Research Of Workflow Oriented Automotive Manufacturing Supply Chain Collaborative Control Scheduling

Processing time,production quality and cost are important indexes to measure the market competitiveness of automobile manufacturing enterprises.However,there are many factors that affect these indexes in the automotive manufacturing supply chain.If these factors can not be dynamically balanced in time,it will lead to the imbalance of these indexes,reduce the core competitiveness of enterprises,and even cause serious consequences of losing the market.Therefore,how to optimize the processing time,production quality,cost and increasing coordination control ability not only has a very important strategic significance for automobile manufacturers,but also has a high academic value,and is worth studying in depth.The traditional automobile manufacturing supply chain scheduling method is only optimized around a single index,which has problems of one-sided optimization and low efficiency.As one of the latest scheduling techniques,workflow has a strong model description and quantitative solution ability.Therefore,it can solve the dynamic optimization problem of multi indexes by applying workflow technology to the scheduling process of automobile manufacturing supply chain.This dissertation combines workflow technology with Petri net model,and improves it according to the characteristics of company X automobile manufacturing technology,and puts forward a collaborative control scheduling optimization method for workflow oriented automobile manufacturing supply chain.In the method,one part is used to solve the multiobjective optimization scheduling problem of the general workflow and the special workflow with feedback constraints in the automotive manufacturing supply chain;the other is used to solve the problem of improving the automobile manufacturing supply chain collaborative control scheduling capability,such as: execution time performance monitoring,diagnostic resource use conflict,etc.Aiming at the problem that the concurrent supply chain of automobile manufacturing is difficult to dynamically balance the processing time,production quality and cost,the dissertation firstly abstracts the sets of the supply chain's place and transition nodes,builds a workflow model by combining the partial order relation of the technology.Secondly calculats the degree of each place node's freedom in each layer based on the proposed rules of common workflow constraint recognition,and then reduces them from back to forward stratification by the series reduction algorithm,calculates the optimal configuration solution for each layer.Finally,adopts the forward scheduling algorithm to complete the multi-objective optimal scheduling of the whole workflow model.Aiming at the restriction and feedback process in some parts of the automobile manufacturing supply chain,the former workflow multi-objective optimization method has some problems such as interference and other problems.So the dissertation proposes a virtual workflow technology.The technology first establishes a feedback workflow based on the process flow.It combines the virtual technology to scan the whole workflow and finds the virtual node to reconstruct,so as to achieve the establishment of the virtual workflow model.Secondly,the model is segmented according to the actual situation,and uses the virtual series reduction algorithm to reverse stratified solution in each segmen,and uses cumulative processing strategy to link each segment.Finally,adoptes the forward scheduling algorithm to complete the multi-objective optimal scheduling of the whole virtual workflow model.Aiming at the problem that the performance of automobile supply chain coordination control is difficult to be evaluated scientifically and accurately,the dissertation proposes a Markov workflow evaluation method.The method firstly builds a Markov workflow model,and then quantifies the model with the specific production data.Secondly,the solution is solved by the steady-state probability equation proposed,gets the stable execution time of each transition state in the Markov workflow model.Finally,these times are brought into the average execution time formula,and calculates the execution time of the overall automobile manufacturing supply chain collaborative control scheduling,gives the periodic trajectories and completed the task of scientific evaluation.Aiming at the weak ability of finding manufacturing resources conflict detection in the existing automobile manufacturing supply chain collaborative control scheduling system,the dissertation proposes a discrete-continuous hybrid point conflict diagnosis method of the workflow resource input-product output.The method firstly establishes the resource input matrix,the output matrix of the finished product,the initial and the termination state matrix.Secondly,according to the actual situation of the whole supply chain workflow model,these matrices are quantified and the unknown reachable matrix of the system's place node is set up.Finally,it will validate whether there was a positive integer solution for the unknown reachable matrix of the system's place node based on the homogeneous equation proposed.If it doesn't exist,it will indicate that there is resource conflict in the system,determines the source of the conflicts and gives analysis,so as to achieve the purpose of rapidly diagnosing and improving the ability of finding resources to use conflicts.In summary,the dissertation being oriented to the dynamic balance of important indexes such as processing time,production quality,cost and collaborative control ability in automobile manufacturing supply chain,studies the modeling and multi-objective optimization scheduling method using workflow technology,realizes the rational allocation of production resources and the diagnosis of the used conflict.These methods not only provide technical support for automobile manufacturers to control time,production quality and cost,but also provide some reference for other manufacturing industry's collaborative control ability optimization.