Process control based on pattern recognition for routing carbon fiber reinforced polymer

Carbon fiber reinforced polymer (CFRP) is an important composite material.

It has many applications in aerospace and automotive fields.

The little information available about the machining process of this material, specifically when routing process is considered, makes the process control quite difficult.

In this paper, we propose a new process control technique and we apply it to the routing process for that important material.

The measured machining conditions are used to evaluate the quality and the geometric profile of the machined part.

The machining conditions, whether controllable or uncontrollable are used to control part accuracy and its quality.

We present a pattern-based machine learning approach in order to detect the characteristic patterns, and use them to control the quality of a machined part at specific range.

The approach is called logical analysis of data (LAD). LAD finds the characteristic

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