The Optimization Of Motion Trail Of Material Taking Machine On Flexible Automatic Production Line

At home,some manufacturing enterprises has already adopted the Automatic Storage/Retrieval System(AS/RS)into managing self-products,and adopted the information management platform with multi-systems integrated,these conditions has brought much convenient to the enterprises' management.However,one manufacturing company introduced the Flexible Automatic Production Line(FAPL)to reduce the frequency of more than two half-material competing for the same manufacturing machine.This firm also configured an AS/RS into the FAPL,with the help of stock cell which cache the material for processing,it can decrease the time cost on material moving to and fro in the workshop.But the material taking machine(or stacker)which executes the transport process in the AS/RS has a very low effeciency,so it gave rise to the low effeciency of manufacturing machines,and then these low efficient machines affected the product effeciency of the whole FAPL.Targeting at the low effeciency of the stacker in the company,this paper accorded to the actual situation of the workshop,analyzed the main cause that could bring this low effeciency problem is the stacker has not made full use of its idle-time to effectively prepare for the next motion,and not reasonably use the buffer layer's free stock cells.In order to solve the problem of the stacker's route optimization,and minimize the stacker's unnecessary idle time,this paper fully considered the conditions of the stacker's motion trail and the reasonable usage of the stock cells in the buffer layer,then established the optimization goal is to minimize the stacker's running time,found a realizing method is to optimize the target stock cell,has been clear about the optimization strategy is to compare the sum of the stacker's optional cells under the current instruction and the next instruction.By establishing the relevant models of the ant colony algorithm and the greedy algorithm,this paper improved the disadvantages of the two kinds of algorithm,then rose the convergence rate of the improved ant colony algorithm and avoided the greedy algorithm into a ?dead cycle?.At last,as the instance result data showed by,the improved algorithms for the stacker's route optimization problem are feasible and effective.