Study On Multidisciplinary Design Optimization Under Cloud Manufacturing Circumstances And Its Application In Numerical Milling Machine System Design

Nowadays, with the highly development of information technology, manufacturing industry is becoming more and more information-intensive. As such, a service-oriented networked manufacturing model, cloud manufacturing, was proposed.Over the past two decades of the appearance of multi-disciplinary design optimization, a plenty of optimal methods have been raised to solve different multi-disciplinary problems. Thanks to the spread of multi-disciplinary optimization methods and the software Isight, the designing of a system nowadays is unnecessary to separate the whole system into several pieces artificially, and the collaborative effect of the subsystems can be consulted very carefully. If mature search strategies are used simultaneously, a much better global optimal solution could be found more easily.Combining multi-disciplinary design optimization and cloud manufacturing platform as well as offering “optimization as a service” to a larger scale of customers, not only enriches the applications of cloud manufacturing, but also provides a new way to use multi-disciplinary design optimization. The thesis firstly conducts a detail study of cloud manufacturing and multi-disciplinary design optimization, and comes to a conclusion of service resource virtualization model. And a cloud resource pool is built. A specific case is analyzed and optimized using traditional multi-disciplinary optimization methods. And then two models for combining the multi-disciplinary optimization and the cloud manufacturing platform are proposed and compared, at last the thesis use open resource software tools and plug-in units to develop a prototype service platform, which is used for the system design of a milling machine.The study mainly contains the following four points:(1) The software service resources are described with the virtualization description model and method, and put into the cloud manufacturing resource pool.(2) The system design scheme for the CNC milling machine C000017 B is analyzed using the multi-disciplinary design optimization framework, the machine model is built up in Pro/E and its modal is analyzed using Ansys. Finally the system design optimization model of C000017 B is gotten.(3) Two feasible ways are put forward for combining the cloud manufacturing service platform and multi-disciplinary optimization, one of which is chosen to build up the cloud manufacturing optimization service prototype system. It is combined with Isight, and further with multi-disciplinary optimization search strategies to set up the Isight task, which is solved in the cloud environment. The whole process is completed on this prototype platform for the C000017 B machine, including task-submission, result-view, and coupled information between services.(4) The functions of the prototype system are extended, and the existing resources are used to build up a prototype of C000017 B.