Application analysis of SAX and DTW methods on time series obtained from garment sewing machine operator data

The focus of this study lies in the analysis of time series data with a specific emphasis on its applications within the textile industry. Commencing with two fundamental methods, namely PAA and SAX, the process of transforming continuous time series into a symbolic representation is addressed. The SAX method enables e more effective analysis of time series through steps such as symbolic representation generation, segmentation, and statistical summarization, with advantages including pattern highlighting and noise reduction. To address issues such as time shifts and velocity variations, the DTW method is investigated, facilitating the flexible alignment of time series. This method proves particularly effective in measuring the similarity between two temporal sequences with variable velocities. Time series analysis serves as a powerful tool for understanding and enhancing industrial processes, and its applications in the textile sector offer significant advantages in terms of efficiency and quality.