| With the development of modem market economy, the supply and requirement relationship between customers and manufacturing enterprises becomes more dynamic and short. Manufacturing internet of things (MIoT) system is one of the important supporting systems for intelligent manufacturing process, which is put forward higher requirements to respond the customer dynamic requirement (CDR) of production process by the manufacturing enterprises. Production logistics (PL) is an indispensable part of the production process which occupies 95% time of the production process. PL has been focused on by the academic, government and business. Efficient production logistics synchronization (PLS) operation is the key to control the CDR of the manufacturing system. Overview the existing research of the production and PL, we can find that most researches only consider the decision and control problems of production or PL in the dynamic production environment. But actually, the CDR will meanwhile influence the production and PL. The decision of production must consider the decision of PL. At the same time, it is important to consider the impact of local resource shortage influences PL. In view of these, with the CDR influence the PL operation and adding, this thesis research PLS control method with cloud resources for CDR.Firstly, the production stage and the storage stage of PL is the research object of this thesis, discusses the problems of production and PL operation with CDR, and proposes the challenge of PLS for CDR. Secondly, to solve the local resources shortage caused by the CDR, The PL system information framework with cloud resources is established. On the basis of the above, the cloud resources is imported the PLS control process. Then, the qualitative two-level PLS with cloud resources control mechanism is proposed, and the quantitative PLS method based on optimization collaborative (CO) is presented. Thirdly, under the storage with cloud resource platform to expand the storage resources. To solve the production planning problem and storage planning problem of PLS, the system model, the production subsystem planning model and the storage subsystem planning model is established by CO, and proposes an improved genetic algorithm (GA) to solve the production subsystem planning model and a heuristic algorithm to solve the storage subsystem planning model. Fourthly, in order to verify two-level PLS control method, a case applies MATLAB R2013a software programming and simulation, and the results verify the method is feasibility and effectiveness. In addition, with the different strength CDR for different times, compared with the effective of PLS and un-PLS, and the result indicates PLS method well. Finally, on the basis of PLS information framework implements an loT-based PLS management system, through an application case, display the system function and process. The research shows that the two-level PLS control method can effectively control CDR for PL operation, such as resources shortage, multi-stage decision dis-coordinative and multi-phase decision-execution mismatch. |
PDF Full Text Request