Abstract

The intarsia single-bed flat knitting machine is used in Korea for sweater production. It is equipped with a yarn carrier, single needle bed, yarn feeders with a plate panel for insertion, and design software that produces data for sweater production. There is, however, no simulation function for optimal productivity. As yarn connection paths and the initial positions of the yarn feeders vary the production time and costs, they, at their optimums, could reduce labor and material costs and production time respectively. This study thus sought to optimize yarn connection paths and the initial yarn feeders’ positions using two genetic algorithms (GA), which were subsequently applied to a sample sweater design. Compared with a previous study, results show labor cost reduced by 10%, material cost by 6.2%, and production time by 11.5%. The results also suggest an improvement in the productivity of similar single-bed flat knitting machines.

摘要

嵌花单床针织横机在韩国用于毛衣生产。它配备了导纱器、单针床、带有用于插入的板面板的喂纱器，以及为毛衣生产生成数据的设计软件。但是，没有实现最佳生产力的模拟功能。由于纱线连接路径和喂纱器的初始位置会改变生产时间和成本，因此它们在最佳状态下可以分别减少劳动力和材料成本以及生产时间。因此，本研究试图使用两种遗传算法 (GA) 来优化纱线连接路径和初始纱线喂纱器的位置，随后将其应用于样本毛衣设计。与之前的研究相比，结果显示人工成本降低了 10%，材料成本降低了 6.2%，生产时间降低了 11.5%。