Dynamic scheduling algorithm integrating machine vision inspection data for mechanical assembly workshops and its impact on production efficiency improvement
Jianzhao Wang
Jiuquan Polytechnic University
DOI: https://doi.org/10.59429/esta.v12i3.11360
Keywords: dynamic scheduling algorithm; machine vision inspection data; mechanical assembly workshops; production efficiency improvement; real-time status perception
Abstract
Traditional production scheduling algorithms for mechanical assembly workshops often struggle with slow responses to dynamic changes and inaccurate decision-making. To tackle this, we designed a dynamic scheduling algorithm that integrates machine vision inspection data—enabling real-time perception of on-site status (e.g., workpiece assembly deviations, equipment abnormalities) and swift adaptation to unexpected events (e.g., equipment failures, non-conforming products entering the line).This paper provides a detailed exposition of the implementation process of the algorithm and validates its effectiveness through experiments: compared with traditional methods, the production cycle is shortened by 15%, equipment utilization is improved by 10%, and product quality is significantly enhanced. The research results offer a practical and feasible path for intelligent scheduling in mechanical assembly workshops.
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