Scholarlink

<p>AISI 1045 steel is a widely used medium-carbon steel in various industrial applications. However, this material is highly susceptible to oxidation, which deteriorates surface quality and adversely affects the durability of machine components, ultimately reducing the service life of industrial equipment systems. Therefore, surface cleaning of AISI 1045 steel parts is a critical step in the mechanical manufacturing process. Laser cleaning has emerged as a promising solution due to its high efficiency and environmental friendliness. Nevertheless, significant challenges remain in controlling the combined effects of multiple process parameters on surface quality. In this study, a combined simulation and experimental approach was employed to evaluate the influence of laser source parameters (power, pulse width, repetition rate) and process parameter (scanning speed) on the quality of the cleaned surface. The optimal set of parameters from the multivariate regression model adopts a response surface method (RSM) with a power of 50&#xa0;W, a pulse width of 250&#xa0;ns, a repetition frequency of 90 kHz, and a scanning speed of 800&#xa0;mm/s to provide high cleanliness corresponding to the lowest dark point ratio of 9%.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Laser cleaning of AISI 1045 steel: simulation and optimization with the response surface method

  • 期刊论文

  • 发表日期：

    2026年8月4日

查看全文
  • Quang Truong Nguyen,
  • Got Van Hoang,
  • Huy Vu,
  • Van Thuc Tran,
  • Van Quy Hoc Luu,
  • Tung Thanh Vu

摘要

AISI 1045 steel is a widely used medium-carbon steel in various industrial applications. However, this material is highly susceptible to oxidation, which deteriorates surface quality and adversely affects the durability of machine components, ultimately reducing the service life of industrial equipment systems. Therefore, surface cleaning of AISI 1045 steel parts is a critical step in the mechanical manufacturing process. Laser cleaning has emerged as a promising solution due to its high efficiency and environmental friendliness. Nevertheless, significant challenges remain in controlling the combined effects of multiple process parameters on surface quality. In this study, a combined simulation and experimental approach was employed to evaluate the influence of laser source parameters (power, pulse width, repetition rate) and process parameter (scanning speed) on the quality of the cleaned surface. The optimal set of parameters from the multivariate regression model adopts a response surface method (RSM) with a power of 50 W, a pulse width of 250 ns, a repetition frequency of 90 kHz, and a scanning speed of 800 mm/s to provide high cleanliness corresponding to the lowest dark point ratio of 9%.