OPTICS & OPTOELECTRONIC TECHNOLOGY, Volume. 22, Issue 4, 111(2024)

Optical Pattern Design and Machining Parameter Optimization Based on Sensitivity Analysis

YING Zheng-jian1, XIE Zheng-chao1, and LI Jing2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    To meet both the requirements of optical pattern engineering and regulatory,and to quickly find the optimal pattern design and processing parameters,thereby resolving the need for extensive simulations and experiments to achieve multi-objective optimization from design to manufacturing,a comprehensive parameter optimization method based on sensitivity analysis is proposed in this paper. The results indicate that during the design phase,the optical pattern achieves optimal optical utilization performance when the surface roughness of the design parameters is maintained between 0.1 mm and 2 mm. During the manufacturing phase,using HP4A material as an example,the design is sampled using Latin hypercube sampling within the specified range of surface roughness,and the objective function is constructed based on its minimum value. The study examined the effects of cutting parameters:spindle speed(n),feed rate(Vf),and axial cutting depth(ap)on surface roughness(Ra),resulting in the identification of the optimal combination of cutting parameters.Through sensitivity analysis,it is shown that surface roughness negatively correlates with spindle speed and feed rate,and positively correlates with axial cutting depth. By using sensitivity analysis to quickly optimize the full parameters of optical patterns,the method reduces the number of design variables and improves solving efficiency by 30% compared to traditional experimental and simulation methods,which proves its effectiveness.

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    YING Zheng-jian, XIE Zheng-chao, LI Jing. Optical Pattern Design and Machining Parameter Optimization Based on Sensitivity Analysis[J]. OPTICS & OPTOELECTRONIC TECHNOLOGY, 2024, 22(4): 111

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    Paper Information

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    Received: Jan. 24, 2024

    Accepted: --

    Published Online: Aug. 23, 2024

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    DOI:

    CSTR:32186.14.

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