Failure prediction system and failure prediction method

Abstract

To provide a malfunction predicting technology with an excellent prediction precision for the malfunction of a device.SOLUTION: A malfunction predicting system 1 executes malfunction prediction on a device 10 that repeats operation multiple times, and includes: an operation time detecting unit 21 that detects, for each operation, an operation time t necessary for the device 10 from an activation to a deactivation; a transition information deriving unit 22 that derives transition information I on the operation time t from an arbitrary n-th operation of the device 10 to an (n+2)-th operation thereof based on the operation time t detected by the operation time detecting unit 21; and a malfunction predicting unit 23 that predicts such that the malfunction occurring time period of the device 10 comes soon when it is determined that, based on the transition information I derived by the transition information deriving unit 22, the operation time t continuously increases from the n-th operation to the (n+2)-th operation.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a technique for predicting equipment failure. [Background technology]

[0002] Vehicle production facilities use a large number of devices that operate repeatedly. Therefore, failure of each device can cause the production facility to shut down for an extended period of time. For example, Patent Document 1 listed below discloses an equipment failure diagnosis method for managing equipment failures. This equipment failure diagnosis method is a technology that, when the occurrence of a failure is determined based on the operating status of one cycle of the equipment, identifies and displays the device involved in the equipment failure. This equipment failure diagnosis method can reduce the effort required to discover the failure. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 5-189026 Summary of the Invention [Problem to be solved by the invention]

[0004] To avoid prolonged downtime of production equipment, technology is required to identify and address abnormalities before equipment failure occurs. However, the above-mentioned equipment failure diagnosis method is a technology that identifies equipment that has already failed, but does not identify abnormalities before the equipment fails, making it difficult to adopt as a solution to the above-mentioned problem. Furthermore, even if maintenance is performed on each piece of equipment in advance and an upper limit on the cumulative operating time thereafter is set to guarantee operation, failures of each piece of equipment can occur regardless of the period up until the cumulative operating time reaches the upper limit, so this does not provide a fundamental solution to the problem of equipment management.

[0005] The present invention has been made in view of the above-mentioned problems, and aims to provide a failure prediction technique that has excellent accuracy in predicting equipment failures. [Means for solving the problem]

[0006] One aspect of the present invention is A failure prediction system for predicting failures of equipment that repeats multiple operations, an operation time detection unit that detects an operation time required from start to stop of the device for each operation; a transition information deriving unit that derives transition information of the operation time of the device from an arbitrary nth operation to an (n+2)th operation based on the operation time detected by the operation time detecting unit; a failure prediction unit that predicts that a failure of the device is imminent when it is determined that the operating time has increased continuously from the nth time to the (n+2)th time based on the transition information derived by the transition information derivation unit; and Equipped with picture, the transition information derivation unit is configured to derive, as the transition information, a scatter plot having a horizontal axis representing the number of times the device is operated and a vertical axis representing a cumulative operation time, which is a cumulative value of the operation time; The failure prediction unit is configured to predict that a failure of the device is approaching when three points of data from the nth time to the (n+2)th time of the cumulative operating time are connected by an ascending curve in the scatter diagram derived by the transition information derivation unit. Failure prediction systems, is located. Another aspect of the present invention is A failure prediction system for predicting failures of equipment that repeats multiple operations, an operation time detection unit that detects an operation time required from start to stop of the device for each operation; a transition information deriving unit that derives transition information of the operation time of the device from an arbitrary nth operation to an (n+2)th operation based on the operation time detected by the operation time detecting unit; a failure prediction unit that predicts that a failure of the device is imminent when it is determined that the operating time has increased continuously from the nth time to the (n+2)th time based on the transition information derived by the transition information derivation unit; and Equipped with the transition information derivation unit is configured to derive, as the transition information, a scatter plot having a horizontal axis representing the number of times the device is operated and a vertical axis representing a cumulative operation time, which is a cumulative value of the operation time; the failure prediction unit is configured to predict that a failure of the device is approaching when three points of data from the nth time to the (n+2)th time of the cumulative operating time are connected by an ascending curve in the scatter diagram derived by the transition information derivation unit, and when the (n+3)th time of the cumulative operating time, which is estimated to be on an extension of the ascending curve, exceeds a predetermined upper control limit value; is located.

[0007] Another aspect of the present invention is a method for producing a semiconductor device comprising: A failure prediction method for predicting failure of equipment that repeats multiple operations, comprising: an operation time detection step of detecting an operation time required from start to stop of the device by an operation time detection unit every time; a transition information deriving step of deriving transition information of the operation time of the device from an arbitrary nth operation to an (n+2)th operation by a transition information deriving unit based on the operation time detected in the operation time detecting step; a failure prediction step of predicting, by a failure prediction unit, that a time when a failure of the device is imminent when it is determined that the operating time has increased continuously from the nth time to the (n+2)th time based on the transition information derived in the transition information derivation step; With death, In the transition information deriving step, a scatter plot is derived as the transition information, with the horizontal axis representing the number of times the device is operated and the vertical axis representing the cumulative operation time, which is the cumulative value of the operation time; In the failure prediction step, it is predicted that a failure of the device is approaching when three points of data from the nth time to the (n+2)th time of the cumulative operating time are connected by an ascending curve in the scatter diagram derived in the transition information derivation step. Failure prediction methods, is located. Another aspect of the present invention is a method for producing a semiconductor device comprising: A failure prediction method for predicting failure of equipment that repeats multiple operations, comprising: an operation time detection step of detecting an operation time required from start to stop of the device by an operation time detection unit every time; a transition information deriving step of deriving transition information of the operation time of the device from an arbitrary nth operation to an (n+2)th operation by a transition information deriving unit based on the operation time detected in the operation time detecting step; a failure prediction step of predicting, by a failure prediction unit, that a time when a failure of the device is imminent when it is determined that the operating time has increased continuously from the nth time to the (n+2)th time based on the transition information derived in the transition information derivation step; and In the transition information deriving step, a scatter plot is derived as the transition information, with the horizontal axis representing the number of times the device is operated and the vertical axis representing the cumulative operation time, which is the cumulative value of the operation time; a failure prediction method in which, in the failure prediction step, three points of data from the nth time to the (n+2)th time of the cumulative operating time are connected by an ascending curve in the scatter diagram derived in the transition information derivation step, and it is predicted that a failure of the device is approaching when the cumulative operating time of the (n+3)th time, which is estimated to be on an extension of the ascending curve, exceeds a predetermined upper control limit value; is located.

[0008] In each of the above-described aspects, the operating time of a device that repeatedly operates multiple times is detected for each cycle. Based on the detected operating time, transition information on the operating time of the device from an arbitrary nth to (n+2)th operation is derived. Then, based on the derived transition information, it is determined that the operating time has increased three consecutive times from the nth to (n+2)th operation, and it is predicted that the device is nearing a failure. This allows the occurrence of a device failure to be predicted by comparing the transitions in the operating time of the device for the most recent three consecutive operations, enabling highly accurate failure prediction without relying on the guaranteed upper limit value in the device specifications or the guaranteed upper limit value set during device maintenance. As a result, an abnormality can be addressed before a device failure occurs, and long-term downtimes of production facilities equipped with multiple devices can be reduced.

[0009] As described above, according to the above-described aspects, it is possible to provide a failure prediction technology that has excellent accuracy in predicting equipment failures. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a configuration diagram of a failure prediction system according to a first embodiment. [Figure 2] 2 is a diagram for explaining the concept of failure prediction processing in the failure prediction unit in FIG. 1; [Figure 3] FIG. 3 is a partially enlarged view of FIG. 2. [Figure 4] FIG. 2 is a flowchart showing a failure prediction method according to the first embodiment. [Figure 5] FIG. 10 is a diagram corresponding to FIG. 2 for the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Preferred embodiments of the above aspects are described below.

[0012] In the failure prediction system of the above aspect, it is preferable that the transition information derivation unit is configured to derive, as the transition information, a scatter plot with the horizontal axis representing the number of times the device is operated and the vertical axis representing cumulative operation time, which is the cumulative value of the operation time, and the failure prediction unit is configured to predict that a failure of the device is approaching when three points of data from the nth operation to the (n+2)th operation of the cumulative operation time are connected by an ascending curve in the scatter plot derived by the transition information derivation unit.

[0013] This failure prediction system uses a scatter diagram derived from the operating time of the equipment to predict equipment failure based on the relationship between three-point data and an ascending curve from the nth to the (n+2)th cumulative operating time.

[0014] In the failure prediction system of the above aspect, it is preferable that the transition information derivation unit is configured to derive, as the transition information, a scatter diagram with the horizontal axis representing the number of times the device is operated and the vertical axis representing cumulative operation time, which is the cumulative value of the operation time, and the failure prediction unit is configured to predict that a failure of the device is approaching when, in the scatter diagram derived by the transition information derivation unit, three points of data for the cumulative operation time from the nth operation to the (n+2)th operation are connected by an ascending curve, and the cumulative operation time of the (n+3)th operation, which is estimated to be on an extension of the ascending curve, exceeds a predetermined upper control limit value.

[0015] According to this failure prediction system, in addition to the last three consecutive operating conditions of the equipment, the upper management limit value can also be reflected in the failure prediction, thereby improving the accuracy of failure prediction compared to analysis based only on the last three consecutive operating conditions of the equipment.

[0016] In the failure prediction system of the above aspect, the ascending curve preferably constitutes a quadratic curve or an approximation curve that is approximated by a quadratic curve.

[0017] According to this failure prediction system, by making the ascending curve a relatively simple quadratic curve or an approximation thereof, it is possible to simplify the process of determining whether or not the three-point data from the nth cumulative operating time to the (n+2)th cumulative operating time are connected by an ascending curve.

[0018] The failure prediction system of the above aspect preferably includes a notification output unit that notifies a user of the prediction result by the failure prediction unit.

[0019] This failure prediction system can quickly notify users at the production facility site that a device is about to fail.

[0020] In the failure prediction method of the above aspect, in the transition information derivation step, it is preferable that a scatter plot with the number of times the device is operated on the horizontal axis and the cumulative operation time, which is the cumulative value of the operation time, on the vertical axis is derived as the transition information, and in the failure prediction step, it is predicted that the time when a failure of the device will occur is approaching when three points of data from the nth operation to the (n+2)th operation of the cumulative operation time are connected by an ascending curve in the scatter plot derived in the transition information derivation step.

[0021] According to this failure prediction method, equipment failure can be predicted based on the relationship between three points of data from the nth to the (n+2)th cumulative operating time in the scatter diagram and the ascending curve.

[0022] In the failure prediction method of the above aspect, in the transition information derivation step, a scatter plot with the horizontal axis representing the number of times the device is operated and the vertical axis representing cumulative operation time, which is the cumulative value of the operation time, is derived as the transition information, and in the failure prediction step, it is preferable that when three points of data for the cumulative operation time from the nth operation to the (n+2)th operation are connected by an ascending curve in the scatter plot derived in the transition information derivation step, and when the cumulative operation time of the (n+3)th operation, which is estimated to be on an extension of the ascending curve, exceeds a predetermined upper control limit value, the timing of occurrence of a failure of the device is approaching.

[0023] According to this failure prediction method, in addition to the last three consecutive operating conditions of the equipment, the upper management limit value can also be reflected in the failure prediction, thereby improving the accuracy of failure prediction compared to analysis based only on the last three consecutive operating conditions of the equipment.

[0024] In the failure prediction method of the above aspect, the ascending curve preferably constitutes a quadratic curve or an approximation curve that is approximated by a quadratic curve.

[0025] According to this failure prediction method, by making the ascending curve a relatively simple quadratic curve or an approximation thereof, it is possible to simplify the process of determining whether or not the three-point data from the nth cumulative operating time to the (n+2)th cumulative operating time are connected by an ascending curve.

[0026] The failure prediction method of the above aspect preferably includes a notification output step of outputting a notification of the prediction result of the failure prediction step to a user by a notification output unit.

[0027] According to this failure prediction method, it is possible to quickly notify users at the production facility site that a failure of the equipment is imminent.

[0028] Hereinafter, an embodiment for realizing a technology for predicting failures in equipment that repeats multiple operations will be described with reference to the drawings.

[0029] (Embodiment 1) As shown in FIG. 1, the failure prediction system 1 according to the first embodiment is installed in a vehicle production facility, and includes a control panel 11, a data server 14, and a facility management device 20.

[0030] Each control panel 11 is electrically connected to the device 10 to be controlled. Typical examples of the device 10 include operating devices such as motors and cylinders. The control panel 11 is equipped with multiple sensors 12 that detect the start and stop of the device 10. Data D from the multiple sensors 12 is measured by an input / output time measuring instrument 13 (hereinafter simply referred to as the "measuring instrument 13"). The data D measured by the measuring instrument 13 is transmitted to and stored in a data server 14. This data D includes sensor information that can identify the actual start and stop timing of the device 10 (e.g., the output time of an input signal from the sensor 12 to the device 10, the detection time of an output signal from the device 10 to the sensor 12, the ON time and OFF time of each sensor 12, etc.). The data D stored in the data server 14 is transmitted to an equipment management device 20 via a wireless or wired communication line NT.

[0031] The equipment management device 20 is a computer device having a known CPU (Central Processing Unit), ROM, RAM, an interface for inputting and outputting data to and from external devices, etc. This equipment management device 20 is preferably configured as a desktop or notebook personal computer (PC), a tablet terminal, a mobile terminal, etc.

[0032] The equipment management device 20 performs the essential function of the failure prediction system 1, that is, the function of predicting failures of the equipment 10 that repeats multiple operations, based on the data D measured by the measuring instrument 13. The equipment management device 20 includes an operation time detection unit 21, a transition information derivation unit 22, a failure prediction unit 23, and a notification output unit 24.

[0033] The measuring instrument 13 measures information regarding the operation time t required from start to stop of the device 10 for each operation. Here, "one time" can also be referred to as "one cycle." The operation time t at this time is detected by the operation time detection unit 21 performing arithmetic processing using the above-mentioned data D. That is, the operation time detection unit 21 is configured to detect the operation time t required from start to stop of the device 10 for each operation in cooperation with the measuring instrument 13. The transition information derivation unit 22 is configured to derive transition information It (scatter diagram S described later) of the operation time t. The failure prediction unit 23 is configured to predict that a failure of the device 10 is imminent based on a predetermined determination result described later. The notification output unit 24 is configured to output a notification of the prediction result by the failure prediction unit 23 to a user.

[0034] Next, specific processing contents by the equipment management device 20 will be described with reference to Figures 2 to 4. The failure prediction method of embodiment 1 is a method for predicting failure of the device 10, and is made possible by sequentially executing the steps from the first step S101 to the fourth step S104 in Figure 4. In this embodiment, it is preferable that the equipment management device 20 executes all of these steps.

[0035] The operation time detection unit 21 detects the operation time t of the device 10 in a first step S101 (operation time detection step) in Fig. 4. Subsequently, the transition information derivation unit 22 derives transition information It of any three consecutive operation times t based on the operation time t detected by the operation time detection unit 21 in a second step S102 (transition information derivation step) in Fig. 4. The transition information derivation unit 22 derives a scatter diagram S (see Fig. 2) as transition information It of any nth to (n+2)th operation times t of the device 10. Then, the failure prediction unit 23 performs failure prediction processing using the scatter diagram S in a third step S103 (failure prediction step) in Fig. 4.

[0036] Here, the scatter diagram S in Fig. 2 will be described. This scatter diagram S has the number of activations N of the device 10 on the horizontal axis and the cumulative activation time T, which is the cumulative value of the activation time t, on the vertical axis. In this scatter diagram S, the intervals between the number of activations N on the horizontal axis are constant. In this embodiment, a scatter diagram S is shown which shows the correlation between the number of activations N and the cumulative activation time T for the number of activations N from the (n-1)th to the (n+3)th activation of the device 10.

[0037] In this scatter diagram S, when the device 10 is operating normally without any abnormalities, the cumulative operating time T of each operation, except for the initial state until the moving parts (not shown) of the device 10 are adjusted, forms a reference line Lr, which is a straight line that slopes upward to the right. In other words, the operating time t of the device 10 is roughly constant for all operations. However, when an abnormality begins to occur in the device 10, the increase in the cumulative operating time T until the next operation (i.e., the actual operating time t) increases. In this case, the time difference between the previous and next cumulative operating times T exceeds the normal time difference ΔT. In FIG. 2, the time difference A between the cumulative operating time T(n+1) and the cumulative operating time T(n), and the time difference B between the cumulative operating time T(n+2) and the cumulative operating time T(n+1) both exceed the normal time difference ΔT.

[0038] The failure prediction process by the failure prediction unit 23 is a process of predicting that the time when a failure of the device 10 will occur is approaching when it is determined that the operation time t has increased three consecutive times from the nth time to the (n+2)th time based on the scatter diagram S in Fig. 2. Specifically, the determination that the operation time t has increased consecutively is made based on whether or not three points of data from the nth time to the (n+2)th time of the cumulative operation time T are connected by an ascending curve L in the scatter diagram S. Then, when these three points of data are connected by the ascending curve L, it is predicted that the time when a failure of the device 10 will occur is approaching, and when this is not the case, it is predicted that the device 10 will not immediately fail.

[0039] The "rising curve L" referred to here is a curve that is substantially convex downward in the range from the nth to the (n+2)th plot and whose differential coefficient (the slope of the tangent at each plot point) is always positive. In this case, the differential coefficient may be constant or not. This rising curve L is typically preferably a quadratic curve with a positive coefficient or an approximation curve that is approximated by this quadratic curve. By making the rising curve L a relatively simple quadratic curve or its approximation curve, it is possible to simplify the process of determining whether the above three data points are connected by the rising curve L. However, the rising curve L is not limited to a quadratic curve or its approximation curve, and other curves may be applied as needed.

[0040] When the above three data points are connected by such an ascending curve L, it is estimated that the (n+3)th cumulative operating time T(n+3) is plotted on an extension of this ascending curve L (i.e., on the curve indicated by the two-dot chain line in FIG. 2) (see the square plot in FIG. 2). Therefore, there is a high possibility that the cumulative operating time T will increase significantly in the (n+3)th operation and exceed the predetermined upper limit control value UL. The upper limit control value UL is typically the guaranteed upper limit value in the specifications of the device 10 or the guaranteed upper limit value set during maintenance of the device 10. Therefore, if the cumulative operating time T exceeds the upper limit control value UL, there is a high possibility that the device 10 will actually malfunction.

[0041] Therefore, in this embodiment, a failure prediction of the device 10 is performed based on the relationship between the above three data points and the ascending curve L, and when the above three data points are connected by the ascending curve L, it is predicted that a failure of the device 10 is imminent. Then, predictions are continued with the cumulative operating time T of the most recent three consecutive times as one set. This makes it possible to constantly analyze the operating status of the device 10 for the most recent three consecutive times and reflect the analysis results in the failure prediction of the device 10 without using the upper control limit value UL.

[0042] Alternatively, the three data points may be connected by an ascending curve L, and when the time difference between the (n+3)th cumulative operating time T(n+3) and the (n+2)th cumulative operating time T(n+2), which are estimated to be on an extension of the ascending curve L, is twice or more the time difference B (see FIG. 2), it may be predicted that a failure of the device 10 is imminent. This is effective in improving the accuracy of failure prediction of the device 10.

[0043] Alternatively, when the three data points are connected by an ascending curve L and the (n+3)-th cumulative operating time T(n+3), which is estimated to be on an extension of the ascending curve L, exceeds the upper control limit UL, it may be predicted that a failure of the device 10 is imminent. This allows the failure prediction to reflect not only the most recent three consecutive operating states of the device 10, but also the upper control limit UL. In this case, the accuracy of the failure prediction can be improved compared to an analysis based only on the most recent three consecutive operating states of the device 10.

[0044] In contrast, as shown in Figure 3, which is a part of Figure 2, examples in which the above three data points are not connected by an ascending curve L include, for example, a first comparative example in which they are connected by a straight line La, a second comparative example in which they are connected by a curve Lb, and a third comparative example in which they are connected by a curve Lc.

[0045] In the first comparative example, although the cumulative operating time T increases three consecutive times from the nth to the (n+2)th time, the three data points are connected by a straight line La, which is essentially different from the increasing curve L of the present embodiment. The operating time T is constant from the nth to the (n+2)th time. In this case, the rate of increase of the cumulative operating time T changes around the nth time and increases after the nth time, but the rate of increase remains constant from the nth to the (n+2)th time, so it cannot be said that the device 10 is unequivocally in an abnormal state.

[0046] In the second comparative example, the curve Lb is an upwardly convex curve and does not correspond to the ascending curve L of the present embodiment. In the third comparative example, the curve Lc is a downwardly convex curve like the ascending curve L, but the differential coefficient of the curve Lc (the slope of the tangent at each plot point) is negative in the range from the nth to the (n+1)th time, and therefore it is differentiated from the ascending curve L of the present embodiment.

[0047] Although not specifically shown, it is preferable that the determination of whether the above three data points are connected by an ascending curve L in the scatter diagram S is performed automatically using a known program or an AI model (trained model) based on artificial intelligence that is pre-installed in the equipment management device 20. Alternatively or additionally, the user may visually check the scatter diagram S and make the determination directly.

[0048] 4 (notification output step), the notification output unit 24 outputs a notification of the prediction result by the failure prediction unit 23. The "notification output" here broadly encompasses various output forms such as screen display output, audio output, alarm output, and printout output. This makes it possible to quickly notify a user at the production facility site that a failure of the device 10 is imminent.

[0049] Next, the effects of the above-described first embodiment will be described.

[0050] In the first embodiment, the operation time t of the device 10, which repeats multiple operations, is detected for each operation. Furthermore, based on the detected operation time t, transition information It of the operation time t of the device 10 from an arbitrary nth operation to an (n+2)th operation is derived. Then, based on the derived transition information It (scatter plot S), it is determined that the operation time t has increased three consecutive times from the nth operation to the (n+2)th operation, and it is predicted that a failure of the device 10 is imminent. This allows the occurrence of a failure of the device 10 to be predicted by comparing the transitions of the operation time t of the device 10 for the most recent three consecutive operations, thereby enabling highly accurate failure prediction without relying on the guaranteed upper limit UL in the device 10 specifications or the guaranteed upper limit UL set during device maintenance. As a result, an abnormality can be addressed before a failure occurs in the device 10, and long-term shutdowns of production facilities equipped with multiple devices 10 can be reduced.

[0051] Furthermore, if the transitions in the operation time t for two consecutive times are compared, it is difficult to determine whether the abnormality is due to an error or a fluctuation, and if the transitions in the operation time t for four or more consecutive times are compared, the cumulative operation time T will have risen significantly, and there is a high possibility that the device 10 has already reached a breakdown. For this reason, neither of these measures is effective in detecting an abnormality before the device 10 breaks down.

[0052] As described above, according to the first embodiment, it is possible to provide the failure prediction system 1 and failure prediction method that are excellent in the accuracy of predicting equipment failures.

[0053] Hereinafter, other embodiments related to the above-described embodiment 1 will be described with reference to the drawings. In these embodiments, the same elements as those in embodiment 1 are denoted by the same reference numerals, and the description of these same elements will be omitted.

[0054] (Embodiment 2) The failure prediction system and failure prediction method of the second embodiment are basically the same as those of the first embodiment. However, as shown in Fig. 5, the scatter diagram S' derived by the transition information derivation unit 22 as the transition information It (see Fig. 1) is different from the scatter diagram S (see Fig. 2) of the first embodiment.

[0055] The scatter diagram S' has the number of activations N of the device 10 on the horizontal axis and the activation time t on the vertical axis. In this scatter diagram S', the intervals between the number of activations N on the horizontal axis are constant. In this embodiment, the scatter diagram S' shows the correlation between the number of activations N and the cumulative activations t for the number of activations N of the device 10 from the (n-1)th to the (n+3)th activations.

[0056] In this scatter diagram S', when the device 10 is operating normally without any abnormalities, the operation time t of the device 10 is roughly constant for all times, and connecting the operation times t of each time forms a horizontal reference line Mr. However, when abnormalities begin to occur in the device 10, the actual operation time t required increases. In this case, the time difference between the previous and next operation times t becomes a positive value. In Figure 2, the time difference A between operation times t(n+1) and t(n), and the time difference B between operation times t(n+2) and t(n+1) are both positive values.

[0057] The failure prediction process by the failure prediction unit 23 (see FIG. 1) is a process of predicting that a failure of the device 10 is imminent when it is determined that the operation time t has increased three consecutive times, from the nth operation to the (n+2)th operation, based on the scatter diagram S' in FIG. 5. The determination that the operation time t has increased consecutively is made, specifically, by checking whether or not three points of data from the nth operation to the (n+2)th operation t are connected by an ascending curve M in the scatter diagram S'. Then, when these three points of data are connected by an ascending curve M, it is predicted that a failure of the device 10 is imminent, and when this is not the case, it is predicted that the device 10 will not immediately fail.

[0058] The "rising curve M" here refers to a curve that is substantially convex downward in the range from the nth to the (n+2)th operation, and whose differential coefficient (the slope of the tangent at each point) is always positive, similar to the rising curve L in embodiment 1. When the above three data points are connected by such a rising curve M, it is estimated that the (n+3)th operation time t(n+3) is plotted on an extension of this rising curve M (i.e., on the curve indicated by the two-dot chain line in Figure 5) (see the square plot in Figure 5).

[0059] In this embodiment, as in the first embodiment, when the three data points are connected by an ascending curve M, it is predicted that the device 10 is about to experience a failure. Alternatively, when the three data points are connected by an ascending curve M and the time difference between the (n+3)th cumulative operation time T(n+3) and the (n+2)th cumulative operation time T(n+2), which are estimated to be on an extension of the ascending curve M, is equal to or greater than twice the time difference B (see FIG. 5 ), it may be predicted that the device 10 is about to experience a failure. Alternatively, when the three data points are connected by an ascending curve M and the (n+3)th cumulative operation time T(n+3), which is estimated to be on an extension of the ascending curve M, exceeds the upper limit control value UL, it may be predicted that the device 10 is about to experience a failure.

[0060] The other configurations and methods are the same as those of the first embodiment.

[0061] According to the second embodiment, a scatter diagram S' derived from the operating time of the device 10 can be used to predict failure of the device 10 based on the relationship between three-point data and the ascending curve M from the nth to the (n+2)th operating time t.

[0062] In addition, the same effects as those of the first embodiment are achieved.

[0063] The present invention is not limited to the above-described embodiments, and various applications and modifications are possible without departing from the scope of the present invention. For example, the following embodiments can be implemented by applying the above-described embodiments.

[0064] In the above embodiment, an example is given of the case where the prediction result by the failure prediction unit 23 (failure prediction step) is output to the user by the notification output unit 24 (notification output step), but instead, the prediction result may simply be output as data.

[0065] In the above-described embodiment, the failure prediction system 1 and failure prediction used in vehicle production facilities are exemplified, but the type of production facility is not particularly limited, and it goes without saying that these technologies can be applied to equipment failure prediction technologies in production facilities other than vehicles. [Explanation of symbols]

[0066] 1. Failure prediction system 10 equipment 21 Operation time detection unit 22 Transition information derivation part 23 Failure Prediction Department 24 Notification output unit t,t(n-1),t(n),t(n+1),t(n+2),t(n+3) Operating time It operation time transition information L rising curve N operation times S,S' Scatter Plot (Transition Information) S101 Operation time detection step S102 Transition information derivation step S103 Failure prediction step S104 Notification output step T,T(n-1),T(n),T(n+1),T(n+2),T(n+3) Cumulative operating time UL upper control limit

Claims

1. A failure prediction system for predicting failures of equipment that repeats multiple operations, an operation time detection unit that detects an operation time required from start to stop of the device for each operation; a transition information deriving unit that derives transition information of the operation time of the device from an arbitrary nth operation to an (n+2)th operation based on the operation time detected by the operation time detecting unit; a failure prediction unit that predicts that a failure of the device is imminent when it is determined that the operating time has increased continuously from the nth time to the (n+2)th time based on the transition information derived by the transition information derivation unit; Equipped with the transition information derivation unit is configured to derive, as the transition information, a scatter plot having a horizontal axis representing the number of times the device is operated and a vertical axis representing a cumulative operation time, which is a cumulative value of the operation time; the failure prediction unit is configured to predict that a failure of the equipment is imminent when three points of data from the nth to the (n+2)th cumulative operating time are connected by an ascending curve in the scatter diagram derived by the transition information derivation unit.

2. A failure prediction system for predicting failures in equipment that repeats multiple operations, an operation time detection unit that detects an operation time required from start to stop of the device for each operation; a transition information deriving unit that derives transition information of the operation time of the device from an arbitrary nth operation to an (n+2)th operation based on the operation time detected by the operation time detecting unit; a failure prediction unit that predicts that a failure of the device is imminent when it is determined that the operating time has increased continuously from the nth time to the (n+2)th time based on the transition information derived by the transition information derivation unit; Equipped with the transition information derivation unit is configured to derive, as the transition information, a scatter plot having a horizontal axis representing the number of times the device is operated and a vertical axis representing a cumulative operation time, which is a cumulative value of the operation time; The failure prediction unit is configured to predict that a failure of the equipment is imminent when three points of data from the nth to the (n+2)th cumulative operating time are connected by an ascending curve in the scatter diagram derived by the transition information derivation unit, and when the (n+3)th cumulative operating time, which is estimated to be on an extension of the ascending curve, exceeds a predetermined upper control limit value.

3. 3. The failure prediction system according to claim 1, wherein the ascending curve is a quadratic curve or an approximation curve that is approximated by a quadratic curve.

4. 3. The failure prediction system according to claim 1, further comprising a notification output unit that notifies a user of the prediction result by said failure prediction unit.

5. A failure prediction method for predicting failure of equipment that repeats multiple operations, comprising: an operation time detection step of detecting an operation time required from start to stop of the device by an operation time detection unit every time; a transition information deriving step of deriving transition information of the operation time of the device from an arbitrary nth operation to an (n+2)th operation by a transition information deriving unit based on the operation time detected in the operation time detecting step; a failure prediction step of predicting, by a failure prediction unit, that a time when a failure of the device is imminent when it is determined that the operating time has increased continuously from the nth time to the (n+2)th time based on the transition information derived in the transition information derivation step; and In the transition information deriving step, a scatter plot is derived as the transition information, with the horizontal axis representing the number of times the device is operated and the vertical axis representing the cumulative operation time, which is the cumulative value of the operation time; In the failure prediction step, when three data points from the nth to the (n+2)th cumulative operating time are connected by an ascending curve in the scatter diagram derived in the transition information derivation step, it is predicted that a failure of the equipment is imminent.

6. A failure prediction method for predicting failure of equipment that repeats multiple operations, comprising: an operation time detection step of detecting an operation time required from start to stop of the device by an operation time detection unit every time; a transition information deriving step of deriving transition information of the operation time of the device from an arbitrary nth operation to an (n+2)th operation by a transition information deriving unit based on the operation time detected in the operation time detecting step; a failure prediction step of predicting, by a failure prediction unit, that a time when a failure of the device is imminent when it is determined that the operating time has increased continuously from the nth time to the (n+2)th time based on the transition information derived in the transition information derivation step; and In the transition information deriving step, a scatter plot is derived as the transition information, with the horizontal axis representing the number of times the device is operated and the vertical axis representing the cumulative operation time, which is the cumulative value of the operation time; In the failure prediction step, when three points of data from the nth to the (n+2)th cumulative operating time are connected by an ascending curve in the scatter diagram derived in the transition information derivation step, and the cumulative operating time of the (n+3)th cumulative operating time, which is estimated to be on an extension of the ascending curve, exceeds a predetermined upper control limit value, it is predicted that a failure of the equipment is imminent.

7. 7. The failure prediction method according to claim 5, wherein the ascending curve is a quadratic curve or an approximation curve that is approximated by a quadratic curve.

8. 7. The failure prediction method according to claim 5, further comprising a notification output step of outputting a notification of the prediction result from said failure prediction step to a user by a notification output unit.

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