Machining accuracy diagnosis device and machining accuracy diagnosis method for machine tools

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

[Technical Field]

[0001] The present disclosure relates to an apparatus and method for predicting and diagnosing the effect on the machining accuracy of a machine tool when the room temperature or other temperature in the environment where the machine tool is placed changes. [Background technology]

[0002] When machining is performed using a machine tool, changes in the room temperature in the factory cause thermal displacement in the machine tool, which deteriorates the machining accuracy of the workpiece. To maintain the machining accuracy of machine tools, it is effective to use air conditioning (including air conditioning facilities and equipment) to prevent large fluctuations in the room temperature inside the factory. However, implementing advanced temperature control 24 hours a day increases the energy consumption of the air conditioning and the cost burden. For this reason, it is desirable to turn off the air conditioning at night and on weekends when there are no workers. However, in this case, the room temperature changes suddenly when the air conditioning is turned on again, and it takes a long time for the accuracy of the machine tools to stabilize. Another widely used method for suppressing thermal displacement in machine tools is thermal displacement compensation, which involves attaching temperature sensors to various parts of the machine tool's structure, calculating the amount of displacement based on the measured temperature, and then adjusting the amount of axis movement accordingly. However, there is a limit to the accuracy of thermal displacement compensation, and errors will occur if the temperature change is large. For example, if the room temperature changes suddenly, such as when starting up an air conditioner in winter, the error in thermal displacement compensation is likely to increase. As a countermeasure to the above problems, Patent Document 1 discloses a method of estimating temperature changes in the environment in which the machine tool is placed based on the temperature of the machine tool's structure, and then diagnosing the magnitude of the impact on thermal displacement based on this. Furthermore, Patent Document 2 discloses a method of suppressing thermal displacement by surrounding the entire machine tool with a cover and controlling the temperature inside the cover to a constant level using air conditioning, thereby keeping the temperature of the machine tool constant even in an environment where the room temperature changes. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 5912756 [Patent Document 2] Japanese Utility Model Application Publication No. 59-183340 Summary of the Invention [Problem to be solved by the invention]

[0004] The method of Patent Document 1 can determine the magnitude of the current effect of thermal displacement, but it does not know how long the effect will last, making it difficult to create a processing schedule based on the diagnosis results. The method in Patent Document 2 appears to be very effective in suppressing thermal displacement caused by changes in room temperature. However, it consumes energy for air conditioning the machine tool. Furthermore, this method is a countermeasure for a single machine tool, and if you want to ensure accuracy for a variety of new and old machine tools in a factory, you will need to continue air conditioning the factory as usual. In the past, when room temperature changed due to factors such as turning on the air conditioning, the time until the accuracy of the machine tool stabilized was predicted empirically, and the time to start machining and turn on the air conditioning was often determined based on this. However, the time until accuracy stabilizes varies depending on factors such as the outside temperature, and the criteria for judgment also differ depending on the size of the machine tool, the time required for machining, and the required accuracy. This is easy to predict when the workpiece is the same each time, but when the workpiece is different, it is difficult to predict using empirical rules alone.

[0005] Therefore, the present disclosure aims to provide a machining accuracy diagnosis device and machining accuracy diagnosis method for machine tools that can quantitatively predict the impact of temperature control means such as air conditioning on the machining accuracy of machine tools. [Means for solving the problem]

[0006] In order to achieve the above object, a first configuration of the present disclosure is a machining accuracy diagnosis device that predicts and diagnoses the effect on machining accuracy when a machine body temperature is changed by a temperature adjustment means that affects the machine body temperature of a machine tool in a factory where the machine tool is installed, a temperature control operation pattern setting means for setting an operation pattern of the temperature control means; a machining condition setting means for setting at least a scheduled machining start time and a scheduled machining end time for the machine tool; a temperature information acquisition means for acquiring an influence temperature of the temperature adjustment means on the machine temperature and / or an air temperature outside the factory; 1) the operation pattern of the temperature adjustment means acquired from the temperature adjustment operation pattern setting means; 2) the scheduled processing start time and the scheduled processing end time acquired from the processing condition setting means; and 3) At least one of the influence temperature and / or the temperature outside the factory acquired from the temperature information acquisition means, and the set temperature of the temperature adjustment means acquired from the temperature adjustment operation pattern setting means; Three pieces of information and a machining accuracy influence amount prediction means for predicting the amount of influence of the temperature adjustment means on the machining accuracy based on the above. In this disclosure, "affecting temperature" refers to a temperature that can affect the body temperature of the machine tool, such as the room temperature in a factory due to air conditioning, or the set temperature of a temperature control device such as an oil jacket that is directly installed on the machine tool. Another aspect of the first configuration is characterized in that, in the above configuration, it further comprises a schedule change means for changing at least one of the operation pattern of the temperature adjustment means set by the temperature adjustment operation pattern setting means and the scheduled processing start time set by the processing condition setting means based on the predicted amount of impact on the processing accuracy. Another aspect of the first configuration is characterized in that, in the above configuration, the schedule change means changes the operation pattern of the temperature adjustment means based on a comparison between the amount of influence on the machining accuracy predicted by the machining accuracy influence amount prediction means and a preset allowable value of the influence amount during the machining time acquired from the machining condition setting means. Another aspect of the first configuration is, in the above configuration, the schedule change means predicts the energy consumption of the temperature adjustment means using the influencing temperature, the set temperature of the temperature adjustment means, and the air temperature outside the factory, The operation pattern of the temperature adjusting means is changed so as to satisfy the condition that the amount of influence on the machining accuracy is smaller than the allowable value and to minimize the energy consumption of the temperature adjusting means. Another aspect of the first configuration is characterized in that, in the above configuration, the schedule change means changes the scheduled machining start time so that the amount of influence on the machining accuracy predicted by the machining accuracy influence amount prediction means becomes smaller than a preset allowable value of the influence amount during the machining time acquired from the machining condition setting means. In another aspect of the first configuration, in the above configuration, the temperature information acquisition means includes a room temperature sensor that measures the room temperature inside the factory, which is the influencing temperature, and an outside temperature sensor that measures the air temperature outside the factory, The machining accuracy influence amount prediction means estimates a change in room temperature in the factory using a preset room temperature change estimation formula based on the current room temperature in the factory measured by the room temperature sensor and the set temperature of the temperature adjustment means or the air temperature outside the factory, during the machining time acquired from the machining condition setting means, estimates a change in machine body temperature of the machine tool using a preset machine body temperature change estimation formula based on the estimated change in room temperature in the factory, and estimates a thermal displacement of the machine tool using a preset thermal displacement estimation formula based on the predicted change in machine body temperature of the machine tool, and determines the change in thermal displacement within the machining time as an influence amount on machining accuracy. Another aspect of the first configuration is that, in the above configuration, the temperature adjustment means is an air conditioner installed in the factory, The machining accuracy influence amount prediction means is characterized in that, when estimating the room temperature change using the room temperature change estimation formula, when the air conditioner is turned on, the set temperature of the air conditioner is used as an input, and when the air conditioner is turned off, the air temperature outside the factory is used as an input to estimate the room temperature change inside the factory. Another aspect of the first configuration is characterized in that, 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 corrects the room temperature change estimation formula. Another aspect of the first configuration is the above configuration, further comprising a machine body temperature sensor that measures a machine body temperature of the machine tool, The machining accuracy influence amount prediction means is characterized in that it compares the temperature measured by the machine body temperature sensor with the machine body temperature estimated by the machine body temperature change estimation formula, and corrects the machine body temperature change estimation formula.

[0007] In order to achieve the above object, a second configuration of the present disclosure is a machining accuracy diagnosis method for predicting and diagnosing an effect on machining accuracy when a machine body temperature is changed by a temperature adjustment means that affects the machine body temperature of a machine tool in a factory where the machine tool is installed, comprising: a temperature control operation pattern acquisition step of acquiring an operation pattern of the temperature adjustment means; a machining condition acquisition step of acquiring at least a scheduled machining start time and a scheduled machining end time for the machine tool; a temperature information acquisition step of acquiring at least one of an influence temperature of the temperature adjustment means on the machine temperature and / or an air temperature outside the factory, and a set temperature of the temperature adjustment means; 1) the acquired operation pattern of the temperature adjustment means; 2) The acquired scheduled processing start time and scheduled processing end time, and 3) At least one of the acquired influence temperature and / or the temperature outside the factory, and the set temperature of the temperature adjustment means; Three pieces of information and a machining accuracy influence amount prediction step of predicting the amount of influence of the temperature adjustment means on the machining accuracy based on the above. Another aspect of the second configuration is characterized in that, in the above configuration, a schedule change step is further executed to change at least one of the operation pattern of the temperature adjustment means acquired in the temperature adjustment operation pattern acquisition step and the scheduled processing start time acquired in the processing condition acquisition step based on the predicted impact on the processing accuracy. [Effects of the Invention]

[0008] According to the present disclosure, the impact of the temperature adjustment means on processing accuracy can be quantitatively predicted using information such as the operating pattern of the temperature adjustment means (for example, in the case of air conditioning, information on the time to turn the power on and off or change the set temperature), the scheduled start time and scheduled end time of processing, and the affected temperature. According to another aspect of the present disclosure, in addition to the above-mentioned effects, by employing a schedule change means, the operation pattern and / or processing schedule of the temperature adjustment means for maintaining processing accuracy can be appropriately and easily changed in accordance with the predicted impact on processing accuracy. According to another aspect of the present disclosure, in addition to the above effects, when the time to process the workpiece is predetermined, the schedule change means changes the operation pattern of the temperature adjustment means so that the required accuracy of the workpiece can be met, so when processing that requires high accuracy is scheduled, the temperature adjustment means can be operated in advance to stabilize the temperature of the machine before processing begins and ensure processing accuracy. In this case, when processing that requires high accuracy is not scheduled, energy can be saved by turning off the temperature adjustment means or loosening the set temperature range. 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 as to reduce the energy consumption of the temperature adjustment means, thereby making it possible to determine the operation pattern of the temperature adjustment means so as to meet the required accuracy while saving energy consumption. According to another aspect of the present disclosure, in addition to the above-described effects, the schedule change unit changes the scheduled machining start time so that the amount of influence on machining accuracy becomes smaller than the tolerance value, and therefore, by predicting the time until the amount of influence on machining accuracy caused by the temperature adjustment unit becomes equal to or smaller than the tolerance value, it becomes possible to create a machining schedule taking the influence on machining accuracy into consideration. This is effective when the operation pattern of the temperature adjustment unit is determined in advance. According to another aspect of the present disclosure, in addition to the above effects, a change in room temperature in the factory due to a temperature control means is estimated by calculation using a physical model, and a change in the body temperature of the machine tool is estimated based on the change in room temperature, and the thermal displacement of the machine tool is further estimated based on the change in body temperature to determine the amount of impact on machining accuracy, thereby enabling an accurate estimation of the impact on actual workpiece accuracy. According to another aspect of the present disclosure, in addition to the above-mentioned effects, by changing the method of predicting room temperature changes depending on the state of the air conditioning power supply, it becomes possible to accurately predict room temperature changes in a factory. According to another aspect of the present disclosure, in addition to the above-described effects, the room temperature change estimation formula is corrected by comparing the estimated room temperature result with the actual measurement result, thereby improving the accuracy of prediction. According to another aspect of the present disclosure, in addition to the above effects, the estimated results of the aircraft temperature change are compared with the actual measurement results to correct the aircraft temperature change estimation formula, thereby improving the accuracy of prediction. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a conceptual diagram of a factory where machine tools are installed and a machining accuracy diagnosis device. [Figure 2] 10 is a flowchart of a machining accuracy diagnosis method of form 1 for determining the power-on time of an air conditioner. [Figure 3] 10 is a graph showing the results of temperature change prediction when determining the power-on time of an air conditioner. [Figure 4] 10 is a graph showing the calculation results of an accuracy change function when determining the power-on time of an air conditioner. [Figure 5] 10 is a flowchart of a machining accuracy diagnosis method of a second embodiment for determining a machining schedule when an air conditioning schedule is determined in advance. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, a first embodiment of the present disclosure will be described with reference to the drawings. FIG. 1 shows an example of a factory in which a machining accuracy diagnosis device according to a first configuration of the present disclosure is installed. The factory 1 is equipped with machine tools 2, 2 and an air conditioner 3 that controls the temperature inside the factory. The air conditioner 3 is an example of the temperature adjusting means of the present disclosure. In addition, multiple machine body temperature sensors 4, 4... are installed in each part of the machine tools 2, 2. Multiple room temperature sensors 5, 5... are installed inside the factory 1. An outside air temperature sensor 6 is installed outside the factory 1. The room temperature sensor 5 and the outside air temperature sensor 6 are examples of temperature information acquisition means of the present disclosure. The room temperature acquired by the room temperature sensor 5 is an example of an 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, and determines a machining schedule for the machine tool 2 and an operation pattern for the air conditioning 3. The machining accuracy diagnosis device 10 may be installed separately from the machine tool 2, or some or all of the functions may be shared by the NC device of the machine tool 2. The machining accuracy diagnosis device 10 does not have to be installed inside the factory 1. The machining accuracy diagnosis device 10 is configured to include a CPU and a memory connected to the CPU, and operation control is achieved by these.

[0011] Specifically, the processing accuracy diagnosis device 10 includes an air conditioning operation pattern setting unit 11, a processing condition setting unit 12, an accuracy change tolerance setting unit 13, a processing accuracy influence amount prediction unit 14, and a schedule change unit 15. The air conditioning operation pattern setting unit 11 sets operation patterns such as the timing to turn the air conditioner 3 on and off and the set temperature. The operation pattern is set by input means (not shown) as well as by commands from the schedule changing unit 15. The air conditioning operation pattern setting unit 11 is an example of a temperature adjustment operation pattern setting means of the present disclosure. The machining condition setting unit 12 sets at least a scheduled machining start time and a 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) and also by a command from the schedule changing unit 15. The machining condition setting unit 12 is an example of a machining condition setting means of the present disclosure. The accuracy change tolerance setting unit 13 sets a tolerance 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 input means (not shown).

[0012] The machining accuracy influence amount prediction unit 14 predicts the amount of influence of the air conditioning 3 on machining accuracy based on the operation pattern of the air conditioning 3 set in the air conditioning operation pattern setting unit 11, the scheduled machining start time and scheduled machining end time set in the machining condition setting unit 12, and information from each of the temperature sensors 4 to 6. 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 changes (resets) either the operation pattern of the air conditioning operation pattern setting unit 11 or the scheduled processing start time of the processing condition setting unit 12, based on the amount of influence on processing accuracy predicted by the processing accuracy influence amount prediction unit 14 and the tolerance set by the accuracy change tolerance setting unit 13. The schedule change unit 15 is an example of a schedule change means of the present disclosure.

[0013] In this embodiment 1, taking as an example a case where the machining schedule on the machine tool 2 side has already been determined in advance by the machining condition setting unit 12, the machining accuracy influence prediction unit 14 predicts the influence of the air conditioning 3 on the machining accuracy, and the schedule change unit 15 changes the operating pattern of the air conditioning 3 so as to ensure accuracy based on the prediction. Machining typically involves a rough machining stage that does not require high machining accuracy, and a finish machining stage that does require high machining accuracy. Therefore, if the temperature change in the machine tool 2 is small at the time of finish machining, the required accuracy of the workpiece can be met. However, as shown in Figure 3, the body temperature of the machine tool 2 changes with a delay relative to changes in the room temperature in the factory 1. Therefore, even if the room temperature changes stabilize, the temperature of the machine tool 2 continues to change, and accuracy may become unstable. For this reason, it is necessary to monitor and predict changes in the body temperature of the machine tool 2 along with changes in the room temperature in the factory 1. Therefore, a machining accuracy diagnosis method in which the machining accuracy influence amount prediction unit 14 predicts a change in accuracy of the machine tool 2 and the schedule change unit 15 determines the timing to turn on the power to the air conditioner 3 will be described below using the flowchart in FIG. 2 and the graphs in FIGS. 3 and 4.

[0014] Stage A1: Information on the factory 1 side is acquired (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. The room temperature inside the factory 1 is measured using the current value measured by the room temperature sensor 5 installed inside the factory 1. In this embodiment 1, the temperature outside the factory 1 is measured using the outside temperature sensor 6, but external data such as weather data can also be used. Furthermore, in addition to the current value, forecast values ​​of future changes can also be used as needed. Regarding the information on the power on / off and set temperature of the air conditioner 3, not only current information but also information on future settings from the air conditioner 3 schedule is used as needed.

[0015] Stage A2: Information on the machine tool 2 side is acquired (processing condition acquisition step). The information obtained from the machine tool 2 side includes the current machine temperature, the machining schedule, and the tolerance for accuracy change (allowable accuracy change). The information on the machining schedule and allowable accuracy change is set in advance in the machine tool 2, for example, as shown in Figure 4. First, the required machining accuracy is set for the type of workpiece to be machined and the machining programs prepared according to the machining stage, such as rough machining and finish machining. Furthermore, the time periods during which each machining program is scheduled to be executed are set in the machine tool 2, thereby setting the allowable accuracy change for each time period on the machine tool 2. In the example of Figure 4, the allowable accuracy change is set to 50 μm from 9:00 to 13:00 on Mondays because rough machining is performed, and 10 μm from 13:00 to 19:00 because finish machining is performed.

[0016] Stage A3: Assume that the present is the time to turn on the air conditioner 3 (or change the set temperature). Then, the power-on time is changed between the present and the end of machining, and the calculations of stages A4 to A7 are performed to predict the effect of thermal displacement on machining accuracy. Stage A4: Predict changes in room temperature within factory 1 due to turning air conditioning 3 on and off or changing settings. Predict the change in room temperature in Factory 1 when Air Conditioner 3 is turned off. When Air Conditioner 3 is turned off, the room temperature in Factory 1: θ in is the temperature outside factory 1 as shown in the following equation 1: θ outIt is expressed as a change in first-order lag with the input of Equation 1. Equation 1 is an example of a room temperature change estimation equation (air conditioning power OFF) of the present disclosure.

[0017]

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[0018] On the other hand, when air conditioner 3 is turned on, the room temperature in factory 1 is: θ in is the set temperature of air conditioner 3 as shown in the following equation 2: θ C It is expressed as a change in first-order lag with the input of Equation 2. Equation 2 is an example of a room temperature change estimation equation (air conditioning power ON) of the present disclosure.

[0019]

number

[0020] In Equation 1 and Equation 2, the time constant T off and T on The value of T represents the ability of the room temperature to follow the input temperature, and the smaller the time constant, the faster the change. Normally, the room temperature changes more quickly when air conditioning 3 is ON, so T off ≫T on This value also varies depending on the size of the space in the factory 1, the insulation of the factory 1, the output of the air conditioning 3, etc. If this value is identified in advance, it is possible to predict changes in room temperature. In addition, it is considered that the change in room temperature is affected by the outside temperature even when the air conditioning 3 is ON. In this regard, the predicted value of the change in temperature is taken in, and based on this, the time constant T on For example, when predicting changes when heating is used in winter, the lower the outside temperature, the harder it is for the room temperature to rise. on In the first embodiment, prediction is performed using Equation 1 and Equation 2, but other equations may be used for prediction based on measurement results or the like.

[0021] Step A5: Predict the power consumption of air conditioner 3. For example, the power consumption can be roughly calculated using the following equation 3. The first term in equation 3 is the power consumption required to start up air conditioner 3, and the second term is the power consumption required to maintain a constant room temperature inside factory 1 when it is affected by the temperature outside factory 1.

[0022]

number

[0023] Stage A6: Predict the change in machine tool body temperature and thermal displacement after the air conditioning 3 is turned on. When the room temperature of the environment in which the machine tool 2 is placed changes, the machine body temperature also changes with a delay. The change in machine body temperature at this time can be expressed as a first-order lag response with the room temperature change as input. This response can be found by sequentially calculating using a difference equation such as the following Equation 4. Equation 4 is an example of a machine body temperature change estimation equation disclosed herein.

[0024]

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[0025] Equation 4 is calculated for each machine tool 2 and for each temperature measurement location, and the change in machine body temperature at each part is estimated when the room temperature change predicted by Equations 1 and 2 occurs. Furthermore, the change in accuracy due to thermal displacement of the machine tool 2 is predicted from the estimated change in machine body temperature of the machine tool 2. This change in accuracy can be expressed as a function of machine body temperature, as in Equation 5 below. Hereinafter, this function will be referred to as the accuracy change function of the machine tool 2. The type of function to use as the accuracy change function is determined in advance based on experiments and analysis.

[0026]

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[0027] Specifically, the accuracy change function can be expressed as a linear expression of the temperature of each part of the machine tool 2, for example, as in the following Equation 6.

[0028]

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[0029] In this method, temperature sensors are attached to multiple structures of the machine tool 2, such as the bed, column, and spindle, and the temperatures are multiplied by a preset proportionality constant and added together to estimate the thermal displacement of the machine tool 2. The proportionality constant can be identified by finding the relationship between temperature and thermal displacement through FEM analysis or actual measurement. In this embodiment 1, a machine body temperature sensor 4 is provided on the machine tool 2, and current temperature information is used to predict changes in the temperature of the machine body, but it is not necessary to install a machine body temperature sensor in order to predict changes in the accuracy of the machine tool. Also, equations other than the linear equation shown in Equation 6 can be considered as the accuracy change function of the machine tool. Furthermore, it is also possible to use variables other than the machine body temperature, such as variations in room temperature around the machine.

[0030] Step A7: Predict the change in accuracy of the machine tool 2 while machining the workpiece. By calculating the range of change in the accuracy change function of the machine tool 2 obtained in step A6 during the time period corresponding to the machining schedule set in step A2, it is possible to predict and estimate the change in accuracy of the machine tool 2 while machining each workpiece, as shown in the following equation 7. Equations 5 to 7 are examples of thermal displacement estimation equations disclosed herein, 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 impact on machining accuracy).

[0031]

number

[0032] Step A8: Determine whether calculations have been completed for all power-on times. If the power-on time is equal to the scheduled machining end time, the calculations are completed. 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 in steps A4 to A7 are repeated. Steps A3 to A9 are the machining accuracy influence amount prediction steps of the present disclosure. Step A10: The time when the condition of accuracy change during workpiece processing < tolerance for accuracy change (tolerable accuracy change) is met and the predicted power consumption of air conditioner 3 is at its smallest is determined as the time to turn on air conditioner 3 (schedule change step).

[0033] Figure 3 shows an example of determining the timing to turn on the air conditioner 3 based on the above flow. In this example, when the power to the air conditioner 3 is turned off on Friday night, the best timing to turn on the air conditioner 3 is sought in order to ensure accuracy in the machining that is performed on Monday after the weekend. In this simulation, to make the results easier to understand, the set temperature of the air conditioner θ C is constant at 20℃, and the temperature outside factory 1 is θ out is assumed to be constant at 10°C. Also, the time constant T off = 360 (min), time constant T of room temperature change when air conditioning is ON on = 60 (minutes) and calculations are performed based on Equation 1 and Equation 2. These values ​​are identified in advance through experiments and calculations. When air conditioning 3 is turned off on Friday evening, the temperature in factory 1 drops to θ in The temperature of each part of the machine decreases gradually with a delay from the change in room temperature. m,1 , θ m,2 , θ m,3 The degree of delay from the room temperature change varies depending on the part, and this difference in the degree of delay causes a temperature difference in the machine, which results in thermal displacement. This degree of delay can also be expressed by the time constant shown in Equation 4. In the example of Figure 3, the time constants of the machine temperature change are T m,1 =240(min), T m,2 =180(min), T m,3 = 120 (minutes), and the calculation is based on Equation 4. The value of the time constant of the temperature change of the aircraft is also identified in advance through experiments and calculations.

[0034] On the other hand, when air conditioner 3 is turned on, the room temperature θ in rises to approach the set temperature, and the temperature of the body θ m,1 , θ m,2 , θ m,3also increases. The problem here is that even if the room temperature returns to normal and becomes constant, the temperature of the machine body continues to change, which may cause unstable machining accuracy. For this reason, it is necessary to turn on the power to the air conditioner 3 well in advance before machining begins. Also, the power consumption of the air conditioner 3 is calculated using Equation 3, but in this example, the room temperature when the air conditioner 3 is turned on is 10°C, and the power consumption at start-up is constant regardless of the time it is turned on. Since the outside temperature is also assumed to be constant at 10°C, the calculation shows that the power consumption of the air conditioner 3 increases depending on the time it is turned on. For this reason, it is best to delay the power-on time as much as possible within the range that still satisfies machining accuracy.

[0035] In the example of Figure 4, the allowable accuracy change is set to 50 μm from 9:00 to 13:00 on Mondays for rough machining, and 10 μm from 13:00 to 19:00 for finish machining. Also, in this example, the accuracy change function ΔX m is calculated using the temperatures of the aircraft at three locations using the following equation 8.

[0036]

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[0037] At this time, the accuracy change ΔX of the workpiece is calculated according to the method in the flowchart of Figure 2. w By calculating this, it can be seen that if air conditioning unit 3 is turned on at 3:00 AM on Monday, the change in accuracy for both rough machining and finish machining will be within the allowable range. If air conditioning unit 3 is set to turn on automatically based on the judgment results, air conditioning unit 3 in Factory 1 will turn on automatically at 3:00 AM on Monday before work starts, and machining can begin after work starts with the machine's temperature changes stable. In Equation 5, the accuracy change function is calculated as being simply proportional to the temperature of the aircraft at a certain location, but the accuracy change function formula can be set arbitrarily. For example, formulas based on the room temperature or aircraft temperature variation at multiple locations, or the differential value of temperature change, etc., are also possible.

[0038] As described above, the machining accuracy diagnosis device 10 for the machine tool 2 of the above-mentioned form 1 includes an air conditioning operation pattern setting unit 11 that sets the operation pattern of the air conditioning 3, a machining condition setting unit 12 that sets the scheduled machining start time and scheduled machining end time by the machine tool 2, a room temperature temperature sensor 5 and an outside air temperature temperature sensor 6 that acquire the room temperature inside the factory 1 and the air temperature outside the factory 1 using the air conditioning 3, and a machining accuracy influence amount prediction unit 14 that predicts the amount of influence of the air conditioning 3 on machining accuracy based on the operation pattern of the air conditioning 3 acquired from the air conditioning operation pattern setting unit 11, the scheduled machining start time and scheduled machining end time acquired from the machining condition setting unit 12, the room temperature inside the factory 1 and the air temperature outside the factory 1 acquired from the room temperature sensor 5 and the outside air temperature sensor 6, and the set temperature of the air conditioning 3 acquired from the air conditioning operation pattern setting unit 11, and executes the above-mentioned machining accuracy diagnosis method. According to this configuration, the impact of the air conditioning 3 on processing accuracy can be quantitatively predicted using information such as the operating pattern of the air conditioning 3, the scheduled start and end times of processing, and the room temperature in the factory 1.

[0039] In particular, the system further includes a schedule change unit 15 that changes the operation pattern of the air conditioning 3 set by the air conditioning operation pattern setting unit 11 based on the predicted impact on machining accuracy, so that the operation pattern of the air conditioning 3 for maintaining machining accuracy can be appropriately and easily changed according to the predicted impact on machining accuracy. Furthermore, the schedule change unit 15 changes the operation pattern of the air conditioner 3 based on a comparison between the amount of influence on machining accuracy predicted by the machining accuracy influence amount prediction unit 14 and a preset tolerance for accuracy change during the machining time acquired from the machining condition setting unit 12. Therefore, when machining requiring high precision is scheduled, it is possible to stabilize the temperature of the machine before the start of machining and ensure machining precision by operating the air conditioner 3 in advance. In this case, when no machining requiring high precision is scheduled, it is possible to save energy by turning off the air conditioner 3 or loosening the set temperature range. Furthermore, the schedule change unit 15 predicts the power consumption (energy consumption) of the air conditioner 3 using the room temperature inside the factory 1, the set temperature of the air conditioner 3, and the air temperature outside the factory 1, and changes the operating pattern of the air conditioner 3 so that the condition is met where the amount of impact on processing accuracy is smaller than the tolerance value for accuracy change and the predicted value of the power consumption of the air conditioner 3 is minimized, so that the operating pattern of the air conditioner 3 can be determined so as to save energy consumption while meeting the required accuracy.

[0040] Then, the machining accuracy influence amount prediction unit 14 estimates the room temperature change in factory 1 based on the current room temperature in factory 1 measured by the room temperature sensor 5 and the air temperature outside factory 1 using a preset room temperature change estimation formula within the machining time obtained from the machining condition setting unit 12, and estimates the body temperature change of machine tool 2 using a preset machine body temperature change estimation formula based on the estimated room temperature change in factory 1, and estimates the thermal displacement of machine tool 2 using a preset thermal displacement estimation formula based on the predicted body temperature change of machine tool 2, and calculates the amount of change in thermal displacement within the machining time as the amount of influence on machining accuracy. In other words, the change in room temperature in the factory 1 due to the air conditioning 3 is estimated by calculation using a physical model, and the change in the body temperature of the machine tool 2 is estimated based on that change in room temperature.The thermal displacement of the machine tool 2 is then estimated based on the change in body temperature to determine the amount of impact on machining accuracy, so the impact on actual workpiece accuracy can be accurately estimated. In particular, when estimating room temperature changes using the room temperature change estimation formula, the machining accuracy influence amount prediction unit 14 estimates room temperature changes in the factory 1 using the set temperature of the air conditioner 3 as an input when the air conditioner 3 is turned on, and using the air temperature outside the factory 1 as an input when the air conditioner 3 is turned off, thereby making it possible to accurately predict room temperature changes in the factory 1.

[0041] The second embodiment of the present disclosure will be described below. In the above-described first embodiment, a machining schedule is determined in advance, and a method for turning on the air conditioning 3 in advance to ensure the required accuracy based on that schedule has been described. On the other hand, it is also possible that the time for turning on the air conditioning 3 has already been determined, and the scheduled machining start time is determined based on that. In that case, it is sufficient to determine the time required for the room temperature change to stabilize and for the required accuracy to be ensured. Below, a specific example according to the second configuration of the present disclosure will be described. However, since the configuration of the machining accuracy diagnosis device 10 is the same as that of the above-described first embodiment, a machining accuracy diagnosis method with different processing will be described based on the flowchart of FIG. 5. Stage 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 status 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 process as described in stage A1 of Figure 2. Stage B2: Information on the machine tool 2 side, including the current machine temperature, the machining schedule, and the allowable accuracy change, is acquired (machining condition acquisition step). Regarding the machining schedule, the required machining time is a fixed value because it is determined by the machining, but the scheduled machining start time is undetermined at this point and will be determined after the processing of the later stage B6 is performed. Step B3: Set the time to turn on the air conditioning 3 or change the set temperature. Stage B4: Predict changes in room temperature in the factory 1 due to turning on / off or changing the settings of the air conditioning 3. The calculation method is the same as Stage A4. Step B5: Predict the temperature change and thermal displacement of the machine tool 2 body after powering on the air conditioner 3. The calculation method is the same as in step A6.

[0042] Stage B6: Predict the change in accuracy during workpiece machining when the scheduled start time for workpiece machining is changed. The time required to process the workpiece is constant, so the start time of the workpiece processing t w,start If we shift it later, the workpiece processing end time t w,end In Equation 4, t w,start and t w,end While changing the accuracy change ΔX during workpiece machining wSteps B3 to B6 are the machining accuracy influence amount prediction steps of the present disclosure. Step B7: As a result of the processing in step B6, a scheduled machining start time that satisfies the condition that the change in accuracy during workpiece machining is less than the tolerance for the change in accuracy is displayed (schedule change step). 3 and 4, it can be seen that after the air conditioning 3 is turned on, it takes 10 hours for the temperature change of the machine tool 2 to stabilize and for finish machining to be possible. If this time is displayed on the operation screen of the machine tool 2 as the machining accuracy stabilization time, the operator can determine the machining schedule so that finish machining will be performed after the temperature change of the machine tool 2 has stabilized.

[0043] In this way, in the machining accuracy diagnosis device 10 and machining accuracy diagnosis method of the above-mentioned form 2, the influence of the air conditioning 3 on machining accuracy can be quantitatively predicted using information such as the operation pattern of the air conditioning 3, the scheduled machining start time and scheduled machining end time, and the room temperature in the factory 1. In particular, the system further includes a schedule change unit 15 that changes the planned start time of machining set by the machining condition setting unit 12 based on the predicted impact on machining accuracy, so that the machining schedule for maintaining machining accuracy can be appropriately and easily changed according to the predicted impact on machining accuracy. Furthermore, the schedule change unit 15 changes the scheduled machining start time so that the amount of influence on machining accuracy predicted by the machining accuracy influence amount prediction unit 14 becomes smaller than a preset tolerance value for accuracy change during the machining time acquired from the machining condition setting unit 12. Therefore, by predicting the time until the amount of influence on machining accuracy caused by the air conditioning 3 becomes equal to or less than the tolerance value, it becomes possible to create a machining schedule taking into account the influence on machining accuracy. This is effective when the operation pattern of the air conditioning 3 is determined in advance.

[0044] Below, modifications common to both the first and second embodiments will be described. In the above formulas 1, 2, and 4, the time constant T on , T off , T m,iThese values ​​must be identified in advance when making a prediction. In addition to determining them by calculation from the size of the factory 1, the volume of the machine structure, and the physical properties of the materials, it is also possible to identify the values ​​based on actual measurement results. Using a known parameter search method, the time constant T on , T off , T m,i In this way, by comparing the estimated results with the actual measurement results and correcting the estimation formula, the accuracy of the prediction can be improved. Furthermore, when operating the machining accuracy diagnosis device 10, if the parameters can be identified and updated using information on temperatures actually measured by the room temperature sensor 5 in the factory 1 and the machine body temperature sensor 4 of the machine tool 2, the accuracy of predictions can be further improved.

[0045] Furthermore, in the above-described embodiments 1 and 2, the amount of influence on machining accuracy is calculated by calculating the change in room temperature, the temperature change in machine tool 2, and the thermal displacement of machine tool 2 in that order using equations based on a physical model such as those shown in equations 1 to 5, but calculations based on theoretical equations are not necessarily required when determining 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 using machining time, temperature information, and the like as inputs. Furthermore, in the above-described first and second embodiments, the schedule change unit changes either the air conditioning operation pattern or the scheduled machining start time based on the amount of influence on machining accuracy, but it may also change both. The numbers and arrangements of the machine tool, air conditioner, and temperature sensors are not limited to those of the first and second embodiments. The temperature adjustment means includes not only the air conditioning exemplified in the above-mentioned embodiments 1 and 2, but also a temperature adjustment device that adjusts the temperature by being directly installed on the machine tool body, such as an oil jacket (cooling passage) installed on a column. In this case, the acquired influence temperature is the temperature of the coolant, and the time constant of the machine body temperature change is also the value when the oil jacket is used. "Temperature adjustment" is not limited to cooling, but also includes heating. [Explanation of symbols]

[0046] 1··Factory, 2··Machine tool, 3··Air conditioning, 4··Machine body temperature sensor, 5··Room temperature sensor, 6··Outdoor temperature sensor, 10··Machining accuracy diagnosis device, 11··Air conditioning operation pattern setting unit, 12··Machining condition setting unit, 13··Accuracy change tolerance setting unit, 14··Machining accuracy impact amount prediction unit, 15··Schedule change unit.

Claims

1. A machining accuracy diagnosis device for predicting and diagnosing an effect on machining accuracy when a machine body temperature is changed by a temperature adjustment means that affects the machine body temperature of a machine tool in a factory where the machine tool is installed, comprising: a temperature control operation pattern setting means for setting an operation pattern of the temperature control means; a machining condition setting means for setting at least a scheduled machining start time and a scheduled machining end time for the machine tool; a temperature information acquisition means for acquiring an influence temperature of the temperature adjustment means on the machine temperature and / or an air temperature outside the factory; a machining accuracy influence amount prediction means for predicting an influence amount on the machining accuracy caused by the temperature adjustment means based on three pieces of information: 1) an operation pattern of the temperature adjustment means acquired from the temperature adjustment operation pattern setting means; 2) the scheduled machining start time and the scheduled machining end time acquired from the machining condition setting means; and 3) at least one of the affected temperature and / or the air temperature outside the factory acquired from the temperature information acquisition means and the set temperature of the temperature adjustment means acquired from the temperature adjustment operation pattern setting means; A machining accuracy diagnosis device for a machine tool, comprising:

2. 2. The machining accuracy diagnosis device for a machine tool according to claim 1, further comprising a schedule change means for changing at least one of the operation pattern of the temperature adjustment means set by the temperature adjustment 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.

3. 3. The machining accuracy diagnosis device for a machine tool according to claim 2, wherein the schedule change means changes the operation pattern of the temperature adjustment means based on a comparison between the amount of influence on the machining accuracy predicted by the machining accuracy influence amount prediction means and a preset allowable value of the influence amount during the machining time acquired from the machining condition setting means.

4. 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 air temperature outside the factory; 4. A machining accuracy diagnosis device for a machine tool as described in claim 3, characterized in that the operating pattern of the temperature adjustment means is changed so as to satisfy the condition that the amount of influence on the machining accuracy is smaller than the allowable value and to minimize the energy consumption of the temperature adjustment means.

5. 3. The machining accuracy diagnosis device for a machine tool according to claim 2, wherein the schedule change means changes the scheduled machining start time so that the amount of influence on the machining accuracy predicted by the machining accuracy influence amount prediction means becomes smaller than a preset allowable value of the influence amount during the machining time acquired from the machining condition setting means.

6. the temperature information acquisition means includes a room temperature sensor that measures the room temperature inside the factory, which is the influencing temperature, and an outside temperature sensor that measures the air temperature outside the factory; 6. The machining accuracy diagnosis device for a machine tool according to any one of claims 1 to 5, wherein the machining accuracy influence amount prediction means estimates a change in room temperature in the factory using a preset room temperature change estimation formula based on the current room temperature in the factory measured by the room temperature sensor and the set temperature of the temperature adjustment means or the air temperature outside the factory, during the machining time acquired from the machining condition setting means, estimates a change in machine body temperature of the machine tool using a preset machine body temperature change estimation formula based on the estimated change in room temperature in the factory, and estimates a thermal displacement of the machine tool using a preset thermal displacement estimation formula based on the predicted change in machine body temperature of the machine tool, thereby obtaining an amount of change in the thermal displacement within the machining time as an influence amount on machining accuracy.

7. the temperature adjusting means is an air conditioner installed in the factory, 7. The machining accuracy diagnosis device for machine tools according to claim 6, wherein the machining accuracy influence amount prediction means, when estimating the change in room temperature using the room temperature change estimation formula, estimates the change in room temperature inside the factory using the set temperature of the air conditioning as an input when the air conditioning is turned on, and using the air temperature outside the factory as an input when the air conditioning is turned off.

8. 7. The machining accuracy diagnosis device for a machine tool according to claim 6, wherein 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.

9. 8. The machining accuracy diagnosis device for a machine tool according to claim 7, wherein 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.

10. a machine body temperature sensor for measuring a machine body temperature of the machine tool; 7. The machining accuracy diagnosis device for a machine tool according to claim 6, wherein the machining accuracy influence amount prediction means compares the temperature measured by the machine temperature sensor with the machine temperature estimated by the machine temperature change estimation formula, and corrects the machine temperature change estimation formula.

11. a machine body temperature sensor for measuring a machine body temperature of the machine tool; 8. The machining accuracy diagnosis device for a machine tool according to claim 7, wherein the machining accuracy influence amount prediction means compares the temperature measured by the machine temperature sensor with the machine temperature estimated by the machine temperature change estimation formula, and corrects the machine temperature change estimation formula.

12. a machine body temperature sensor for measuring a machine body temperature of the machine tool; 9. The machining accuracy diagnosis device for a machine tool according to claim 8, wherein the machining accuracy influence amount prediction means compares the temperature measured by the machine temperature sensor with the machine temperature estimated by the machine temperature change estimation formula, and corrects the machine temperature change estimation formula.

13. a machine body temperature sensor for measuring a machine body temperature of the machine tool; 10. The machining accuracy diagnosis device for a machine tool according to claim 9, wherein the machining accuracy influence amount prediction means compares the temperature measured by the machine temperature sensor with the machine temperature estimated by the machine temperature change estimation formula, and corrects the machine temperature change estimation formula.

14. A machining accuracy diagnosis method for predicting and diagnosing an effect on machining accuracy when a machine body temperature is changed by a temperature adjustment means that affects the machine body temperature of a machine tool in a factory where the machine tool is installed, comprising: a temperature control operation pattern acquisition step of acquiring an operation pattern of the temperature adjustment means; a machining condition acquisition step of acquiring at least a scheduled machining start time and a scheduled machining end time for the machine tool; a temperature information acquisition step of acquiring at least one of an influence temperature of the temperature adjustment means on the machine temperature and / or an air temperature outside the factory, and a set temperature of the temperature adjustment means; a machining accuracy influence amount prediction step of predicting an influence amount of the temperature adjustment means on the machining accuracy based on three pieces of information: 1) the acquired operation pattern of the temperature adjustment means; 2) the acquired scheduled machining start time and scheduled machining end time; and 3) at least one of the acquired influence temperature and / or the air temperature outside the factory and the set temperature of the temperature adjustment means; A machining accuracy diagnosis method for a machine tool, comprising:

15. The machining accuracy diagnosis method for a machine tool according to claim 14, further comprising a schedule change step of changing at least one of 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 based on the predicted amount of impact on the machining accuracy.

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