Research On Discrete Intelligent Manufacturing Unit Of Smart Factory

As "Big Data","Internet of things","Cloud Manufacturing","Industry 4.0" and "Made in China 2025" a series of major development strategies were proposed,Internet and Manufacturing were closely linked together,the orders scale presented varieties and small batches.In order to meet the personalized requirements of customers,the manufacturing pattern is transforming from large-scale assembly line production to customer demand oriented smart factory.Smart factory advocates clean manufacturing and green manufacturing,how to efficient and reasonable scheduling intelligent robots to complete the processing tasks is the subject of domestic and international research frontier.Smart factory normally consists of several discrete intelligent manufacturing units,through intelligent processing robots,automated machining islands,Cyber-Physical System(CPS)as well as the central processor module,achieves the intelligent manufacturing from raw material to finished products.This paper research on the discrete intelligent manufacturing unit of smart factory: Firstly,this paper described the characteristics of intelligent factory manufacturing model and discrete intelligent manufacturing unit,pointed out relations and distinctions between smart factory and the traditional production model,made a description from the shortest production cycle and the shortest path planning;Secondly,the paper established the intelligent factory discrete intelligent manufacturing unit scheduling model as the minimum tatal energy consumption of target and considered the product variety,product quantity and robot processing constraint rules factors;Then,the target can be divided into two parts: robot walking energy consumption and processed products energy cost.Three kinds of solution strategies were designed: the Simulated Annealing algorithm(SA),Particle Swarm Optimization algorithm(PSO)and nested SA-PSO algorithm;Finally,the smart chip manufacturing unit of Germany company KUKA was took as example,scheduling model according to the product type and order sizes was set up,respectively solve problems by using the above three algorithms,the influence of parameter settings through the control variable method was discussed.Compared the results,conclude optimal scheduling strategy by SA-PSO algorithm and verify the validity of the model and algorithm.According to the results of this paper,the model methods and solution strategy proposed by this paper for discrete intelligent manufacturing uint can help enterprises to make a reasonable allocation of manufacturing resources based on order size and increse productivity.Meanwhile,to meet the low carbon manufacturing philosophy widely proposed by the current international community...