Monitoring of Cutting Forces/Torques
The tool breakage costs both time and the material. It is estimated that around 20% of downtime is caused due to the tool failure. By employing conservative machining conditions, tool wear and breakage can be avoided at the cost of machining efficiency. Part machining experts select heavy-cut over high-speed machining. This demands intermittent tool changes which increases the cost of tooling. Reliable and accurate Tool Condition Monitoring abbreviated as TCM can decrease machining time up to 10-15%. Scheduling TCM in advance can also reduce downtime which has made it possible to carry out an active study on in-situ breakage detection and tool wear.
Cutting Force Monitoring by External Sensors
Sensors which are installed to observe cutting force on machining tools are collectively known as external sensors. Internal sensors which are also known as current sensors are mounted on tools of NC machines for spindle and servo motors. Cutting force is measured using dynamometers which are commercially available. These dynamometers determine cutting force by means of quartz crystal piezoelectric transducers. Spindle and table dynameters are available commercially and they can be utilized for micro machining due to their sufficient resolution. They are employed using a small rotating or a non-rotating tool whose dimensions are in some dozens of microns. Despite of the fact that commercial dynamometers are accurate and reliable but they are not frequently used in machining because they are very expensive
Commercially available piezoelectric dynamometers are used to determine cutting torque on the spindle. Use of magnetostrictive sensor to determine torque in the spindle was studied. Spindle motors generate heat which is a critical issue associated with the sensors installed in spindles. In a study suggested temperature compensation can be employed to monitor torque in a reliable manner. In many machines, it is difficult to install force or torque sensor inside the spindle due to limited space. Tool holders are an alternate option to install sensor as they are available commercially. A study used strain gauges in the tool holder for determining radial forces, axial forces and torque. Small sensor-mounted rings or plates mounted at different parts of the machine which are influenced by the cutting force for the commercial use.
Cutting Force Calculation by Spindle Displacement
Monitoring torque or force by using sensor directly on the spindle of a machine requires an extremely intricate arrangement to obtain required resolution during the entire power range of machine tool. Moreover, it is also mandatory that the measurement signal is transmitted without coming into contact with rotating spindle. It is easier to measure spindle displacement without coming into contact than the measurement of torque or force. The study of calculation of cutting force using spindle displacement has also been carried out. Kim et al. made a capacitance based sensor of a cylindrical shape which can be mounted nearby front spindle bearing to calculate the distance variation between the spinning spindle shaft and sensor head under cutting load. The use of capacitance based sensor for the calculation cutting force. It was shown that a bandwidth of up to 1000 Hz was attained when spindle dynamics was compensated for. In the similar manner the measurement of spindle displacement in turning process incorporating three capacitances based sensor. In a motorized spindle that is supported by active magnetic bearings, the gap is determined from command voltage to magnetic bearings in a manner similar to capacitance based sensor which can be utilized for the calculation of cutting force. A high-speed spindle with integrated sensors installed to monitor different spindle conditions that includes run out, vibration and temperature is being extensively used in commercial high-speed machines. Four contamination-resistant and low-priced eddy-current type displacement sensors were used (S1-S4). However, calculation of cutting force using spindle displacement has two major problems i.e. spindle stiffness and thermal influence. Rotating spindle can get deformed or displaced due to the heat generated by motor which should be differentiated from the displacement triggered by cutting force. In commercially established machining centers, coolant is circulated using cooling jackets to control the spindle temperature. Control period has significant influence on thermal deformation in on-off type temperature control. Several thermocouples are used for the calculation of thermal displacement in our study. Numerous studies have done thermal-mechanical spindle modeling.
Cutting Force Monitoring by Internal Sensors
Commercial NC machine tools which use servo motors for spindle rotation or feed drive use current sensor for motion control. The most economical way to calculate cutting force or torque is through the armature current of the motor. When motor disturbance is induced by the torque, servo controller modifies the armature current to curb its effect. In this method, there is no need to use any extra sensors. In study for detection of tool breakage using cutting force calculated by the current of servo motor. An analogous attempt was carried out by observing armature current of the spindle motor. In several commercialized CNCs, a screen displays the spindle load which is considered the simplest way to calculate cutting torque. Some CNCs show the disturbance calculated from servo motors in digital form. Commercially available products to observe servo motor or spindle current also offer fault detection. Drive system’s dynamic characteristics affect armature current. Particularly, to compensate for the dynamics of moving mass in a feed drive is imperative in segregating the effect of cutting force. Feed drive can utilize a disturbance observer to achieve this purpose. To detect and analyze unusual machining process i.e. tool breakage, algorithms have caught the focus of academia for years. Complexity Analysis, Wavelet analysis, artificial neural network, statistics analysis and a frequency domain analysis were used in detecting fault.