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/pdf/design-of-a-custom-software-application-to-monitor-and-ulj7mkrsw4.pdf

Condition monitoring of drill process using a telemetry system

Design of a custom software application to monitor and communicate cnc machining process information to aid in chatter identification

In-Process Monitoring of Tool Wear Stage by the Frequency Band-Energy Method

A machining economics problem is considered where feed rate selection and tool replacement policies are to be determined. A new stochastic model for tool wear, called a diffusion-threshold model, is proposed. This tool wear model allows the machining economics problem to be formulated as a stochastic optimal control problem incorporating measurement feedback of tool wear. Two types of control policies are described. One is a traditional machining economics policy and the other utilizes tool wear feedback and allows on-line decision making. The optimal policy is described for both types. An example problem based on actual data is worked out that compares the two approaches and demonstrates the utility of information feedback and on-line control.

/pdf/the-drilling-problem-a-stochastic-modeling-and-control-1d8stb531r.pdf

The drilling problem: A stochastic modeling and control example in manufacturing

Real-time control of drilling was carried out by measuring the thrust force and determining its gradient. Using a microcomputer-based feedback control system, experiments were carried out under different cutting conditions to test the effectiveness of the thrust force gradient in predicting failure. The system was able to predict failure due to excessive wear commonly encountered with 5 and 8 mm drills. With such drills, excessive weat at the outer corner led to an increase in the local temperature which in turn increased the wear. This led to very high temperatures (>600°C), causing local welding of the drill material to the peripheral surface of the hole being drilled. Furthermore, the high temperatures reduced the compressive yield strength of the drill material, causing sub-surface fracture to occur under the influence of the cutting loads. This cyclic phenomenon of “seizure” due to local welding and “release” due to shear fracture (i.e. “stick-slip”) caused sharp fluctuations in the thrust force under constant feed. This paper discusses the effectiveness of the control system described above in predicting failure due to the excessive wear common to large drills. This system is also contrasted with another based on vibration measurements which has been successfully used to predict failure due to fracture common with small drills. This paper also presents other experimental sensor schemes in the literature. Finally, this paper proposes a framework for an “intelligent” machining process control system driven by multiple sensors, which would facilitate untended machining.

Condition monitoring of drill process using a telemetry system

Citations

Design of a custom software application to monitor and communicate cnc machining process information to aid in chatter identification

References

In-Process Monitoring of Tool Wear Stage by the Frequency Band-Energy Method

The drilling problem: A stochastic modeling and control example in manufacturing

Drill wear sensing and failure prediction for untended machining

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