Measurement and Supervision in Automated Production

Abstract

This thesis consists of two main parts.

Part I:

A general introduction to data collection and storage. Experiments are conducted to store events with timestamps in two different production cells. The information is used to increase the productivity by finding the inefficient parts of the production. The information is also used to get a greater overview of the different parts of the production to create better production equipment configurations.

Part II:

Two very different cases are studied to find out how increased knowledge of the process can improve the processes.

The first case is to monitor forces and vibration in milling. Experiments are conducted in milling of a difficult-to-cut material, and some methods are proposed on how a worn out tool can be detected.

The second case is to monitor forces in an assembly operation. Experiments are conducted to find out how the forces gathered can be used to increase the knowledge about the assembly operations, and some methods are proposed on how the information can be used to increase productivity and quality.