustment method is proposed. Finally, taking small and medium-sized WPL as the research object, the capacity evaluation and scheduling optimization system of ship components is developed to evaluate the production capacity of ship components. The validation results indicate that the optimized process scheme has increased production efficiency by 7.27%.
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The data that support the findings of this study are available from the corresponding author upon request.
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Funding
This work was supported by the [National Natural Science Foundation of China] under Grant No. [52075229]; [the National Key Research and Development Program of China] under Grant No. [2020YFB1708400]; [Natural Science Foundation of Jiangsu Province] under Grant No. [BK20202007]; [The Natural Science Foundation of the Jiangsu Higher Education Institution of China] under Grant No. [20KJA460009]; Sponsored by Qing Lan Project.
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JL: definitions, methodology, writing. QJ: methodology, software. XZ: software, case study. YC: modeling method, writing. YZ: quality prediction, review and editing. XL: capacity evaluation, scheduling optimization; MT: software, case study.
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Liu, J., Ji, Q., Zhang, X. et al. Digital twin model-driven capacity evaluation and scheduling optimization for ship welding production line. J Intell Manuf (2023). https://doi.org/10.1007/s10845-023-02212-2
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DOI: https://doi.org/10.1007/s10845-023-02212-2