Development of a model for persistent storage of process data in double-sided surface grinding with planetary kinematics

Abstract

The terms Industry 4.0, Internet of Things and Big Data have been among the central themes in the industrial environment for several years. Through the use of modern information and communication technology, industrial production will connect more strongly in the so-called fourth industrial revolution. This requires that there be data available based on the optimization that can be carried out. These data include, for double face grinding, the characteristics of the process and the tool, but also the qualities of the work piece achieved in the process. So far, a lot of different parameters are stored before, during and after the processes. However, until now there is no central possibility of storing the data linked together persistently. In order to store the process data, in this project a relational database using MySQL has been created and a program to process the machine files and inserting data into the DB using Python language has been coded. With the help of this network, it should be possible to optimize the entire value chain. However due to time constrains it has not been possible to create a user-friendly environment and the project should be developed further by the next developer to come.