Development of intelligent machining knowledge database for manufacturing cloud system of machine tool

For the mechanical equipment manufacturers, the processing providers are very important third party partners. However, the traditional method to develop the processing providers, such as telephone interviews or browsing the official websites, both are unable to provide the vendors processing for the information immediately and efficiently. In order to solve this problem, a platform is required which can rapidly obtain information processing suppliers and has a proper recommendation mechanism to the customers. This study will build and integrate knowledge base cloud for machine system and machine tool analysis algorithms, three key technologies 'machine filter module', 'component cost analysis function' and 'machine recommendation algorithm' that would deliver an effective choice can meet the needs of the processing machine tool vendor solutions. Create a 'Machine tools analysis algorithms,' the best metal cutting program and get the best processing time, the element of cutting optimization program and knowledge processing capacity of the cloud vendors to compare analysis by processing components of key indicators such as: surface roughness, precision, cutting time, cutter location (CL) information, tools, materials and manufacturing costs, and then choose the tools that meet best the needs of machining's manufactures.