Research And Implementation Of Production Control System Towards Intelligent Manufacturing

Intelligent Manufacturing is an opportunity for the revitalization of manufacturing industry in the world and the transformation and upgrade of manufacturing industry in China.With the development of advanced information technology and manufacturing technology as well as artificial intelligence,intelligent manufacturing has set off a research boom around the world.Although intelligence manufacturing is a systematic concept whose connotation is gradually progressing,the basic target of its development is to raise production efficiency,product quality and effectiveness,cut energy consumption and cost of production,dispose rationally the physical resources,and improve the core competitiveness.As a key link in the manufacturing process of the enterprise,assembly production has a great impact on production efficiency and product quality.How to use the intelligent features such as self-decision and selfadaptation to optimize the mixed-flow assembly line balance and logistics scheduling in the assembly shop is an issue worthy of in-depth study,which plays an important role in enterprise gain reduction and rapid response to market demand changes.Therefore,this paper provides theoretical and practical research for production control system of Intelligent Manufacturing in assembly shop.Firstly,on the basis of the existing theory of intelligent manufacturing,the characteristics of the production control system oriented to intelligent manufacturing was analyzed and the self-decision and self-adaptive model architecture of the shop floor was given.After this,the overall implementation framework of production control system oriented to intelligent manufacturing in assembly workshop was designed.And the current situation analysis of an assembly flow shop was carried out.Secondly,the second type of balance problem of mixed-flow assembly line considering the stochastic fluctuation of working time of uncertainty demand was described mathematically.Additional constraints are added to make the model more realistic.At the same time,a discrete adaptive particle swarm optimization algorithm was designed to solve the problem.The model and algorithm are applied to the balancing problem of the mixed flow assembly line while the standard producing time is measured in the assembly workshop.The optimal allocation scheme of the workstation operation under different demand ratios were derived.Then,the collaborative mode of assembly line balancing and logistics scheduling was designed and the evaluation index of logistics scheduling efficiency was given.This is based on the optimization of assembly line balancing and with the help of dynamic scheduling strategy of production workshop.The collaborative model is verified by an example in the assembly shop.The results show that the assembly shop could carry out adaptive collaborative optimization of assembly line balance and logistics scheduling with different disturbances.At the last,the production control prototype system for the Intelligent Manufacturing of the assembly shop was designed and developed through the Visual Studio platform.The system included functional modules such as order management,material management,assembly line balancing,and logistics scheduling.Applied the control prototype system to the actual case of the mixed flow assembly line balance and logistics dispatching in an assembly workshop,which verifies the availability of the production control system.