Abstract
The main focus of this study is to verify the possibility to monitor diamond mill wear by measuring the cutting force during stone machining. An ornamental stone was machined on an NC machining centre, retrofitted with a 3-axis dynamometer and data acquisition systems, to investigate the effects of variations in machining parameters. The sensor data include cutting force measurements, further divided into measurable components, such as x, y, and z. Those components were analysed to determine the sensory features that best correlate with diamond mill wear. Tool wear and machining parameters appeared significantly influencing cutting force signals. This suggests that even under the varying cutting conditions involving different values of process parameters, the identified cutting force feature can be used for the reliable and accurate control of diamond mill wear during stone cutting operations.
Highlights
The intense international market competition in stone field has driven the attention of manufacturers on the automation of manufacturing systems as means for increasing the productivity and improving the quality of products.Monitoring of the stone cutting processes plays a very important role to avoid down time of the machine, or to prevent unwanted conditions such as excessive tool wear or breakage
A vast amount of literature exists in the field of tool wear monitoring in metal cutting environment; it suggests that a variety of process parameters can be used to predict the cutting tool state [1]
The present work demonstrated that force measurements may be effectively used to monitor diamond mill wear during stone cutting
Summary
The intense international market competition in stone field has driven the attention of manufacturers on the automation of manufacturing systems as means for increasing the productivity and improving the quality of products.Monitoring of the stone cutting processes plays a very important role to avoid down time of the machine, or to prevent unwanted conditions such as excessive tool wear or breakage. A recent survey of literature in the field of tool condition monitoring stresses the fact that the choice of sensors and the signal interpretation are critical to establish a reliable tool condition monitoring system [1]. Direct methods are less beneficial because the cutting area is largely inaccessible, and online monitoring cannot be carried out while the tool is engaged in in-process cutting. These methods include touch trigger probes, optical, radioactive, proximity sensors, and electrical resistance measurement techniques. The cutting conditions (speed, feed-rate, and depth of cut) are known to affect the sensor signals and a range of methods have been suggested for separating the effects of these conditions from those of wear on the measured parameter
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