研究目的
To determine the optimal combination of laser cutting control factors for Nimonic 263 alloy sheets with respect to multiple characteristics of the cut area.
研究成果
The PSO-based approach was successful in optimizing a complex process with multiple process parameters and multiple correlated responses, showing its appropriateness for use in industrial practice. The optimized laser cutting parameters significantly improved the quality of the Nimonic 263 cut area and the microstructure. The proposed approach successfully deals with a large number of responses, addressing their correlations and multiple conflicting objectives without any trade-offs, and performing a global optimization in a continual space.
研究不足
The study focused on process quality improvement in terms of the technological characteristics of the cut material. Future work could include techno-economic optimization, involving responses that address productivity and economic aspects such as the material removal rate.
1：Experimental Design and Method Selection:
The study used an advanced multiresponse optimization methodology to design laser cutting parameters. Statistical methods and artificial neural networks (ANNs) were employed to develop the process measure and determine the functional relationship between cutting parameters and the process measure. Particle swarm optimization (PSO) was then used to find the optimal values of laser cutting parameters.
2：Sample Selection and Data Sources:
Nimonic 263 alloy sheets, 2 mm in thickness, were used. The experiment was based on the L9 matrix, with nine trials repeated to collect enough data for accurate process modeling.
3：List of Experimental Equipment and Materials:
A Bystronic laser, BYSTAR 3015 CNC Laser cutting machine was used for cutting. The material's chemical composition and laser specifications were provided.
4：Experimental Procedures and Operational Workflow:
The process parameters considered were the laser power, the pressure of the assisting gas (nitrogen), the focus position, and the cutting speed. The resulting structural changes were investigated by light microscopy, scanning electron microscopy, and energy-dispersive spectroscopy (EDS). A noncontact optical profiler was utilized for the determination of the surface characteristics and topography.
5：Data Analysis Methods:
Analysis of variance (ANOVA) was conducted to determine the statistical significance of the cutting parameters. Taguchi’s quality loss (QL) function, principal component analysis (PCA), and gray relational analysis (GRA) were used for data processing and optimization.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
