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Research On Parallel Machine Production Scheduling Considering Fatigue Of Front-line Employees

Posted on:2021-02-05Degree:MasterType:Thesis
Country:ChinaCandidate:X Z LiFull Text:PDF
GTID:2439330602970251Subject:Industrial engineering
Abstract/Summary:PDF Full Text Request
Due to the need for mass production,the parallel machine production model has been generally promoted because it can greatly improve the production efficiency of enterprises.In recent years,with the vigorous promotion of intelligent manufacturing in China,various enterprises have also increased their efforts in the introduction of intelligent equipment.Facing the demand of enterprises for the improvement of mass production efficiency in reality,how to effectively schedule the production of parallel machines with intelligent equipment to better serve the production has become the focus of many scholars.For a long time,the research on parallel machine production scheduling mainly focuses on machine disturbance,algorithm optimization,model optimization and so on.However,the human factors of machine operators have rarely been discussed,especially employees are extremely fatigued to production resources and production needs which affects the production efficiency of enterprises.It is an urgent problem that stabilizing the production efficiency and reducing the employees fatigue by coordinating the production equipment with the personnel.Based on this,it is considered that the parallel machine production scheduling problem with the participation of front-line employees.The impact of front-line employees fatigue is the center of attention.The main research contents are as follows:Firstly,the research status of production scheduling,front-line employees fatigue,and evaluation indicators of production scheduling is explained.The necessity of front-line employees to participate in parallel machine production scheduling research is clarified.Furthermore,the production scheduling theory,front-line employees fatigue theory,production balance theory,and ant colony algorithm are introduced.A basis is provided for further exploring the impact of front-line employees fatigue on the production efficiency of enterprises.Secondly,the parallel machine production system was taken as the research object.The corresponding hypotheses were put forward by describing the problem background.On the basis of the production resources and production demand of the enterprise,combining with the previous literature on employee fatigue,a function of front-line employees' fatigue was constructed,and the influence of front-line employees' fatigue on the enterprise's production process was described by using the exponential function.A mathematical model for production scheduling of constant-speed parallel machines considering the fatigue of front-line employees wasestablished.Based on the standard ant colony algorithm,the ant colony algorithm and the improved ant colony algorithm were designed to solve the problem.Thirdly,it was described that the current situation of parallel machine production scheduling with front-line employees in F Company from the company profile,site layout and parameters.The relevant parameters in the proposed production scheduling model were set.It was applied in this company.Different parameters were used to simulate different production situations.The influence of front-line employees fatigue on the production efficiency of the company was verified by analyzing different production scheduling schemes.Finally,the production scheduling problem considering the fatigue of front-line employees was explained from the output of the enterprise,the effective work rate of employees,and the efficiency of machine utilization.It is proposed that the algorithms have their own advantages,the front-line employees have a certain production intensity,and the improvement of machine utilization is the key to improve the production efficiency of the enterprises.It is hopeful to improve the production efficiency of enterprises.
Keywords/Search Tags:production scheduling, parallel machines, front-line employees, ant colony algorithm
PDF Full Text Request
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