Claims:WE CLAIM:
1. A method for thermal error compensation of a CNC machine for distortion caused by changes in ambient temperature, the method comprising steps of:
(i) calibrating temperature dependent parameters of the machine or part thereof to arrive at abaseline characteristic for tool centre point; said calibration involving-
a) fixing metrology fixture [7] on table of a 3-axis vertical machining centre and plurality of temperature sensors and displacement sensors onto the machine;
b) predicting of temperature evolution of machineby computing the thermal contact resistance and conductance of the machine tool components by flushing the machine to predetermined ambient temperature;
c) testing environmental temperature variation error of the machine component kept in idle and in real time with respect to time as a function of temperature; and
d) developing of thermal network model for machine structure and linear network error chain model for predictingbaseline characteristics for tool centre point;
(ii) periodically compensating for real time thermal error generated in the active machine; said compensation involving-
a) setting of the coordinates of the machine after switching on the machine;
b) periodically measuring the ambient temperature using temperature sensors and communicating through internet of things (IOT) to industrially programmable logic control module;
c) estimating temperature evolution of the machine ;
d) computing tool centre point distortion by linear network error chain model;and
e) updating external offsets in the CNC controller through IRIS
to compensate for the distortion caused by changes in the ambient temperature.
2. The method as claimed in claim 1, wherein the CNC machine is selected from a group comprising vertical machining centre, horizontal machining centre, double column machining centre, turning machines, grinding machines and special purpose machine tools.
3. The method as claimed in claim 1, wherein the temperature dependent parameter is measured using a plurality of sensors selected from a group comprising of ambient temperature, chemical changes and physical changes.
4. The method as claimed in claim 1, the metrology fixture [7] is used to measure the Tool Center Point (TCP) distortion.
5. The method as claimed in claim 1, wherein temperature variation error comprises geometry error and volumetric error.
6. The method as claimed in claim 1, wherein geometry error and volumetric error is measured using plurality of fixed sensors mounted on the machine to calculate the
geometry error and volumetric error as a function of temperature on a timed basis.
7. The method as claimed in claim 1, wherein environmental temperature variation error of the machine component is carried out by mapping tool path error and tracking changes in machine geometry as a function of temperature on a timed basis.
8. The method as claimed in claim 1, wherein external offsets are updated involving data from a plurality of sensors from the baseline characterization.
9. The method according to claim 1, wherein the communication of the ambient temperature, work and tool offsets between the CNC machine and IoT device is two way.
10. The method as claimed in claim 1, wherein the sensor is selected from a group comprising thermal sensor, photoelectricsensors, thermoelectricsensors, electrochemicalsensors, electromagneticsensors, thermo-optic sensorsand combination thereof.
11. A system for compensating real time thermal error in a CNC machine during machining, said system comprising-
metrological fixture with sensors to assess displacement; thermal sensors to asses distortion due to ambient temperature; Internet of Things platform communicating the thermal changes to controller of CNC machine and compensating error due to thermal changes during machining.
, Description:TECHINICAL FIELD
The present disclosure is in relation to an automatic thermal compensation system for a Computer Numerical Control (CNC) machine. Particularly, the present invention provides a method for thermal compensation for a machine to account for ambient temperature fluctuations due to day-night cycle or seasonal variations. More particularly, the disclosure involves a method for thermal compensation using the thermal network model.
BACKGROUND AND PRIOR ART
The performance of a CNC machine can be judged based on the observed accuracy, precision, surface finish as well as the cycle time taken during machining. Although geometric, assembly-related, fixture-related, machine wear-related and thermal issues are causes for the reduced precision in machining; it is noted in the literature [J. B. Bryan, (1990) CIRP Annals - Manufacturing Technology, 39(2), 645–656; Ramesh et. al. (2000), The International Journal of Machine Tools and Manufacture, 40(9), 1257–1284] that the thermal causes are significant and they might contribute anywhere from 40% to 70% of all machining errors. It is well known that ambient temperature fluctuations in a 24-hour day-night cycle, as well as seasonal changes, are among major reasons for thermal distortion of Tool Centre Point (TCP). It is therefore important to account for these variations and compensate them electronically at regular intervals of time. This compensation will be useful for both automotive industrial applications wherein repetitive tasks are performed as well as for die-mold machining carried out continuously over a few days to a few weeks. It is to be noted that a few machine tool users work around these problems manually by shifting the origin of the machine at regular intervals of time to account for changing TCP position with time. Further, to reduce these effects on machining accuracy and precision, some machine tool manufacturers recommend users to commission the machine in a temperature-controlled environment. Some standards even provide a guideline for the temperature level to be set at 20°C as the metrology inspection procedures are generally carried out at 20°C temperature. Such a stringent requirement will put lot of hardship on CNC machine users in terms of high investment cost to set-up air-conditioned space in addition to high operating costs. This invention is regarding the development of a thermal compensation methodology to cater to ambient temperature fluctuations and dispense the requirement of a temperature controlled environment for the commissioning of a CNC machine tool. A few prior scientific works regarding the thermal compensation system to cater to ambient temperature fluctuations are briefed herein.
Mian et al., (2013), Precision Engineering, 37, 372-379 uses a numerical technique known as finite element analysis to predict the distortion of the tool center point of a CNC machine subject to ambient temperature variations. Although the prediction of the distortion is in close correspondence with the experimental measurements, real-time implementation of the same on the shop floor is difficult due to the higher computation effort requirements.
Zhang et al. (2017), Precision Engineering, 47, 231-238 model thermal errors using a technique known as thermal error transfer method to take care of ambient temperature variations. In this technique, the time constant of constituent elements of a machine tool are calculated and the thermal error transfer for each component are derived and then assembled for a complete machine tool using construction relationship. Although the technique is simple to implement, the accuracy is not very high.
Tan et al. (2014), International Journal of Machine Tools and Manufacture, 82-83, 11-20, employed a combination of Fourier synthesis of ambient temperature variations, Newton’s cooling law and regression techniques to arrive at a thermal network model between ambient temperature and the thermal error at every instant of time. Although this method was developed considering large machine tools subjected to seasonal and day-night variations which typically show a non-linear hysteretic behaviour, the method can be employed for smaller machine tools as well. However, this method is not suitable for real-time application of compensation.
US 5619414, US 7354386 and US 2008/0215178 describe about thermal compensation modelling and deployment strategy for CNC machine tools. However, very little work has been done regarding thermal compensation to cater to external heat sources such as fluctuating ambient temperature due to day-night and seasonal variations. In light of these circumstances, thermal compensation to cater to ambient temperature variations is of utmost importance as a reliable compensation model deployed in a machine tool can dispense its requirement of expensive installation and operation in a climate controlled chamber.
Considering the quality of machining accuracy and precision of machined components in a cost-effective manner, it is necessary to develop an accurate thermal compensation method to manage thermal issues appropriately and overcome the disadvantages associated with the available methods.
SUMMARY OF INVENTION
Accordingly, the present invention provides a method for thermal compensation of a CNC machine for distortion caused by changes in ambient temperature, the method comprising steps of:
calibrating temperature dependent parameters of the machine or part thereof to arrive at abaseline characteristic for tool centre point; said calibration involving-
fixing metrology fixture [7] on table of a 3-axis vertical machining centre and plurality of temperature sensors and displacement sensors onto the machine;
predicting temperature evolution of machineby computing the thermal contact resistance and conductance of the machine tool components by flushing the machine to predetermined ambient temperature;
testing environmental temperature variation error of the machine component kept in idle and in real time with respect to time as a function of temperature; and
developing of thermal network model for machine structure and linear network error chain model for predictingbaseline characteristics for tool centre point;
periodically compensating for real time thermal error generated in the active machine; said compensation involving-
setting of the coordinates of the machine after switching on the machine;
periodically measuring the ambient temperature using temperature sensors and communicating through internet of things (IOT) platform named IRIS;
estimating temperature evolution of the machine ;
computing tool centre point distortion by linear network error chain model;and
updating external offsets in the CNC controller through IRISto compensate for the distortion caused by changes in the ambient temperature.
The present invention is also in relation to a system for compensating real time thermal error in a CNC machine during machining, said system comprising- metrological fixture withsensors to assess displacement; thermal sensors to asses distortion due to ambient temperature; Internet of Things platform communicating the thermal changes to controller of CNC machine and compensating error due to thermal changes during machining.
BRIEF DESCRIPTION OF FIGURES
The features of the present invention can be understood in detail with the aid of the appendedfigures. It is to be noted however, that the appended figures illustrate only typical embodimentsof this invention and are therefore not to be considered limiting of its scope for the invention.
Figure 1: A schematic of the experimental set-up along with the precision metrology fixture containing the precision capacitive displacement sensors.
Figure 2: The illustration of thermal network model for machine tool through nodes and resistances.
Figure 3: The linear thermal error chain for a C-frame vertical machining centre.
Figure 4: The thermal distortion of TCP in Y- and Z- directions are significant during machine idling condition over day-night cycle.
Figure 5: The thermal compensation model is fit to the experimental data shown in Figure 5 and the predicted distortion show a close correspondence with the experimental values.
Figure 6: The compensation methodology is further validated by subjecting the machine tool in a thermal chamber and exposed to three different ambient temperature profiles: a) profile-1, b) profile-2 and c) profile-3.
Figure 7: The predicted TCP distortion in Z- direction matches well with the experimentally observed distortion for all three ambient temperature profiles.
DETAILED DESCRIPTION OF INVENTION:
The foregoing description of the embodiments of the invention has been presented for the purpose of illustration. It is not intended to be exhaustive or to limit the invention to the precise form disclosed as many modifications and variations are possible in light of this disclosure for a person skilled in the art in view of the figures, description and claims. It may further be noted that as used herein and in the appended claims, the singular forms "a", "an", and "the" include plural reference unless the context clearly dictates otherwise. Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by person skilled in the art.

The thermal characteristics of machine tools are influenced by both external and internal heat sources. For instance, the machine tools are susceptible to exogenous influences, which are derived mainly from varying environmental conditions like day and night cycles or seasonal transitions during which considerable amount of temperature change occurs resulting in heterogeneous temperature distribution within the machine tool structure. These thermal gradients cause heat flow in the machine tool structure, which result in thermal deformations regardless of whether the machine is in operation mode or idling.
The present invention provides a compensation method to cater to the changes in the TCP distortion because of changes in ambient temperature thereby dispensing the stringent requirement of commissioning of the machine tool in a temperature-controlled space. The compensation method involves a thermal network model. A lumped system assumption is used during the modelling of machine tool components and using the ambient temperature, the machine’s temperature evolution and the resulting thermal distortion of Tool Centre Point (TCP) is predicted in order to compensate, i.e., shift the origin of the coordinate system through the CNC controller
The present invention is in relation to a method for thermal compensation of a CNC machine for distortion caused by changes in ambient temperature, the method comprising steps of:
calibrating temperature dependent parameters of the machine or part thereof to arrive at abaseline characteristic for tool centre point; said calibration involving-
fixing metrology fixture [7] on table of a 3-axis vertical machining centre and plurality of temperature sensors and displacement sensors onto the machine;
predicting of temperature evolution of machineby computing the thermal contact resistance and conductance of the machine tool components by flushing the machine to predetermined ambient temperature;
testing environmental temperature variation error of the machine component kept in idle and in real time with respect to time as a function of temperature; and
developing of thermal network model for machine structure and linear network error chain model for predictingbaseline characteristics for tool centre point;
periodically compensating for real time thermal error generated in the active machine; said compensation involving-
setting of the coordinates of the machine after switching on the machine;
periodically measuring the ambient temperature using temperature sensors and communicating through internet of things (IOT) to industrially programmable logic control module;
estimating temperature evolution of the machine ;
computing tool centre point distortion by linear network error chain model;and
updating external offsets in the CNC controller through IRIS
to compensate for the distortion caused by changes in the ambient temperature.
In an embodiment of present invention, the CNC machine is selected from a group comprising vertical machining centre, horizontal machining centre, double column machining centre, turning machines, grinding machines and special purpose machine tools.
In another embodiment of present invention, the temperature dependent parameter is measured using a plurality of sensors selected from a group comprising of ambient temperature, chemical changes and physical changes.
In another embodiment of present invention, the metrology fixture [7] is used to measure the Tool Center Point (TCP) distortion.
In another embodiment of present invention,temperature variation error comprises geometry error and volumetric error.
In another embodiment of present invention,geometry error and volumetric error is measured using plurality of fixed sensors mounted on the machine to calculate thegeometry error and volumetric error as a function of temperature on a timed basis.
In another embodiment of present invention,environmental temperature variation error of the machine component is carried out by mapping tool path error and tracking changes in machine geometry as a function of temperature on a timed basis.
In another embodiment of present invention,external offsets are updated involving data from a plurality of sensors from the baseline characterization.
In another embodiment of present invention, the communication of the ambient temperature, work and tool offsets between the CNC machine and IoT device is two way.
In another embodiment of present invention, the sensor is selected from a group comprising thermal sensor, photoelectric sensors, thermoelectric sensors, electrochemical sensors, electromagnetic sensors, thermo-optic sensors and combination thereof.
The present invention is also in relation to a system for compensating real time thermal error in a CNC machine during machining, said system comprising-
metrological fixture withsensors to assess displacement; thermal sensors to asses distortion due to ambient temperature; Internet of Things platform communicating the thermal changes to controller of CNC machine and compensating error due to thermal changes during machining.
The main aspect of the invention is to develop a method for thermal compensation of a CNC machine involving a thermal network model to understand the thermo-mechanical behaviour of a machine subjected to ambient temperature variations. The following are the main assumptions during thermal networkmodelling: the machine components are taken as lumped systems; the machine is in idle mode and hence internal heat sources are neglected and only external heat source because of ambient temperature is considered; the thermal contact resistance between different machine elements is computed using phenomenological models; and the thermal error chain is linear.
The first step in the thermal network modelling process is prediction of the evolution of temperature of machine components subjected to ambient temperature changes. The temperature of machine components at any given instant of time generally differ from each other because of different time constants? t?_i. Further, since the machine components are connected to each other, the thermal contact resistance at the joints are computed which are then used to update the temperature of machine components through a thermal network solution obtained from a set of Ordinary Differential Equations (ODE) describing the thermo-mechanical behaviour of the machine tool. Next, a linear thermal error chain is assumed and the thermal expansion concept is used to compute the TCP displacement for validation with the experimentally measured data.
Further, the real-time deployment of this ambient temperature compensation system is straightforward since the solution of the ordinary differential equation at chosen time instants are computationally inexpensive. The compensation or offsets is then written automatically to the external offset function in the CNC controller at periodic intervals of time to change the origin of the coordinate system through the in-house developed Internet of Things (IoT) device, named IRIS. Further details on the thermal network modelling and deployment process are elucidated in the following sections.
A thermal network model is formulated which incorporates the mechanism of heat transfer in the contact region between different machine tool components through thermal contact resistance. Then, the heat conservation equation for each of the considered machine component is set-up and the resulting system of ordinary differential equation is solved to obtain the temperature evolution of each machine tool component. Then, using the linear thermal error chain for the machine tool, the TCP distortion is estimated, which is used for compensation. The schematic of the development procedure of thermal network model-based compensation strategy in a machine is depicted in Scheme I.

Scheme I
Typically, the process flow diagram on the operation of thermal compensation involving IOT platform (IRIS) is provided in scheme II and is as follows:

Scheme II
the first step is to measure critical parameters such as the ambient temperature, monitoring them, setting controlling parameters and communicating the required information (external offsets) to the corresponding physical systems. IRIS is used as the platform to set-up communication between different physical systems. It reads the real-time temperature information from CNC control unit through the PLC module. The communication setup of IRIS with CNC is independent of the controller and hence, thermal compensation technique works for all type of controllers and consequently for different kinds of CNC machine tools: vertical machining centre, horizontal machining centre, double column machining centre, turning machines, grinding machines and special purpose machine tools.
The detailed process of thermal network modelling is explained for a C-frame vertical machining centre as an example in the following sections.
For C-frame structures, the machine tool is symmetric about the YZ plane and therefore, the X-deviation of TCP position is negligible. If the machine is assumed as consisting of lumped components, then from the heat conservation equation, the relation between machine tool component temperature, thermal time-constant and environmental temperature is,
t_i¬(dT_i)/dt+ T_i= T_E (Eqn. 1)
where, t_i is the thermal time constant of the ith machine tool component in seconds, T_i is the temperature of the machine tool component, i, in degree Celsius, T_E is the environmental temperature in degree Celsius and t is the time duration in seconds. The above equation is valid for every machine tool component, i, and illustrates that for a given change in ambient or environmental temperature, the temperature of each machine tool part will evolve differently depending on its time constant t_i. Physically, it can be seen that the thermal time constant of each machine tool component is different as it indicates how fast it responds to the change in environmental temperature. That is, the thermal time constant of a component is a function of different material, geometric and external parameters like density of the component material (?), volume of the component (V), specific heat of the component material (Cp), coefficient of convective heat transfer (h) and the total convective surface area of the component (As) and is computed as,
t_i= (? V C_p)/(h A_s ) (Eqn. 2)
The thermal network model of machine structure considering the heat flow betweenmachine components is shown in Figure 2. Nodes represent the machine components while the resistors present in between the machine nodes are a measure of the heat that is being conducted between the two adjacent machine components. The heat conservation equation is modified to include the effects of thermal contact conductance between the contact regions. The thermal contact conductance is calculated using Mikicmodel [B.B.Mikic, (1974) International Journal of Heat and Mass Transfer 17(2), 205-214] based on the type of joining method used, the parameters used for joining such as tightening torque and so on. The system of ordinary differential equations which describes the evolution of temperature for different machine components is provided in Eqn. 3 as follows:
?(?C_p V)?_C (dT_C)/dt=-h A_C (T_C-T_E )-h_CB A_CB (T_C-T_B )- h_CM A_CM (T_C-T_M)
?(?C_p V)?_B (dT_B)/dt = -h A_B (T_B-T_E )-h_CB A_CB (T_B-T_C )- h_CSB A_CSB (T_B-T_CS)
?(?C_p V)?_M ( dT_M)/dt = -h? A?_M (T_M-T_E )-h_CM A_CM (T_M-T_C )- h_MS A_MS (T_M-T_S)
?(?C_p V)?_S (dT_S)/dt = -h? A?_S (T_S-T_E )-h_MS A_MS (T_S-T_M )
?(?C_p V)?_CS (dT_CS)/dt = -h? A?_CS (T_CS-T_E )-h_CSB A_CSB (T_CS-T_B )- h_CST A_CST (T_CS-T_T)?(?C_p V)?_T (dT_T)/dt = -h? A?_T (T_T-T_E )-h_CST A_CST (T_T-T_CS )
where,
T_C= temperature in the column unit (°C)
T_B = temperature in the bed unit (°C)
T_M= temperature in the milling head unit (°C)
TS = temperature in the spindle unit (°C)
T_CS = temperature in the cross-slide unit (°C)
T_T= temperature in the work-table unit (°C)
T_E = ambient or environmental temperature (°C)
h = convective heat transfer coefficient (W/m2K)
? = density value of respective machine components (Kg/m3)
A = surface area of respective machine components (m2)
Cp = specific heat of respective component materials (J/KgK)
V = volume of respective machine components (m3)
h_CB= thermal contact conductance between the column and the bed (W/m2K)
h_CM= thermal contact conductance between the column and the milling head (W/m2K)
h_CSB= thermal contact conductance between the cross-slide and the bed (W/m2K)
h_MS= thermal contact conductance between the milling head and the spindle (W/m2K)
h_CST= thermal contact conductance between the cross-slide and the work-table (W/m2K)
A_CB= contact area between the column and the bed (m2)
A_CM= contact area between the column and the milling head (m2)
A_CSB = contact area between the cross-slide and the bed (m2)
A_MS= contact area between the milling head and the spindle (m2)
A_CST= contact area between the cross-slide and the work-table (m2)
The system of ODEs is solved to obtain the evolution of temperature of different machine tool elements using the initial condition, the temperature of machine tool components at time t = 0 is assumed to be equal to the ambient temperature. Next, the concept of thermal error dimension chain is introduced to reduce the complexity in the analysis. The machine tool structure is disintegrated into several units composed of relatively simple geometry with respect to their construction. The thermal error dimension chain in the machine tool is shown in Figure 3. It can be noted that the closed loop, H_0, the distance between the tooltip and the worktable top can be formed using dimensions of other machine tool parts: vertical height of the column from top of base to the horizontal axis of milling head indicated through? H?_1, the height of the milling head from its centre? H?_2, the relevant height of spindleH_3, and the height of the cross slide and table indicated by H_4and? H?_5respectively. Based on these dimensions, the thermal error dimension chain using the closed loop is calculated through,
H_0= ?H_1-H?_2-H_3-H_4-H_5 (Eqn. 4)
Once the evolution of temperature of machine components subjected to ambient temperature is estimated, the next step is to compute the thermal distortion of every component using the coefficient of thermal expansion and reference lengths, H_i.
?(?z)?_i= a?T_i H_i, (Eqn. 5)
where, ?(?z)?_icorresponds to thermal distortion of the ith machine component, a is the coefficient of thermal expansion, ?T_i is the change in temperature of the ith machine component from the reference time (t = 0) and H_i corresponds to the relevant dimension of the ith machine tool component in Z- direction. Although only the thermal distortion component in Z- direction is specified, the same procedure can be applied to obtain the component in Y-direction as well.Finally, the thermal distortion of the tool centre point or the distortion between the tool tip and the top surface of the table is computed using linear thermal error chain.
The complete process of thermal compensation model development and deployment is divided into two steps: the first is the model building process using various experiments consisting of day-night cycles over different seasons and calibration of its parameters, while the next step is the validation of the developed model and its real-time deployment for practical use. As discussed before, the scheme-I illustrates the thermal compensation model building process while scheme-III illustrates the different steps of the compensation model deployment process. The actual deployment process as shown in Scheme-III can be explained as follows: the IoT device is also switched ON automatically when the CNC machine is switched ON. The first step is to load the fixtures and the work piece onto the table, develop or create G&M codes and decide the tools to be used during the manufacturing process. The next step is to set the work and tool offsets of the machining process so that the origin is defined. It is to be noted that the operator can set multiple tool and work offsets as and when the need arises and the compensation algorithm takes them into account. The compensation algorithm code is automatically started after the origin is set. The only real-time input for the compensation algorithm is the ambient temperature, which will be acquired every ?t seconds using the PLC module and the IoT device named IRIS. The next step is to solve for the temperatures of the individual machine tool components using a set of ordinary differential equations (Eqn. 3) using the initial condition. For the first iteration, the temperatures of the machine tool components are considered equal to the initial ambient temperature, i.e., at the time instant when the tool and the work offsets are set; for the further iterations, the temperatures of the machine tool components at the previous converged iteration is taken as the initial condition. Once the temperatures of machine tool components are estimated at time instant t + ?t, the next step is to estimate the TCP components using linear thermal error chain (Eqns. 4 and 5). The final step is the communication of the real-time offsets to the CNC controller using the IoT device, IRIS. This process of updating the external offsets is continued in real-time till the machine is switched OFF.

Scheme III
Experimental:The experimental set-up includes a metrology fixture [7] (Figure 1) fixed on the table of a 3-axis vertical machining center. As discussed before, the metrology fixture [7] is used to measure the Tool Center Point distortion using the capacitive sensors. The components of the machine tool/fixture shown in Figure 1 are numbered in an ascending manner from 1 to 7 refer to the following: table [1], cross-slide [2], bed [3], column [4], milling head [5], spindle [6] and metrology fixture [7]. Resistance Temperature Detector (RTD) sensor for ambient temperature (TE) is monitored using a PLC. In addition, a precision ground diskis rigidly clamped onto spindle shaft to act as its extension and a steel fixture is designed to place six precise capacitive sensorsso as to measure spindle distortion at six designated points (Figure 1; sensors Sa, Sb,Sc, Sd, Se and Sf) on the rotating disk. Each of the three sensors are used for radial and axial displacement measurements. The sensors are placed at 120 degrees angle from each other while the radial sensor S_a is placed at angle ? from X-axis (Figure 1). The displacements recorded from sensors (Sa, Sb,Sc, Sd, Se and Sf) are then transformed to obtain thermal distortion,?x, ?y,?z, ?R,pitch and yaw angles (?x and ?y) using the solution of following matrix equations:
[¦(1&R_0 sin?&-R_0 cos?@1&?-R?_0 sin?(60+?)&R_0 cos?(60+?)@1&R_0 cos?(30+?)&R_0 sin?(30+?))][¦(?z@?_x@?_y )]=[¦(S_d@S_e@S_f )], (Eqn. 6)
[¦(cos?&sin?&1@-cos?(60+?)&-sin?(60+?)&1@-sin?(30+?)&cos?(30+?)&1)][¦(?x@?y@?R)] = [¦(S_a@S_b@S_c )] (Eqn. 7)
Where, R_0 is the radius of the disk on which radial displacement measurements are performed (Figure 1). Custom-built IoT system named IRIS is used to synchronize the data from FANUC CNC controller (such as spindle load and motor temperature) along with temperature data and simultaneously, the spindle distortion is calculated through capacitive sensors (Equations 6 and 7).
The experiment is spanned in such a way that the machine tool is subjected to idling or Environmental Temperature Variation Error (ETVE) test for more than 24 hours to capture the day-night cycle ambient temperature variation. The actual ambient temperature profile and the spindle distortion in Y- and Z- directions are shown in Figure 4. It is to be highlighted that although the ambient temperature varies by about 8 degrees within 24 hours, the Z-direction TCP distortion is about 50 microns while Y-direction distortion is about 20 microns. It is observed that the other components of TCP distortions were negligible. The next step is to calibrate the compensation model parameters so that the deviation between the predicted and the actual TCP distortion is minimized. The resulting plot after this step is shown in Figure 5. It can be seen that the predicted thermal distortion of TCP is in close correspondence with the experimentally measured data. The final step is then to validate the compensation model by subjecting the machine tool to ambient temperature variations different from the one used to calibrate the model. For this, the machine tool is put into a thermal chamber and exposed to three different ambient temperature profiles (Figure 6). The resulting temperature at different points of machine tool structure and TCP distortion is recorded. It can be noted from Figure 7 that the predictions are in the same trend as the experimental data but with some mismatch for the experimental profile-1. The deviations can be attributed to the assumptions during thermal network modelling as well as experimental uncertainties. The same procedure can be repeated to compute TCP distortion in Y-direction. Once the TCP distortions are recorded, they can be updated to the CNC controller through the in-house IoT device, IRIS. By using the method, the thermal error of the machining is reduced to 40 – 50% of the original error. Further to this, present invention is downward compatible, i.e., the compensation methodology can be deployed on existing CNC machine tools as well as new machine tools, only one ambient temperature sensor is used for training the thermal network model parametersand the subsequent implementation of thermal compensation in an automated fashion.Using this process, the requirement of a temperature-controlled environment for operation of a CNC machine tool is dispensed without significantly compromising on the machining precision.