Conversion of a Gaussian-distributed circular beam to a flat-top-distributed square beam in laser shock processing based on a micro-lens array structure

Han, Junfeng; Zhang, Jun; Shan, Xiaonan; Zhang, Yawei; Peng, Hangyu; Qin, Li; Tan, Yan-Nan; Wang, Lijun

doi:10.1016/j.ijleo.2023.170525

Cited by 5 publications

(1 citation statement)

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“…Micro-lens arrays, due to their unique structure at the microscopic level and superior optical performance, have become key components in the modern optoelectronic domain, being widely applied in advanced technological fields like display technology [1], optical imaging [2], and laser processing [3]. The fabrication of such microscopic components, given their high precision requirements, makes the selection and optimization of the production process a pivotal factor limiting their large-scale application.…”

Section: Introductionmentioning

confidence: 99%

Design of a digital twin system for micro-lens array embossing manufacturing

Yang,

Ma,

Zhang

et al. 2024

J. Phys.: Conf. Ser.

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Micro-lens arrays, due to their unique structure and outstanding optical performance, have been widely applied in advanced domains such as display technology, optical imaging, and laser processing. Among the manufacturing techniques, embossing molding is considered an efficient and precise method for fabricating micro-lens arrays. However, given the intricate structural characteristics of these arrays, precise control over the process becomes paramount. This study introduces a digital twin system for micro-lens array embossing manufacturing, grounded on a process knowledge base. The system relies on the rich process knowledge within the backend database combined with real-time sensor data, providing a powerful drive for the digital twin, thereby ensuring the precision and stability of the embossing manufacturing process. Additionally, the digital twin technology not only offers real-time monitoring and feedback for the production process of the micro-lens arrays but also aids researchers in optimizing process parameters, further enhancing product quality and consistency.

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Section: Introductionmentioning

confidence: 99%