Font Size: a A A

A Study On Task Allocation And Material Distribution Optimization Of Production Line In Company L

Posted on:2024-02-21Degree:MasterType:Thesis
Country:ChinaCandidate:J M LiuFull Text:PDF
GTID:2569307052475504Subject:Engineering Management
Abstract/Summary:PDF Full Text Request
The development of medical device enterprises and the continuous inflow of capital have accelerated with the increasing health awareness of domestic residents and the increase in medical demand due to the aging population.At the same time,the competitive pressure of medical device enterprises is gradually increasing in the face of the increasing customer requirements for product price,quality and delivery time,so it is extremely urgent to study the application of supply chain optimization design within medical device enterprises.This paper selects the ultrasound production department of Company L as the focus of the study,aiming to improve the production efficiency,shorten the delivery time,reduce the manufacturing cost of products,and finally enhance the overall competitiveness of the company’s products through the optimization of the production process and the design of material distribution.Firstly,the background and significance of this study are explained,and the current status of domestic and international research is briefly reviewed.After introducing the current situation of the company,many problems of the company were analyzed using tools such as value stream analysis,process capability balance analysis,process procedure analysis,and human-machine operation analysis,including: downtime and waiting during product production,waste caused by improper material distribution and operation.Then,in response to the problems of L Medical Device Company,this paper improved the task allocation rate of the company’s production line and optimized the material allocation path.Firstly,a series of improvement activities were carried out in terms of 5S management,standardized operation and ECRS of the production process to achieve the milestones of quality improvement,cost reduction,production cycle improvement and manufacturing process optimization;based on the preliminary improvement results,a dual-objective mathematical planning model was established and an algorithm of the mathematical planning model was designed to reallocate the process steps and give the production line task allocation The scheme is given.Based on the preliminary improvement results,a dual-objective mathematical planning model was established and an algorithm of the mathematical planning model was designed to reallocate the process steps and give a solution for the task allocation of the production line,thus improving the task allocation rate of the production line,and thus balancing the workstation load,improving the productivity and reducing the waiting waste.Subsequently,on the basis of the improved task allocation solution,the actual material demand of each workstation is analyzed,and a material allocation decision model is established to obtain the optimal material transportation batch for each workstation,and then the allocation interval for each workstation is obtained to solve the over-allocation problem and achieve the goal of zero inventory at the line side.Finally,with the dual objectives of shortest transportation distance and least start-up trolley,a material distribution optimization model was established,and based on the actual space layout of the workshop,a network path diagram was built with reference to the "Chinese messenger problem",and the moment of maximum demand was selected as an example to derive the best material distribution solution for that moment.The effectiveness of the optimization is verified through the evaluation of the implementation phase.The effectiveness of the optimization was verified through the evaluation of the implementation phase.Suggestions for subsequent improvements were summarized and shortcomings were presented.
Keywords/Search Tags:Production Line Task Allocation, Optimal Distribution Lot, Material Distribution Decisions, Hybrid Genetic Algorithm
PDF Full Text Request
Related items