针织智能车间自动换筒任务调度技术

doi:10.13475/j.fzxb.20220801001

纺织学报 ›› 2023, Vol. 44 ›› Issue (12): 189-196.doi: 10.13475/j.fzxb.20220801001

针织智能车间自动换筒任务调度技术

孙磊¹^,², 屠佳佳¹^,², 毛慧敏¹^,², 王俊茹¹^,², 史伟民¹^,²()

1.浙江理工大学机械与自动控制学院, 浙江杭州 310018
2.浙江理工大学浙江省现代纺织装备技术重点实验室, 浙江杭州 310018

收稿日期:2022-12-28 修回日期:2023-03-12 出版日期:2023-12-15 发布日期:2024-01-22
通讯作者: 史伟民(1965—),男,教授,博士。主要研究方向为纺织机械自动化控制。E-mail:swm@zstu.edu.cn。
作者简介:孙磊(1996—),男,博士生。主要研究方向为智能纺织装备技术。
基金资助:
国家重点研发计划项目(2017YFB1304000)

Task scheduling technology for automatic bobbin replacement in intelligent knitting workshop

SUN Lei¹^,², TU Jiajia¹^,², MAO Huimin¹^,², WANG Junru¹^,², SHI Weimin¹^,²()

1. College of Mechanical and Automatic Control, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China
2. Key Laboratory of Modern Textile Machinery & Technology of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China

Received:2022-12-28 Revised:2023-03-12 Published:2023-12-15 Online:2024-01-22

摘要/Abstract

摘要：

在圆型纬编针织智能车间中,为实现针织换筒机器人自动换筒的合理调度,保证纱筒更换效率,提出一种考虑纱筒余纱量的针织换筒机器人换筒任务调度方法。基于纱筒余纱量、换筒任务响应时间、换筒任务总路径和圆机生产连续性等约束结合纱筒更换时序要求和换筒机器人运行速度,建立了以改进遗传算法为核心的针织换筒机器人自动换筒任务调度模型。基于换筒工序改进启发规则,对针织自动换筒任务进行选择排序,优化算法在排序生产和换筒路径规划中的合理性,提升换筒效率。实验测试表明,基于纱筒余纱量约束改进的遗传算法换筒效率优于单纯按空纱筒时间依次排序的算法,效率提升40%左右,且算法前期的收敛速度优于传统遗传算法,提升50%左右,对促进针织生产全流程自动化、换筒工序智能化发展具有实际的参考价值。

关键词: 针织圆机, 纱筒余纱量, 任务调度, 针织换筒机器人, 遗传算法, 针织智能车间

Abstract:

Objective Aiming at the automatic production of the whole process of the circular knitting machine in an intelligent workshop, this research concentrates on the reasonable scheduling of the automatic bobbin replacement of the knitting robot with acceptable efficiency.
Method In the knitting production shops, the effectiveness of bobbin replacement plays a critical role in ensuring uninterrupted production on circular knitting machines. In order to satisfy production demands for bobbin replacement, a comprehensive consideration of various factors is required, such as the amount of yarn remaining in the bobbin, the response time of the bobbin replacement task, and the path followed by the robot during bobbin replacement. This paper presents a multi-objective optimization model for the bobbin replacement task in intelligent knitting workshops and prioritizes the bobbin replacement tasks based on optimizing the heuristic rules for the replacement process. An improved genetic algorithm that takes into account the amount of remaining yarn is introduced for minimizing the overall path length of the bobbin replacement process and decreasing emergency coefficients for bobbin replacement. Emphasis is placed on replacing yarn bobbin with high emergency coefficients to optimize the production sequencing and bobbin replacement path planning, leading to improved bobbin replacement efficiency.
Results To further verify the effectiveness of the algorithm proposed in this paper, comparative experiments were conducted with ant colony algorithm, genetic algorithm, and the improved algorithm presented in this paper. The results showed that compared with the other two algorithms, the proposed algorithm exhibited outstanding performance in both algorithm convergence and solution stability. Compared to the traditional genetic algorithm, the proposed algorithm demonstrated a 50% improvement in early convergence speed and a theoretical 40% increase in efficiency for bobbin replacement. An effective solution is proposed for the bobbin replacement task in the knitting intelligent workshop.
Conclusion This paper proposes an improved genetic algorithm that takes into account the remaining yarn amount. By optimizing the sequence of bobbin replacement from both the total path of the replacement task and the urgency level of the replacement, it has been demonstrated that the constraint of remaining yarn amount can improve the quality of the initial solution of the algorithm. This algorithm can both eliminate inferior solutions with high urgency coefficients of remaining yarn amount and enhance the convergence speed. As a result, the efficiency of bobbin replacement has been improved by 40%, making it a viable solution for scheduling massive bobbin replacement tasks in the intelligent knitting workshop.

Key words: circular knitting machine, remaining yarn amount of bobbin, task scheduling, knitting bobbin changing robot, genetic algorithm, intelligent knitting workshop

中图分类号:

TS181.8

孙磊, 屠佳佳, 毛慧敏, 王俊茹, 史伟民. 针织智能车间自动换筒任务调度技术[J]. 纺织学报, 2023, 44(12): 189-196.

SUN Lei, TU Jiajia, MAO Huimin, WANG Junru, SHI Weimin. Task scheduling technology for automatic bobbin replacement in intelligent knitting workshop[J]. Journal of Textile Research, 2023, 44(12): 189-196.

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换筒任务编号	X轴坐标	Y轴坐标	Z轴坐标	余纱量/%
0	13	5	4	84
1	2	3	4	69
2	4	3	3	33
3	11	2	4	45
4	10	5	1	86
5	1	2	4	39
…	…	…	…	…
64	7	3	3	30
65	8	5	8	20
66	10	1	7	22
67	12	5	1	27
68	13	2	3	94
69	7	4	4	21

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针织智能车间自动换筒任务调度技术

Task scheduling technology for automatic bobbin replacement in intelligent knitting workshop

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参考文献 14

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换筒任务编号	X轴坐标	Y轴坐标	Z轴坐标	余纱量/%
0	13	5	4	84
1	2	3	4	69
2	4	3	3	33
3	11	2	4	45
4	10	5	1	86
5	1	2	4	39
…	…	…	…	…
64	7	3	3	30
65	8	5	8	20
66	10	1	7	22
67	12	5	1	27
68	13	2	3	94
69	7	4	4	21

换筒任务编号	X轴坐标	Y轴坐标	Z轴坐标	余纱量/%
0	13	5	4	84
1	2	3	4	69
2	4	3	3	33
3	11	2	4	45
4	10	5	1	86
5	1	2	4	39
…	…	…	…	…
64	7	3	3	30
65	8	5	8	20
66	10	1	7	22
67	12	5	1	27
68	13	2	3	94
69	7	4	4	21

换筒任务编号	X轴坐标	Y轴坐标	Z轴坐标	余纱量/%
0	13	5	4	84
1	2	3	4	69
2	4	3	3	33
3	11	2	4	45
4	10	5	1	86
5	1	2	4	39
…	…	…	…	…
64	7	3	3	30
65	8	5	8	20
66	10	1	7	22
67	12	5	1	27
68	13	2	3	94
69	7	4	4	21