Data-driven optimization of performance parameters of artificial leather: Performance improvement strategies combined with multiple statistical analysis
Abstract
Abstract This study aims to analyze and optimize the process parameters in the production process of artificial leather to improve product performance. First, data preprocessing is carried out to explore the influence of process parameters and performance through typical correlation analysis, and principal component analysis. The influence of single process parameters and multi-parameter interactions on performance is examined, and the key combinations of process parameters affecting different performance characteristics are identified.
Fields of Study & Subjects
Optimal Experimental Design Methods
Textile materials and evaluations
Machine Learning in Materials Science
Publication details
- Journal / source
- Journal of Physics Conference Series
- Volume
- 3175
- Issue
- 1
- Pages
- 012195–012195
- Publication date
- 1 February 2026
- Language
- EN