Optimization of monocrystalline silicon photovoltaic module assembly lines based on simulation model.
This study presents a systematic approach to enhance the efficiency of monocrystalline silicon photovoltaic module assembly lines using advanced simulation modeling. The research focuses on developing a high-fidelity virtual model of the production line to replicate its physical layout, workflow seq...
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| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0325152 |
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| Summary: | This study presents a systematic approach to enhance the efficiency of monocrystalline silicon photovoltaic module assembly lines using advanced simulation modeling. The research focuses on developing a high-fidelity virtual model of the production line to replicate its physical layout, workflow sequences, and equipment interactions. Key assembly stages-including string welding, stacking, laminating, framing, and performance testing-are rigorously simulated to identify operational bottlenecks and inefficiencies. By analyzing workflow dynamics and resource utilization, targeted optimizations are proposed to streamline processes, reduce idle times, and improve throughput. Practical validation demonstrates that implementing these optimizations increases daily production output by over 6% and raises the production line balance rate by 5%, significantly lowering manufacturing costs while maintaining product quality. The methodology provides actionable insights for manufacturers to reconfigure production layouts, allocate resources effectively, and adapt to fluctuating market demands. This work bridges the gap between theoretical simulation and industrial implementation, offering a scalable framework for enhancing productivity, reducing waste, and advancing sustainable manufacturing practices in the photovoltaic sector. The findings highlight the critical role of simulation-driven strategies in addressing real-world engineering challenges and fostering cost-effective, high-efficiency production systems. |
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| ISSN: | 1932-6203 |