In this paper we present how statistical experimental design, time series analysis and non-linear dynamic models have been applied to gain a deeper insight into BTA-deep-hole drilling process. BTA-deep-hole drilling process is used to produce long holes of a length to diameter ratio larger than 5. This process normally produces holes of high quality with regard to straightness, smoothness of the boring walls and roundness. However, two dynamic disturbances, chatter and spiralling, are sometimes observed in the process. While chatter mainly results in increased wear of the cutting edges of the tool but may also damage boring walls, spilling damages the workpiece severely. In our study we applied experimental design to gain insight into the connection between process parameters and quality measures like roughness and roundness, while at the same time creating a database for dynamic modelling of the processes. This turned out ot be a very helpful approach because we observed all kinds of dynamic disturbances. In this paper we will focus on chatter which turned out to be dominated by a few (eigen-) frequencies. Two models were proposed to describe the variation of the amplitudes of these frequencies, on the one hand a stochastic differential equation and on the other hand a descriptive model based on piecewise periodogramms. In the latter model the knowledge of the underlying experimental design was used to distinguish between the effects of the assembly of the machine, like damping by the starting bush on the tool, and effects of the dynamics and stochastic influences. Because this model is completely data-driven it can be used as a starting point for the development of a suitable dynamic model of a process.
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