Advanced planning and scheduling system and scheduling algorithm for intelligent warp knitting workshop
Objective The textile industry gradually shifts towards multi-variety,small-batch,and order-based production,and the traditional production management models no longer meet the demands for flexible customization management in large-scale production environments.This issue is particularly prominent in warp knitting production enterprises with complex and diverse products.To address the issues of low efficiency and incomplete consideration factors in traditional manual scheduling in the warp knitting industry,this paper reports an advanced planning and scheduling(APS)for warp knitting,aiming to effectively improving production continuity and order delivery efficiency.Method APS system based on microservices architecture for warp knitting workshops is proposed.After elaborating in detail the production planning and scheduling operation mechanism based on APS,a multi-objective warp knitting workshop scheduling model was constructed to minimize the maximum completion time and the number of raw material changes.An optimization algorithm based on Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA Ⅱ)is designed and implemented to solve the intelligent allocation problem for large-scale equipment and orders.Results It is found that APS system can effectively make up for the shortcomings of traditional enterprise resource planning(ERP)and manufacturing execution system(MES)single production planning management mode,which is separated from actual production,lack of production planning and decision support.Through the integration with MES,ERP and other systems,comprehensive data analysis and mining,the development of detailed production plans,to provide decision support for production management.According to the actual production situation,the production process is dynamically adjusted and optimized.Experimental verification shows that the optimization effect of NSGA-Ⅱ based warp knitting shop scheduling optimization method can reach more than 200％as the scale increases in terms of maximum completion time and the number of raw material changes between orders.Compared with the traditional multi-objective genetic algorithm,the scheduling results of this algorithm for small-scale problems are not much different.However,with the expansion of the problem scale,the optimization ability of the traditional multi-objective genetic algorithm decreases significantly,which may lead to longer optimization time,local optimal solution,loss of excellent properties,and even worse scheduling results than manual scheduling.Conclusion This paper proposes a warp knitting production APS system based on microservice architecture according to actual production needs.It can meet the complex business processes of warp knitting production and future business expansion,and can monitor and coordinate the management of orders and resources in the warp knitting production process in real time,better meeting the actual needs of the warp knitting workshop.In addition,this paper also uses the NSGA-Ⅱ algorithm to optimize scheduling problems,which can significantly improve production efficiency and continuity,effectively solve the problem of effective allocation of large-scale orders and equipment,and can adapt to further expansion in the future.In summary,the warp knitting production APS system reported in this paper is an efficient and intelligent production management tool with a wide range of application prospects and promotional value.
micro service architectureadvanced planning and scheduling systemwarp knitting shopworkshop scheduling optimization methodnon-dominated sorting genetic algorithmintelligent production
万方数据
维普
