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This paper is the first in a two-part work, where the investigation into the characteristics of multiple machine processes is made in order to accurately control them via the frequently used machine centre platform. The two machining processes under investigation are grinding and hole making: for grinding anomalies, grinding burn and chatter and for hole making, drilling, increased tool wear and onset of drill tool malfunction, which is also significant to severe scoring and material dragging. Most researchers usually report on one machining process as opposed to multiple which is less consistent with automated flexible systems where more than one machining process must be catered for. For efficient monitoring of automated multiple manufacturing processes, any unwanted anomalies should be identified and dealt with in a prompt and seamless manner. This first part provides two experimental set-ups (same set-up with tool interchange) to obtain signal signatures for both grinding and drilling phenomena (using the same material). Here, an approach based on neural networks and CARTs is used to reliably detect anomalies for both processes using a single acquisition path, opening the door for control implementation. [ABSTRACT FROM AUTHOR]

Part 2 of this work looks at the simulation for the accurate control of multiple machine processes made on a machining centre. Specifically the models are based on controlling against two grinding anomalies; grinding burn and chatter, and for hole making; drilling tool wear and the onset of drill tool malfunction, which is also significant to severe scoring and material dragging. The work developed here takes the ideas of part 1 further where intelligent control based on the identification of force and accelerations in z axis time-frequency domain is applied. This work is significant to automated manufacturing, where observed anomalies significant to surfaces quality cannot be accepted and play an integral part to flexible automated manufacturing systems. The simulation models displayed in this part can easily be realised into prototype embedment promoting real-time control against unwanted surface anomalies for multiple machine processes. [ABSTRACT FROM AUTHOR]