Productivity optimization for intarsia single-bed flat knitting machine using genetic algorithm

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.

KEYWORDS:

• Intarsia
• production costs
• genetic algorithm
• crossover
• mutation

Disclosure statement

No potential conflict of interest was reported by the authors.

Geolocation information

IP Address: 220.149.124.48; Seoul, Republic of Korea; ISP: Seoul National University of technology; Latitude: 37.5683; Longitude: 126.9778

Additional information

Funding

No funding was received for the composition of this work.