Research on Single Bottleneck Optimization Based on Intelligent Manufacturing Mode

More and more manufacturing companies are adopting a multi-variety, low-volume production model, and there are bottlenecks in the workshop due to the different demands on machine capacity for different products. The presence of the bottleneck in the workshop will severely limit the daily output of the workshop, reducing productivity and profits. In this paper, an improved Jaya algorithm based on problem characteristics is proposed to solve the single bottleneck optimization problem within intelligent manufacturing mode. Firstly, under the single bottleneck of intelligent manufacturing mode, the flexible factor of the manufacturing machine is considered, which effectively solves the problem of machine load distribution in the workshop. Secondly, based on the basic JAYA algorithm, a two-layer encoding mechanism and decoding mechanism based on problem characteristics are proposed, as well as the improvement of the similarity method. Finally, the effectiveness of the improved algorithm in this problem is demonstrated by comparing it with other algorithms.