Research And Application Of Collaboration Consistency Method Of Production-Logistics Resources In Smart Workshop

With the development of industry 4.0,the traditional factory of large-scale integrated production is transforming to the intelligent factory of personalized customization,multi-variety,and collaborative service production.To cope with the rapid changes in the market,Smart Work Shop(SWS)needs to deal with the following three problems:(1)Real-time order disturbance caused by customization;(2)Various scheduling resources and fuzzy operation time;(3)High efficiency and low cost.From the perspective of production and logistics,it requires the dynamic collaboration of Production Logistics Resources(PLRs)of the intelligent factory to respond to market changes quickly and to be able to reorganize production-logistics based on dynamic service capability for real-time tasks.On the other hand,the scheduling system of the intelligent shop floor needs to adapt to the change of resource reorganization to promote the development of the manufacturing system in an orderly.Collaborative scheduling of PLRs has become the critical technical bottleneck restricting the efficient operation of the SWS.The main features are described as follows:(1)At the resource modeling stage,it is necessary to build a heterogeneous industrial resource model of the PLRs.(2)At the stage of real-time task allocation,the on-demand task allocation based on task demand and resource capability is realized.(3)At the task triggering stage,how to maximize the utilization of information to achieve the stability of the manufacturing system and the robustness of scheduling results.The main research work and innovation points of this thesis are introduced as follows:(1)A collaborative scheduling architecture of swarm PLRs based on Device to Device(D2D)is proposed.Based on the characteristics of new elements,new features,and new requirements of the SWS,the flexible and dynamic organization mode of production and logistics in SWS is studied.The formal description of the swarm system is constructed by introducing graph theory and ontology modeling technology.The multi-level coupling relationship between the swarm system and manufacturing system is analyzed,and the concept of the industrial swarm is proposed.For the real-time interaction requirements of multi-resources in intelligent operation,the PLRs collaboration mode is designed.The swarm resource collaboration architecture is constructed,which lays the foundation for the controllable evolution of swarm resources.(2)This thesis proposes an adaptive collaborative method of PLRs based on task consistency.For the demand of flexibility,a real-time coordinated strategy of production logistics is proposed according to the dynamic scheduling of production logistics.According to the characteristics of personalized order,the task slack index is constructed.For the social attributes of swarm resources in the environment of the industrial Internet of things,a swarm dual attribute model is built.The social factors of real-time tasks are constructed based on the consistency of real-time tasks.Based on the social attributes of real-time tasks,the real-time evaluation index of production logistics service composition is built to realize the adaptive collaboration of swarm resources.Experimental results show that the proposed method can ensure the orderly development of the manufacturing process in the unexpected arrival of orders.(3)According to the random arrival time of orders and the fuzzy attributes of swarm resources,a multi-disturbance factor model of a flexible job shop is constructed.The information theory is introduced to carry out multi-resource real-time scheduling to solve the coordination problem of PLRs in multi-disturbance environment.Firstly,a real-time task triggering strategy that maximizes information utilization is proposed to explore the time when using real-time information.Secondly,a collaborative method for Production-Logistics Resources is studied to analyze how to use real-time information.Thirdly,a real-time self-adaptive scheduling algorithm based on information entropy is utilized to obtain a stable and feasible solution.Finally,the effectiveness and advancement of the proposed method are verified by a practical case.(4)A real-time collaborative scheduling simulation platform is developed.In order to realize the application of the Real-time Scheduling Method of PLRs based on Swarm Consistency(RSMo PSC),we use Python 3.7 to create a swarm collaborative scheduling program and integrate it with plant simulation software to build a swarm resource real-time collaborative scheduling platform.Aiming to upgrade the manufacturing Work Shop of a robot manufacturing enterprise in Wuhan,the potential value of the proposed method to the high disturbance manufacturing environment is simulated and analyzed by taking the hub manufacturing Work Shop as an example.Experimental results show that the proposed theoretical method can effectively improve the ability of the Work Shop to deal with disturbance and improve manufacturing system efficiency.