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Cutting Force Monitoring Experiment 02

An experiment was set up at the Oak Ridge National Laboratory (ORNL) to test methods for estimating the cutting forces in real time within machine tools for any spindle speed, force profile, tool type, and cutting conditions. Before cutting, a metrology suite and instrumented tool holder were used to induce magnetic forces during spindle rotation, while on-machine vibrations, magnetic forces, and error motions were measured for various combinations of speeds and forces. A model may then relate the measured accelerations to the forces, such that during cutting, on-machine measured vibrations may be used in the model to estimate the cutting forces in real time. To test this process, the metrology suite and the instrumented tool holder were removed, except that the on-machine accelerometers remained. A dynamometer was then set up on the worktable with a workpiece to independently measure cutting forces during machining. Various cutting passes were performed with an end mill while the dynamometer data and accelerometer data were collected. Even though considerable research has been conducted to estimate cutting forces with accelerometers and measured frequency response functions (FRFs), one main challenge remains: a method must be created to estimate the cutting forces in real-time for any spindle speed, force profile, tool type, and cutting conditions. This dataset can be used to develop or advance such methods for industrial adoption.

About this Dataset

Updated: 2024-02-22
Metadata Last Updated: 2023-12-01 00:00:00
Date Created: N/A
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Data Provided by:
smart manufacturing
Dataset Owner: N/A

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Title Cutting Force Monitoring Experiment 02
Description An experiment was set up at the Oak Ridge National Laboratory (ORNL) to test methods for estimating the cutting forces in real time within machine tools for any spindle speed, force profile, tool type, and cutting conditions. Before cutting, a metrology suite and instrumented tool holder were used to induce magnetic forces during spindle rotation, while on-machine vibrations, magnetic forces, and error motions were measured for various combinations of speeds and forces. A model may then relate the measured accelerations to the forces, such that during cutting, on-machine measured vibrations may be used in the model to estimate the cutting forces in real time. To test this process, the metrology suite and the instrumented tool holder were removed, except that the on-machine accelerometers remained. A dynamometer was then set up on the worktable with a workpiece to independently measure cutting forces during machining. Various cutting passes were performed with an end mill while the dynamometer data and accelerometer data were collected. Even though considerable research has been conducted to estimate cutting forces with accelerometers and measured frequency response functions (FRFs), one main challenge remains: a method must be created to estimate the cutting forces in real-time for any spindle speed, force profile, tool type, and cutting conditions. This dataset can be used to develop or advance such methods for industrial adoption.
Modified 2023-12-01 00:00:00
Publisher Name National Institute of Standards and Technology
Contact mailto:[email protected]
Keywords Smart manufacturing , Industry 4.0 , Data-driven dynamics , Frequency response function , Machine tool , Modeling , Dynamics , Machining processes , Sensing , Monitoring , Diagnostics
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}

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