Study On Dynamic Scheduling Of Flexible Job-shop Under Ubiquitous Environment

With the diversification of customer demands and the shortening of the manufacturing leading time,the complexity of the manufacturing system is escalating.The complexity of the manufacturing system is embodied in a number of dynamic uncertainties affecting factors of small batch scheduling mode and the manufacturing implementation.As the core of manufacturing,the traditional job-shop scheduling has been unable to meet the current actual needs.At the same time,with the continuous development of science and technology,a ubiquitous environment which combines informatization and industrialization has become a new round of industrial revolution hot spots.To support the operation of manufacturing systems effectively,it is necessary to set up a scheduling strategy which can prevent as well as respond quickly to uncertain factors in actual demand of production scheduling.In the view of this,this thesis takes the ubiquitous environment as the research background and flexible job-shop as the object of study,combined with the traditional dynamic scheduling strategy at the same time.The reseach is as follows:Firstly,the information elements of the ubiquitous environment are analyzed.Based on the core technology of ubiquitous environment,this thesis analyzs the scheduling and control mode of flexible job-shop from the perspective of information acquisition mode.Through the definition of resource object class information,monitoring class information and decision class information,the information framework system of ubiquitous flexible job-shop scheduling is established,which builds the basis for the scheduling strategy.Secondly,the research on the scheduling scheme in the ubiquitous environment is carried out.In the initial scheduling decision,a scheduling strategy is designed based on reserved maintenance time and reserved production capacity under the premise that the ubiquitous manufacturing environment may obtain device related state information and historical scheduling data,which makes the scheduling scheme can not only ensure the existing tasks are completed in an optimized state,but also have the ability to maintain the health of the equipment and the ability to cope with unplanned changes in tasks.On the basis of above ideas,a multi-objective optimization model isestablished,and a genetic algorithm is designed to solve the problem.Based on the initial scheduling decision-making scheme,the rescheduling strategy in the ubiquitous manufacturing environment has been studied.Firstly,based on the analysis and classification of the uncertain factors in the system,the content of the system monitoring information is determined.Second,by the means of the ubiquitous technology,a hybrid driven rescheduling mechanism is designed for the layers of manufacturing execution,equipment resource and planning task.An idle match algorithm and rescheduling genetic algorithm are designed to realize real time and effective tracking and processing to uncertain factors in production process.Finally,through the experimental verification and analysis,the feasibility and validity of the strategy designed in this thesis were proved.