This article presents the development of software for automating the statistical processing of the linear dimensions of worn parts of tillage implements. It addresses pressing issues related to the need to analyze large volumes of data obtained during micrometric measurements of worn parts. A software solution implemented in Python using the PyQtGraph and openpyxl libraries and modules providing a graphical interface and analytical functionality is proposed. This program automates data partitioning into intervals, calculating key statistical indicators (mean values, variance, and coefficient of variation), and plotting graphs. Examples of software application based on cultivator tine wear monitoring data are provided, confirming the adequacy of calculations and the program’s ease of use.
Feskov et al. (Thu,) studied this question.