Work

Optimal planning with multiple collaborative processing analysis in atmospheric pressure plasma processing for imprinting continuous phase plates

Year: 2025
Type: article
Abstract: Large-aperture continuous phase plate (CPP) plays a crucial role in high-power laser systems, spawning a substantial demand for high-volume manufacturing. Given the intricate surface topographies of CPPs, the utilization of multiple tool influence functions (TIFs) during fabrication has been widely recognized as an efficacious means to strike a more favorable balance between machining efficiency and precision. However, it should be noted that even with the same set of multiple TIFs, the collaborative performance can exhibit variations across different designed CPP surfaces, thereby introducing ambiguity into the determination of the optimal processing strategy. In this manuscript, we introduce an optimized planning paradigm underpinned by multiple collaborative processing (MCP) analysis, which is specifically applied to the atmospheric pressure plasma processing (APPP) technique for CPP imprinting. Initially, the fundamental characteristics of APPP are expounded, succeeded by the elucidation of the MCP analysis concept and its corresponding simulation demonstrations. Subsequently, the factors influencing the collaborative performance are dissected through the transformation of the multi-objective optimization problem (MOP), trailed by meticulous simulations. Moreover, an advanced optimal planning methodology is devised to identify the optimal processing scheme from the existing TIF library for any arbitrarily designed CPP surface. Eventually, a comprehensive suite of simulations and experiments is carried out to validate the proposed optimal planning approach. The experimental outcomes affirm that the proposed method not only enables the identification of an optimal processing scheme in a feasible and effective manner but also substantially curtails the computational overhead, thereby augmenting the overall efficiency of CPP fabrication via APPP.
Authors: Peng Ji, Duo Li, Xing Su, Yuan Jin, Bo Wang
Language: English
Open Access status: gold
Estimated APC paid: $2,270
OpenAlex ID: W4407315887
FWCI: 1.783
Cites: 28
Cited by: 4
Related to: 10