JP2023107737A - Machine tool processing accuracy diagnostic device and processing accuracy diagnostic method - Google Patents

Abstract

To quantitatively predict the influence of temperature adjusting means such as an air conditioner on the processing accuracy of a machine tool.SOLUTION: A processing accuracy diagnostic device 10 of a machine tool 2 includes: an air conditioner operation pattern setting part 11 which sets an operation pattern of an air conditioner 3; a processing condition setting part 12 which sets a processing start scheduled time and a processing end scheduled time by the machine tool 2; a room temperature sensor 5 and an outside temperature sensor 6 which acquire the room temperature in a plant 1 obtained by air conditioner 3 and a temperature outside the plant 1; and a processing accuracy influence degree prediction part 14 which predicts the degree of influence of the air conditioner 3 on the processing accuracy based on the operation pattern of the air conditioner 3 acquired from the air conditioner operation pattern setting part 11, the processing start scheduled time and the processing end scheduled time acquired from the processing condition setting means 12, the room temperature in the plant 1 and the temperature outside the plant 1 acquired from the room temperature sensor 5 and the outside temperature sensor 6, and the setting temperature of the air conditioner 3 acquired from the air conditioner operation pattern setting part 11.SELECTED DRAWING: Figure 1

Description

The present disclosure relates to an apparatus and method for estimating and diagnosing the influence on machining accuracy of a machine tool when the room temperature or the like of the environment in which the machine tool is placed changes.

When machining is performed using a machine tool, if the room temperature in the factory changes, thermal displacement occurs in the machine tool, degrading the machining accuracy of the workpiece.
In order to maintain the machining accuracy of machine tools, it is effective to use air conditioning (including air conditioners and air conditioners) to prevent large changes in the room temperature in the factory. However, implementing high-level temperature control 24 hours a day increases the energy consumption of air conditioning and increases the cost burden. Therefore, it is desirable to turn off the air conditioner at night and on weekends when there are no workers. However, in that case, there is a problem that the room temperature changes abruptly when the air conditioning is turned on again, and it takes a long time until the accuracy of the machine tool stabilizes.
In addition, as another method of suppressing thermal displacement of machine tools, temperature sensors are attached to each part of the machine tool structure, the amount of displacement is calculated based on the measured temperature, and the amount of axial movement is changed accordingly. Correction is widely used. However, there is a limit to the accuracy of thermal displacement correction, and errors occur when temperature changes are large. For example, if the room temperature changes abruptly, such as when the air conditioning system is turned on in winter, the thermal displacement correction error may increase.
As a countermeasure against the above problems, Patent Document 1 estimates the temperature change of the environment in which the machine tool is placed based on the temperature of the structure of the machine tool, and based on that, the magnitude of the effect on thermal displacement is disclosed. Disclosed is a method for diagnosing inequality.
In addition, Patent Document 2 discloses that the entire machine tool is surrounded by a cover, and the inside of the cover is controlled to a constant temperature by air conditioning so that the temperature of the machine tool remains constant even in an environment where the room temperature changes, thereby suppressing thermal displacement. A method for doing so is disclosed.

Japanese Patent No. 5912756 Japanese Utility Model Laid-Open No. 59-183340

In the method of Patent Literature 1, although the magnitude of the influence of thermal displacement at the present time is known, it is not known how long the influence will continue.
The method of Patent Document 2 is considered to be very effective in suppressing thermal displacement due to changes in room temperature. However, energy is consumed for air conditioning for machine tools. In addition, this method is a countermeasure for machine tools alone, and if an attempt is made to ensure the accuracy of various old and new machine tools in a factory, air conditioning of the factory is required as before.
Conventionally, when the room temperature changes due to turning on the air conditioning, etc., it is often the case that the time to start machining and the time to turn on the air conditioning are determined based on an empirical rule of thumb for estimating the time required for the accuracy of the machine tool to stabilize. . However, the time it takes for the accuracy to stabilize varies depending on factors such as the outside temperature, as well as the size of the machine tool, the time required for processing, and the required accuracy. It is easy to predict when the work is the same each time, but when the work is different, it is difficult to predict based on empirical rules alone.

Therefore, an object of the present disclosure is to provide a machining accuracy diagnosis device and a machining accuracy diagnosis method for a machine tool that can quantitatively predict the influence of temperature adjustment means such as air conditioning on the machining accuracy of the machine tool. It is a thing.

In order to achieve the above object, a first configuration of the present disclosure provides machining accuracy when the body temperature of the machine tool is changed by temperature adjustment means that affects the body temperature of the machine tool in a factory where the machine tool is installed. A machining accuracy diagnosis device that predicts and diagnoses the impact on
temperature control operation pattern setting means for setting an operation pattern of the temperature control means;
machining condition setting means for setting at least a scheduled machining start time and a scheduled machining end time by the machine tool;
a temperature information acquiring means for acquiring the influence temperature on the machine body temperature by the temperature adjusting means and/or the air temperature outside the factory;
The operation pattern of the temperature adjustment means acquired from the temperature adjustment operation pattern setting means, the scheduled processing start time and the scheduled processing end time acquired from the processing condition setting means, and the influence acquired from the temperature information acquisition means The amount of influence of the temperature adjustment means on the machining accuracy based on at least one of the temperature and/or the air temperature outside the factory, and the set temperature of the temperature adjustment means acquired from the temperature adjustment operation pattern setting means. and machining accuracy influence amount prediction means for predicting the
In the present disclosure, the "influence temperature" refers to the temperature that can affect the body temperature of the machine tool, such as the room temperature in the factory due to air conditioning and the set temperature of temperature control devices such as oil jackets directly provided on the machine tool. .
According to another aspect of the first configuration, in the above configuration, the operation pattern of the temperature adjustment means set by the temperature adjustment operation pattern setting means based on the predicted influence amount on the machining accuracy; It is characterized by further comprising schedule changing means for changing at least one of the scheduled processing start time set by the condition setting means.
In another aspect of the first configuration, in the above configuration, the schedule changing means includes the influence amount on the machining accuracy predicted by the machining accuracy influence amount prediction means and the machining accuracy obtained from the machining condition setting means. The operation pattern of the temperature adjusting means is changed based on a comparison with the allowable value of the amount of influence set in advance during time.
According to another aspect of the first configuration, in the above configuration, the schedule changing means uses the influential temperature, the set temperature of the temperature adjustment means, and the temperature outside the factory to use the energy consumption of the temperature adjustment means. to predict
The operation pattern of the temperature adjusting means is changed so that the amount of influence on the machining accuracy is less than the allowable value and the energy consumption of the temperature adjusting means is minimized.
In another aspect of the first configuration, in the above configuration, the schedule changing means changes the amount of influence on the machining accuracy predicted by the machining accuracy influence amount prediction means to the machining accuracy obtained from the machining condition setting means. It is characterized in that the scheduled processing start time is changed so as to be smaller than the allowable value of the influence amount set in advance during the time.
In another aspect of the first configuration, in the above configuration, the temperature information acquiring means includes a room temperature sensor for measuring the room temperature inside the factory, which is the influential temperature, and an outside temperature for measuring the temperature outside the factory. and a temperature sensor for
The machining accuracy influence amount prediction means calculates the current room temperature in the factory measured by the room temperature sensor according to a preset room temperature change estimation formula within the machining time acquired from the machining condition setting means. estimating a room temperature change in the factory based on the set temperature of the temperature adjusting means or the air temperature outside the factory, and estimating a preset airframe temperature change based on the estimated room temperature change in the factory. estimating the body temperature change of the machine tool from the above equation, and estimating the thermal displacement of the machine tool from a preset thermal displacement estimation formula based on the predicted body temperature change of the machine tool, The amount of change in the thermal displacement within the machining time is obtained as the amount of influence on the machining accuracy.
Another aspect of the first configuration is the above configuration, wherein the temperature adjustment means is an air conditioner provided in the factory,
When estimating the room temperature change by the room temperature change estimation formula, the machining accuracy influence amount prediction means receives the set temperature of the air conditioner when the power of the air conditioner is on, and when the power of the air conditioner is off. Time is characterized by estimating changes in room temperature inside the factory by using the temperature outside the factory as an input.
In another aspect of the first configuration, in the above configuration, the machining accuracy influence amount prediction means compares the temperature measured by the room temperature sensor with the room temperature change estimated by the room temperature change estimation formula. and correcting the room temperature change estimation formula.
Another aspect of the first configuration is the above configuration, comprising a machine body temperature sensor that measures a machine body temperature of the machine tool,
The machining accuracy influence amount prediction means compares the temperature measured by the airframe temperature sensor with the airframe temperature estimated by the airframe temperature change estimation formula, and corrects the airframe temperature change estimation formula. and

In order to achieve the above object, a second configuration of the present disclosure provides machining accuracy when, in a factory where a machine tool is installed, the body temperature of the machine tool changes due to temperature adjustment means that affects the body temperature of the machine tool. A machining accuracy diagnosis method for predicting and diagnosing the influence on
a temperature control operation pattern acquisition step of acquiring an operation pattern of the temperature control means;
a machining condition acquiring step of acquiring at least a scheduled machining start time and a scheduled machining end time by the machine tool;
a temperature information acquiring step of acquiring at least one of the temperature that the temperature adjusting means affects the machine body temperature and/or the air temperature outside the factory, and the set temperature of the temperature adjusting means;
Among the acquired operation pattern of the temperature adjusting means, the acquired scheduled processing start time and the acquired scheduled processing end time, the acquired influence temperature and/or the temperature outside the factory, and the set temperature of the temperature adjusting means and a machining accuracy influence amount prediction step of estimating the amount of influence of the temperature adjustment means on the machining accuracy based on at least one of the following.
According to another aspect of the second configuration, in the above configuration, the operation pattern of the temperature adjustment means acquired in the temperature adjustment operation pattern acquiring step and the machining It is characterized by further executing a schedule change step of changing at least one of the scheduled processing start time acquired in the condition acquisition step.

According to the present disclosure, the operation pattern of the temperature adjustment means (for example, information on the time to turn on/off the power or change the set temperature in the case of air conditioning), the scheduled processing start time and processing end scheduled time, and the influence temperature etc. The information can be used to quantitatively predict the effect of the temperature adjustment means on processing accuracy.
According to another aspect of the present disclosure, in addition to the above effects, by adopting the schedule changing means, the operation pattern of the temperature adjustment means for maintaining the machining accuracy and / or The processing schedule can be changed appropriately and easily.
According to another aspect of the present disclosure, in addition to the above effects, when the time to process a work is predetermined, the schedule changing means changes the operation pattern of the temperature adjustment means so that the required accuracy of the work can be satisfied. is changed, when machining that requires high accuracy is planned, the temperature of the machine can be stabilized before machining is started by, for example, operating the temperature adjusting means in advance to ensure machining accuracy. In this case, energy can be saved by turning off the temperature adjusting means or by loosening the range of the set temperature when there is no plan for machining that requires high accuracy.
According to another aspect of the present disclosure, in addition to the above effects, the operation pattern of the temperature adjustment means is changed so that the energy consumption of the temperature adjustment means is reduced. can determine the operation pattern of the temperature adjustment means.
According to another aspect of the present disclosure, in addition to the above effects, the schedule changing means changes the scheduled machining start time so that the amount of influence on the machining accuracy becomes smaller than the allowable value. By estimating the time until the amount of influence on accuracy falls below the allowable value, it becomes possible to schedule machining in consideration of the influence on machining accuracy. This is effective when the operation pattern of the temperature adjusting means is predetermined.
According to another aspect of the present disclosure, in addition to the above effects, a change in room temperature in the factory due to the temperature adjustment means is estimated by calculation using a physical model, and a change in body temperature of the machine tool is estimated based on the room temperature change. Furthermore, since the thermal displacement of the machine tool is estimated based on the machine body temperature change and the amount of influence on the machining accuracy is obtained, the influence on the actual workpiece accuracy can be accurately estimated.
According to another aspect of the present disclosure, in addition to the above effects, by changing the room temperature change prediction method according to the power supply state of the air conditioner, it is possible to accurately predict the room temperature change in the factory.
According to another aspect of the present disclosure, in addition to the effects described above, the room temperature change estimation formula is corrected by comparing the room temperature estimation result and the actual measurement result, so the prediction accuracy can be improved.
According to another aspect of the present disclosure, in addition to the effects described above, the aircraft temperature change estimation formula is corrected by comparing the aircraft temperature change estimation result and the actual measurement result, so the prediction accuracy can be improved.

1 is a conceptual diagram of a factory in which machine tools are installed and a machining accuracy diagnosis device; FIG. 4 is a flow chart of a machining accuracy diagnosis method of form 1 for determining the power-on time of air conditioning. It is a graph showing the temperature change prediction result when determining the power-on time of air conditioning. It is a graph showing the calculation result of the accuracy change function when determining the power-on time of air conditioning. FIG. 10 is a flow chart of a second embodiment of a machining accuracy diagnosis method for determining a machining schedule when an air-conditioning schedule is determined in advance; FIG.

A first embodiment of the present disclosure will be described below with reference to the drawings.
FIG. 1 shows an example of a factory provided with a machining accuracy diagnostic device according to the first configuration of the present disclosure.
A factory 1 is provided with machine tools 2 and 2 and an air conditioner 3 for controlling the temperature in the factory. The air conditioner 3 is an example of temperature adjustment means of the present disclosure.
Further, a plurality of machine body temperature sensors 4, 4, . . . In the factory 1, a plurality of room temperature sensors 5, 5, . . . are installed. Outside the factory 1, a temperature sensor 6 for outside air temperature is installed. The room temperature temperature sensor 5 and the outside temperature temperature sensor 6 are examples of the temperature information acquiring means of the present disclosure. The room temperature acquired by the room temperature sensor 5 is an example of the influence temperature of the present disclosure.
The machining accuracy diagnosis device 10 acquires information from each of the temperature sensors 4 to 6, performs analysis based on the information, determines a machining schedule for the machine tool 2, and determines an operation pattern for the air conditioner 3. The machining accuracy diagnosis device 10 may be installed separately from the machine tool 2, or the NC device of the machine tool 2 may share some or all of the functions. The machining accuracy diagnostic device 10 does not have to be installed inside the factory 1 . The machining accuracy diagnostic device 10 includes a CPU and a memory connected to the CPU, and these control the operation.

Specifically, the machining accuracy diagnosis device 10 includes an air conditioning operation pattern setting unit 11, a machining condition setting unit 12, an accuracy change allowable value setting unit 13, a machining accuracy influence amount prediction unit 14, and a schedule change unit 15. It has
The air conditioning operation pattern setting unit 11 sets operation patterns such as the timing of turning on/off the air conditioner 3 and the set temperature. The operation pattern is set by an input means (not shown) or by a command from the schedule change unit 15 . The air conditioning operation pattern setting unit 11 is an example of the temperature control operation pattern setting means of the present disclosure.
The machining condition setting unit 12 sets at least the scheduled machining start time and the scheduled machining end time based on the machining program in the machine tool 2 . This setting is also performed by an input means (not shown) or by a command from the schedule changing section 15 . The processing condition setting unit 12 is an example of processing condition setting means of the present disclosure.
The accuracy change allowable value setting unit 13 sets an allowable value for accuracy change of the machine tool 2 during the machining time set by the machining condition setting unit 12 . This setting is also performed by an input means (not shown).

The processing accuracy influence amount prediction unit 14 uses the operation pattern of the air conditioner 3 set by the air conditioning operation pattern setting unit 11, the scheduled processing start time and the scheduled processing end time set by the processing condition setting unit 12, and each of the temperature sensors 4 to 6. Based on the information, the amount of influence of the air conditioner 3 on the machining accuracy is predicted. The machining accuracy influence amount prediction unit 14 is an example of the machining accuracy influence amount prediction means of the present disclosure.
The schedule change unit 15 adjusts the air conditioning operation pattern setting unit 11 based on the amount of influence on the machining accuracy predicted by the machining accuracy influence amount prediction unit 14 and the allowable value set by the accuracy change allowable value setting unit 13. Either the operation pattern or the scheduled machining start time of the machining condition setting unit 12 is changed (reset). The schedule changing unit 15 is an example of the schedule changing means of the present disclosure.

In the first embodiment, the machining schedule for the machine tool 2 has already been determined by the machining condition setting part 12 as an example. , the schedule change unit 15 changes the operation pattern of the air conditioner 3 so as to ensure the accuracy of the prediction.
Normally, machining has a rough machining stage that does not require high machining accuracy and a finishing machining stage that requires high machining accuracy. If so, the required accuracy of the workpiece can be satisfied.
However, the body temperature of the machine tool 2 changes with a delay with respect to the change in the room temperature inside the factory 1, as shown in FIG. Therefore, even if the change in room temperature stabilizes, the temperature of the machine tool 2 continues to change, and the accuracy may become unstable. Therefore, it is necessary to monitor and predict changes in the body temperature of the machine tool 2 as well as changes in the room temperature in the factory 1 .
Therefore, the machining accuracy diagnosis method in which the machining accuracy influence amount prediction unit 14 predicts the accuracy change of the machine tool 2 and the schedule change unit 15 determines the timing to turn on the air conditioner 3 will be described below with reference to the flowchart and diagram of FIG. 3 and the graphs of FIGS.

Step A1: Acquire information on the factory 1 side (temperature control operation pattern acquisition step and temperature information acquisition step).
As information on the factory 1 side, the current room temperature inside the factory 1, the temperature outside the factory 1, and the power on/off and set temperature of the air conditioner 3 are acquired. As the room temperature in the factory 1, the current value measured by the room temperature sensor 5 provided in the factory 1 is used. The temperature outside the factory 1 is measured by the outside temperature sensor 6 in the first embodiment, but external data such as meteorological data can also be used. Furthermore, not only the current value but also the predicted value of future changes may be used as needed. As for the information on the power ON/OFF of the air conditioner 3 and the set temperature, not only the current information but also the information on the future setting content from the schedule of the air conditioner 3 is used as necessary.

Step A2: Acquire information on the machine tool 2 side (machining condition acquisition step).
As information on the machine tool 2 side, the current machine body temperature, the machining schedule, and the allowable value of accuracy change (allowable accuracy change) are acquired. Information on the machining schedule and the change in allowable accuracy is set in advance in the machine tool 2 as shown in FIG. 4, for example. First, the required machining accuracy is set for machining programs prepared according to the type of workpiece to be machined and the stage of machining such as rough machining and finishing. Furthermore, by setting in the machine tool 2 in which time period each machining program is scheduled to be executed, the allowable accuracy change in each time period of the machine tool 2 is set. In the example of FIG. 4, the allowable accuracy change is set to 50 μm for rough machining on Mondays from 9:00 to 13:00, and the allowable accuracy change is set to 10 μm for finishing machining from 13:00 to 19:00.

Step A3: Assume that the current time is the time when the air conditioner 3 is powered on (or the set temperature is changed). After that, the power-on time is changed from the present to the end of machining, and the calculations of steps A4 to A7 are performed to predict the influence of thermal displacement on machining accuracy.
Step A4: Estimate changes in room temperature in the factory 1 due to turning on/off the air conditioner 3 and changing settings.
A room temperature change in the factory 1 when the air conditioner 3 is turned off is predicted. When the air conditioner 3 is turned off, the room temperature inside the factory 1: θ _in is represented by a first-order lag change with the temperature outside the factory 1: θ _out as input, as shown in Equation 1 below. Formula 1 is an example of a room temperature change estimation formula (air conditioning power OFF) of the present disclosure.

On the other hand, when the air conditioner 3 is turned on, the room temperature in the factory 1: θ _in is represented by the change of the first-order lag with the set temperature of the air conditioner 3: θ _C as an input, as shown in Equation 2 below. Equation 2 is an example of the room temperature change estimation equation (air conditioning power ON) of the present disclosure.

In Equations 1 and 2, the values of the time constants T _off and T _on express the followability of the room temperature change to the input temperature, and the smaller the time constant, the faster the change. Normally, the room temperature changes more quickly when the air conditioner 3 is ON, so T _off >>T _on . Also, this value varies depending on the size of the space in the factory 1, the heat insulation of the factory 1, the output of the air conditioner 3, and the like. If this value is identified in advance, room temperature changes can be predicted.
Also, it is conceivable that the change in room temperature is affected by the outside air temperature even when the air conditioner 3 is ON. As for this, the value of the time constant T _on is corrected based on the predicted value of the temperature change. For example, when predicting a change when heating is used in winter, the lower the outside air temperature, the more difficult it is for the room _temperature to rise. In the present embodiment 1, prediction is performed using formulas 1 and 2, but other formulas may be used for prediction based on measurement results and the like.

Step A5: Predict the power consumption of the air conditioner 3 . For example, the power consumption can be approximated by Equation 3 below. The first term in Equation 3 is the power consumption required to start up the air conditioner 3, and the second term is the power consumption required to keep the room temperature inside the factory 1 at a constant temperature when affected by the temperature outside the factory 1. be.

Step A6: Estimate the body temperature change and thermal displacement of the machine tool 2 after the air conditioner 3 is powered on. When the room temperature of the environment in which the machine tool 2 is placed changes, the machine body temperature also changes. The airframe temperature change at this time can be represented by a first-order lag response with the room temperature change as the input. This response is obtained by successive calculations using a difference equation such as Equation 4 below. Equation 4 is an example of the airframe temperature change estimation equation of the present disclosure.

Equation 4 is calculated for each machine tool 2 and for each temperature measurement point, and body temperature changes at each part when room temperature changes predicted by Equations 1 and 2 are estimated. Furthermore, the accuracy change due to thermal displacement of the machine tool 2 is predicted from the estimated body temperature change of the machine tool 2 . This accuracy change can be expressed as a function of airframe temperature, as in Equation 5 below. This function is hereinafter referred to as an accuracy change function of the machine tool 2 . The function to be used as the accuracy change function is determined in advance based on experiments and analyses.

Specifically, the accuracy change function can be expressed by a linear expression of the temperature of each part of the machine tool 2, for example, as shown in Equation 6 below.

In this method, temperature sensors are attached to a plurality of structures of the machine tool 2, such as the bed, column, spindle, etc., and the temperatures of these are multiplied by preset proportionality constants and added up to determine the thermal displacement of the machine tool 2. to estimate The constant of proportionality can be identified by obtaining the relationship between temperature and thermal displacement by FEM analysis or actual measurement.
In Embodiment 1, the machine tool 2 is provided with the body temperature sensor 4, and the current temperature information is used to predict the temperature change of the machine body. do not have to. Further, as the accuracy change function of the machine tool, an expression other than the linear expression shown in Expression 6 is conceivable. Additionally, variables other than airframe temperature may be used, such as variations in room temperature around the machine.

Step A7: Predict the accuracy change of the machine tool 2 during work machining. Regarding the accuracy change function of the machine tool 2 obtained in step A6, by calculating the width of change in the time zone corresponding to the machining schedule set in step A2, the following equation 7 shows the accuracy change function for each work being machined. Accuracy change of the machine tool 2 can be predicted/estimated. Equations 5 to 7 are examples of thermal displacement estimation equations of the present disclosure, and the change in accuracy obtained by Equation 7 is an example of the amount of change in thermal displacement within the machining time (the amount of influence on machining accuracy).

Step A8: Determine whether the calculations have been completed for all power-on times. When the power-on time=scheduled machining end time, the calculation ends.
Step A9: If it is determined in step A8 that the power-on time is not equal to the scheduled machining end time, the assumed power-on time of the air conditioner 3 is shifted later, and the calculations of steps A4 to A7 are repeated. Steps A3 to A9 are machining accuracy influence amount prediction steps of the present disclosure.
Step A10: Satisfying the condition of accuracy change during workpiece machining<permissible value of accuracy change (permissible accuracy change), and setting the time at which the predicted value of the power consumption of the air conditioner 3 to be the minimum is the power-on time of the air conditioner 3 (schedule change step).

FIG. 3 shows an example of determining the power-on timing of the air conditioner 3 based on the above flow. In this example, when the power of the air conditioner 3 is turned off on Friday night, the timing to start the air conditioner 3 is determined in order to ensure the accuracy in the processing performed on Monday after the weekend holiday. there is In this simulation, in order to make the results easier to understand, it is assumed that the set temperature θ _C of the air conditioner is constant at 20°C and the air temperature θ _out outside the factory 1 is constant at 10°C. Calculations are made based on Equations 1 and 2 with the time constant T _off =360 (minutes) for room temperature change with the air conditioner OFF and the time constant T _on for room temperature change with the air conditioner ON =60 (minutes). These values are identified in advance by experiments and calculations.
When the air conditioner 3 is turned off on Friday evening, the room temperature θ _in of the factory 1 gradually decreases due to the outside temperature. Airframe temperatures θ _m,1 , θ _m,2 , and θ _m,3 of each part also decrease with a delay from the change in room temperature. The degree of delay from the change in room temperature differs depending on the part, and the difference in the degree of delay causes a temperature difference in the machine, resulting in thermal displacement. Also, the degree of delay can be represented by the time constant shown in Equation (4). In the example of FIG. 3, the time constants of airframe temperature changes are T _m,1 =240 (minutes), T _m,2 =180 (minutes), and T _m,3 =120 (minutes), and based on Equation 4, calculating. The value of the time constant of airframe temperature change is also identified in advance by experiments and calculations.

On the other hand, when _the power of the air conditioner 3 is turned on, the room temperature θ _in of _the factory ₁ first rises so as to approach the set temperature. Rise. The problem here is that even if the room temperature returns to its original state and becomes constant, the body temperature continues to change, and the machining accuracy may become unstable. Therefore, it is necessary to turn on the power of the air conditioner 3 well in advance before processing. The power consumption of the air conditioner 3 is obtained by Equation 3. In this example, the room temperature when the power of the air conditioner 3 is turned on is 10° C., and the power consumption at startup is constant regardless of the time of power-on. Since the outside air temperature is also assumed to be constant at 10° C., the power consumption of the air conditioner 3 is calculated to increase according to the time the power is on. Therefore, the power-on time should be delayed as long as the processing accuracy is satisfied.

In the example of FIG. 4, the allowable accuracy change is set to 50 μm for rough machining on Mondays from 9:00 to 13:00, and the allowable accuracy change is set to 10 μm for finishing machining from 13:00 to 19:00. Also, in this example, the accuracy change function ΔX _m of the machine tool 2 is calculated by the following equation 8 using the machine body temperature at three locations.

At this time, if the work accuracy change ΔX _w is calculated according to the method of the flow chart in FIG. If the power supply of the air conditioner 3 is set to automatically turn on based on the judgment result, the air conditioner 3 of the factory 1 will automatically turn on at 3:00 a.m. before the start of work on Monday, and the temperature change of the machine will be stable after the start of work. can start processing.
In Equation 5, the accuracy change function is obtained simply assuming that it is proportional to the airframe temperature at a certain location, but the accuracy change function can be set arbitrarily. For example, a formula for variations in room temperature and airframe temperature at a plurality of locations, a differential value of temperature change, and the like is also conceivable.

As described above, the machining accuracy diagnostic device 10 for the machine tool 2 of Embodiment 1 sets the air conditioning operation pattern setting unit 11 for setting the operation pattern of the air conditioner 3, and the scheduled start time and scheduled end time of machining by the machine tool 2. A processing condition setting unit 12 to be set, a room temperature sensor 5 and an outside temperature temperature sensor 6 that acquire the room temperature inside the factory 1 and the temperature outside the factory 1 by the air conditioning 3, and the air conditioning operation pattern setting unit 11. 3 operation pattern, the scheduled processing start time and the scheduled processing end time acquired from the processing condition setting unit 12, the room temperature inside the factory 1 acquired from the room temperature sensor 5 and the outside temperature sensor 6, and the temperature outside the factory 1 A processing accuracy influence amount prediction unit 14 for predicting the amount of influence of the air conditioner 3 on the processing accuracy based on the air temperature and the set temperature of the air conditioner 3 acquired from the air conditioning operation pattern setting unit 11. The above processing accuracy diagnosis method. to run.
According to this configuration, the influence of the air conditioner 3 on the machining accuracy is quantitatively predicted using information such as the operation pattern of the air conditioner 3, the scheduled machining start time, the scheduled machining end time, and the room temperature in the factory 1. be able to.

In particular, since the schedule changing unit 15 is further provided for changing the operation pattern of the air conditioner 3 set by the air conditioning operation pattern setting unit 11 based on the predicted amount of influence on the machining accuracy, the predicted influence on the machining accuracy can be Accordingly, the operation pattern of the air conditioner 3 for maintaining machining accuracy can be appropriately and easily changed.
In addition, the schedule change unit 15 calculates the amount of influence on the machining accuracy predicted by the machining accuracy influence amount prediction unit 14 and the allowable value of accuracy change set in advance during the machining time acquired from the machining condition setting unit 12. Since the operation pattern of the air conditioner 3 is changed based on the comparison, when machining that requires high precision is planned, the air conditioner 3 should be operated in advance to stabilize the temperature of the machine before starting machining. machining accuracy can be ensured. In this case, energy can be saved by turning off the air conditioner 3 when there is no plan for machining that requires high accuracy, or by setting the range of temperature loosely.
Furthermore, the schedule change unit 15 predicts the power consumption (energy consumption) of the air conditioner 3 using the room temperature in the factory 1, the set temperature of the air conditioner 3, and the temperature outside the factory 1, and the amount of influence on the machining accuracy is smaller than the permissible value of accuracy change, and the operation pattern of the air conditioner 3 is changed so that the predicted value of the power consumption of the air conditioner 3 is minimized, so that the required accuracy can be satisfied while saving energy consumption. Thus, the operation pattern of the air conditioner 3 can be determined.

Then, the machining accuracy influence amount prediction unit 14 calculates the current temperature inside the factory 1 measured by the room temperature sensor 5 according to a preset room temperature change estimation formula within the machining time acquired from the machining condition setting unit 12. The room temperature change in the factory 1 is estimated based on the room temperature and the temperature outside the factory 1, and the machine tool 2 is calculated based on the estimated room temperature change in the factory 1 using a preset machine body temperature change estimation formula. based on the predicted temperature change of the machine tool 2, estimate the thermal displacement of the machine tool 2 by a preset thermal displacement estimation formula, and estimate the thermal displacement of the machine tool 2 within the machining time The amount of change is obtained as the amount of influence on machining accuracy.
That is, by calculation using a physical model, the room temperature change in the factory 1 due to the air conditioning 3 is estimated, the body temperature change of the machine tool 2 is estimated based on the room temperature change, and the machine tool 2 temperature change is further based on the body temperature change. Since the amount of influence on machining accuracy is obtained by estimating thermal displacement, the influence on actual workpiece accuracy can be accurately estimated.
In particular, when estimating the room temperature change by the room temperature change estimation formula, the machining accuracy influence amount prediction unit 14 receives the set temperature of the air conditioner 3 when the power of the air conditioner 3 is on, and the power of the air conditioner 3 is off. Since the temperature outside the factory 1 is used as an input to estimate the change in the room temperature inside the factory 1, the change in the room temperature inside the factory 1 can be predicted with high accuracy.

Form 2 of the present disclosure will be described below.
In the above embodiment 1, the method of turning on the power of the air conditioner 3 in advance so as to ensure the required accuracy based on the predetermined machining schedule has been described. On the other hand, it is conceivable that the time for turning on the air conditioner 3 has already been determined, and the scheduled processing start time is determined accordingly. In that case, it is sufficient to find the time required until the change in room temperature stabilizes and the required accuracy can be secured. A specific example according to the second configuration of the present disclosure will be described below. However, since the configuration of the machining accuracy diagnostic device 10 is the same as that of the above embodiment 1, the machining accuracy diagnostic method with different processing will be described based on the flowchart of FIG.
Step B1: As information on the factory 1 side, the current room temperature inside the factory 1, the temperature outside the factory 1, and the power on/off and set temperature of the air conditioner 3 are acquired (temperature control operation pattern acquisition step and temperature information acquisition step ). This is the same as the process described in step A1 of FIG.
Step B2: As information on the machine tool 2 side, acquire information on the current machine body temperature, machining schedule, and allowable accuracy change (machining condition acquisition step). Regarding the machining schedule, the required machining time is determined by the machining and is a fixed value, but the expected machining start time is undecided at this point and will be determined after the process of the subsequent step B6 is performed.
Step B3: Set the time to turn on the air conditioner 3 or change the set temperature.
Step B4: Estimate changes in the room temperature in the factory 1 due to turning on/off the air conditioner 3 and changing the settings. The calculation method is the same as step A4.
Step B5: Estimate the body temperature change and thermal displacement of the machine tool 2 after the power of the air conditioner 3 is turned on. The calculation method is the same as step A6.

Step B6: Predict the change in accuracy during machining of the workpiece when the scheduled workpiece machining start time is changed.
Since the time required for machining a workpiece is constant, if the machining start time _tw,start of the workpiece is shifted later, the machining end time _tw,end of the workpiece is also shifted later. In Equation 4, while changing tw _,start and tw _,end , the accuracy change _.DELTA.Xw during machining of the workpiece is obtained. Steps B3 to B6 are machining accuracy influence amount prediction steps of the present disclosure.
Step B7: As a result of the processing of step B6, display the scheduled machining start time that satisfies the condition of accuracy change during workpiece machining<accuracy change tolerance (schedule change step).
Under the conditions shown in FIGS. 3 and 4, it can be seen that it takes 10 hours after the power supply of the air conditioner 3 is turned on until the temperature change of the machine tool 2 stabilizes and finishing can be performed. By displaying this time as the machining accuracy stabilization time on the operation screen of the machine tool 2, the operator can determine the machining schedule so as to perform the finishing machining after the temperature change of the machine tool 2 stabilizes.

As described above, in the machining accuracy diagnostic device 10 and the machining accuracy diagnostic method of Embodiment 2 as well, information such as the operation pattern of the air conditioner 3, the scheduled machining start time, the scheduled machining end time, and the room temperature in the factory 1 is used. , the influence of the air conditioning 3 on the machining accuracy can be quantitatively predicted.
In particular, since it further includes a schedule change unit 15 that changes the scheduled machining start time set by the machining condition setting unit 12 based on the predicted amount of influence on machining accuracy, , the machining schedule for maintaining the machining accuracy can be appropriately and easily changed.
In addition, the schedule change unit 15 determines that the amount of influence on machining accuracy predicted by the amount of machining accuracy influence amount prediction unit 14 is greater than the allowable value of accuracy change set in advance during the machining time acquired from the machining condition setting unit 12. Therefore, by estimating the time until the amount of influence on the machining accuracy due to the air conditioning 3 falls below the allowable value, the machining schedule is scheduled in consideration of the influence on the machining accuracy. to be able to stand This is effective when the operation pattern of the air conditioner 3 is predetermined.

Modifications common to the first and second forms will be described below.
In Equations 1, 2, and 4 above, the time constants T _on , T _off , and T _m,i are used to predict the temperature change. need to leave In addition to calculating the area of the factory 1, the volume of the machine structure, and the physical property values of the materials, a method of identifying the values based on the results of actual measurements is conceivable. The values of the time constants _T.sub.on , _T.sub.off , and _T.sub.m,i may be determined using a known parameter search method so that the error between the actual measurement result and the prediction result is small. By comparing the estimation result and the actual measurement result and correcting the estimation formula in this manner, the accuracy of prediction can be improved.
Furthermore, when operating the machining accuracy diagnostic device 10, if it is possible to identify and update parameters using temperature information actually measured by the room temperature sensor 5 in the factory 1 and the body temperature sensor 4 of the machine tool 2, Prediction accuracy can be further improved.

Further, in the above-described forms 1 and 2, using equations based on physical models such as equations 1 to 5, room temperature change, temperature change of the machine tool 2, and thermal displacement of the machine tool 2 are calculated in this order to perform machining. Although the amount of influence on accuracy is calculated, it is not always necessary to perform calculations based on theoretical formulas when obtaining the amount of influence on machining accuracy. For example, a machine learning technique can be used to create a model that calculates the amount of influence on machining accuracy by inputting machining time, temperature information, and the like.
Furthermore, in Embodiments 1 and 2, the schedule change unit changes one of the air conditioning operation pattern and the scheduled processing start time based on the amount of influence on the processing accuracy, but both can be changed. .
The number and arrangement of machine tools, air conditioners, and temperature sensors are not limited to the first and second modes.
In addition to the air conditioning exemplified in Embodiments 1 and 2 above, the temperature control means includes a temperature control device that is directly provided in the body of the machine tool, such as an oil jacket (cooling passage) provided in the column, for temperature control. . In this case, the acquired influence temperature is the temperature of the cooling liquid, and the time constant of airframe temperature change is also the value when the oil jacket is used. "Temperature adjustment" includes not only cooling but also heating.

1 Factory 2 Machine tool 3 Air conditioning 4 Body temperature sensor 5 Room temperature sensor 6 Outside temperature sensor 10 Machining accuracy diagnosis device 11 Air conditioning operation pattern setting unit 12 Machining condition setting unit 13 Accuracy change allowable value setting unit 14 Machining accuracy influence amount prediction unit 15 Schedule change unit.

Claims (15)

A machining accuracy diagnostic device for estimating and diagnosing the influence on machining accuracy when the body temperature of the machine tool is changed by a temperature adjusting means that affects the body temperature of the machine tool in a factory where the machine tool is installed,
temperature control operation pattern setting means for setting an operation pattern of the temperature control means;
machining condition setting means for setting at least a scheduled machining start time and a scheduled machining end time by the machine tool;
a temperature information acquiring means for acquiring the influence temperature on the machine body temperature by the temperature adjusting means and/or the air temperature outside the factory;
The operation pattern of the temperature adjustment means acquired from the temperature adjustment operation pattern setting means, the scheduled processing start time and the scheduled processing end time acquired from the processing condition setting means, and the influence acquired from the temperature information acquisition means The amount of influence of the temperature adjustment means on the machining accuracy based on at least one of the temperature and/or the air temperature outside the factory, and the set temperature of the temperature adjustment means acquired from the temperature adjustment operation pattern setting means. Machining accuracy influence amount prediction means for predicting
A machining accuracy diagnostic device for a machine tool, comprising: The operation pattern of the temperature adjusting means set by the temperature adjusting operation pattern setting means and the scheduled machining start time set by the machining condition setting means based on the predicted amount of influence on the machining accuracy. 2. The machining accuracy diagnostic apparatus for a machine tool according to claim 1, further comprising schedule changing means for changing at least one of the two. The schedule change means is configured to change the influence amount on the machining accuracy predicted by the machining accuracy influence amount prediction means and an allowable value of the influence amount set in advance during the machining time acquired from the machining condition setting means. 3. The machining accuracy diagnosis device for a machine tool according to claim 2, wherein the operation pattern of said temperature adjusting means is changed based on the comparison of the . The schedule change means predicts the energy consumption of the temperature adjustment means using the influential temperature, the set temperature of the temperature adjustment means, and the temperature outside the factory,
2. The operation pattern of said temperature adjusting means is changed so that the amount of influence on said processing accuracy is less than said allowable value and the energy consumption of said temperature adjusting means is minimized. 4. The machining accuracy diagnostic device for the machine tool according to 3. The schedule changing means is configured so that the amount of influence on the machining accuracy predicted by the amount of machining accuracy influence predicting means is greater than the allowable value of the amount of influence set in advance during the machining time acquired from the machining condition setting means. 3. The machining accuracy diagnosis device for a machine tool according to claim 2, wherein said scheduled machining start time is changed so that the time is also reduced. The temperature information acquisition means includes a room temperature sensor for measuring the room temperature inside the factory, which is the influencing temperature, and an outside temperature sensor for measuring the temperature outside the factory,
The machining accuracy influence amount prediction means calculates the current room temperature in the factory measured by the room temperature sensor according to a preset room temperature change estimation formula within the machining time acquired from the machining condition setting means. estimating a room temperature change in the factory based on the set temperature of the temperature adjusting means or the air temperature outside the factory, and estimating a preset airframe temperature change based on the estimated room temperature change in the factory. estimating the body temperature change of the machine tool from the above equation, and estimating the thermal displacement of the machine tool from a preset thermal displacement estimation formula based on the predicted body temperature change of the machine tool, 6. The machining accuracy diagnostic apparatus for a machine tool according to claim 1, wherein the amount of change in said thermal displacement within machining time is obtained as an amount of influence on machining accuracy. The temperature adjustment means is an air conditioner provided in the factory,
When estimating the room temperature change by the room temperature change estimation formula, the machining accuracy influence amount prediction means receives the set temperature of the air conditioner when the power of the air conditioner is on, and when the power of the air conditioner is off. 7. A machining accuracy diagnosis system for a machine tool according to claim 6, wherein a change in room temperature inside said factory is estimated by inputting the temperature outside said factory. The machining accuracy influence amount prediction means compares the temperature measured by the room temperature sensor with the room temperature change estimated by the room temperature change estimation formula, and corrects the room temperature change estimation formula. 7. The machining accuracy diagnosis device for a machine tool according to claim 6. The machining accuracy influence amount prediction means compares the temperature measured by the room temperature sensor with the room temperature change estimated by the room temperature change estimation formula, and corrects the room temperature change estimation formula. The machining accuracy diagnosis device for a machine tool according to claim 7. A body temperature sensor for measuring the body temperature of the machine tool,
The machining accuracy influence amount prediction means compares the temperature measured by the airframe temperature sensor with the airframe temperature estimated by the airframe temperature change estimation formula, and corrects the airframe temperature change estimation formula. 7. The machining accuracy diagnosis device for a machine tool according to claim 6. A body temperature sensor for measuring the body temperature of the machine tool,
The machining accuracy influence amount prediction means compares the temperature measured by the airframe temperature sensor with the airframe temperature estimated by the airframe temperature change estimation formula, and corrects the airframe temperature change estimation formula. 8. The machining accuracy diagnosis device for a machine tool according to claim 7. A body temperature sensor for measuring the body temperature of the machine tool,
The machining accuracy influence amount prediction means compares the temperature measured by the airframe temperature sensor with the airframe temperature estimated by the airframe temperature change estimation formula, and corrects the airframe temperature change estimation formula. 9. The machining accuracy diagnosis device for a machine tool according to claim 8. A body temperature sensor for measuring the body temperature of the machine tool,
The machining accuracy influence amount prediction means compares the temperature measured by the airframe temperature sensor with the airframe temperature estimated by the airframe temperature change estimation formula, and corrects the airframe temperature change estimation formula. 10. The machining accuracy diagnosis device for a machine tool according to claim 9. A machining accuracy diagnosis method for estimating and diagnosing the influence on machining accuracy when the body temperature of the machine tool is changed by a temperature adjusting means that affects the body temperature of the machine tool in a factory where the machine tool is installed,
a temperature control operation pattern acquisition step of acquiring an operation pattern of the temperature control means;
a machining condition acquiring step of acquiring at least a scheduled machining start time and a scheduled machining end time by the machine tool;
a temperature information acquiring step of acquiring at least one of the temperature that the temperature adjusting means affects the machine body temperature and/or the air temperature outside the factory, and the set temperature of the temperature adjusting means;
Among the acquired operation pattern of the temperature adjusting means, the acquired scheduled processing start time and the acquired scheduled processing end time, the acquired influence temperature and/or the temperature outside the factory, and the set temperature of the temperature adjusting means a machining accuracy influence amount prediction step of estimating the amount of influence of the temperature adjustment means on the machining accuracy based on at least one;
A machining accuracy diagnosis method for a machine tool, characterized by executing Based on the estimated amount of influence on the machining accuracy, the operation pattern of the temperature adjustment means acquired in the temperature adjustment operation pattern acquisition step and the scheduled machining start time acquired in the machining condition acquisition step. 15. The method of diagnosing machining accuracy of a machine tool according to claim 14, further comprising executing a schedule change step of changing at least one of them.

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