WO2018134903A1 - Parameter value determination method, parameter value determination program, and parameter value determination device - Google Patents

Abstract

In order to reduce the set-up time for a product which outputs a signal, a model setting unit (12) sets a model for estimating a limit (y) of a tolerance range of the signal output of a product to be newly set up, from a product feature quantity of the product and on the basis of data of the combination of a product feature quantity of a previously set up product and a parameter value that was being input to the previously set up product when the previously set up product exhibited a signal output value near a limit of a predetermined tolerance range. Further, on the basis of estimates of changes in the signal output of the product to be newly set up as a function of a parameter value, said changes occurring within the tolerance range of the signal output, a correction value calculation unit (14) calculates a correction value (g) for correcting an estimated limit of the tolerance range of the signal output of the product to be newly set up, so as to maximize the possibility that the signal output of the product will fall within the tolerance range. Further, an initial value determination unit (16) calculates an estimated limit of the tolerance range of the signal output of the product to be newly set up, on the basis of said product feature quantity of the product and said model, and corrects the calculated estimated limit of the tolerance range using said correction value, thereby calculating an initial parameter value to be input to the product.

Description

Parameter value determination method, parameter value determination program, and parameter value determination device

The present invention relates to a parameter value determination method, a parameter value determination program, and a parameter value determination device.

Conventionally, at the time of mass production of products that output signals such as optical transmission devices, the process of setting the parameter value of the firmware that controls the signal output to an appropriate value so that the signal output is within a predetermined allowable range is performed. It has been broken.

On the other hand, Patent Document 1 and the like extract past adjustment targets whose adjustment specifications are the same as or similar to various constants necessary for adjustment of a new adjustment target in order to shorten the adjustment time of the adjustment target (for example, an electric motor drive device). A technique for setting an initial value of adjustment based on the extracted past adjustment target is disclosed.

However, in the case of a product that outputs a signal, the output signal is greatly affected by variations in the element values (individual features) of the devices installed in the product, so the parameter values set in another product in the past are used. It ’s difficult. Therefore, in practice, it is necessary to set an initial value of an appropriate parameter for each apparatus, and while searching for an output signal, search while changing the parameter value so that the output falls within an allowable range.

JP-A-6-339295

When searching for a parameter value of a product that outputs a signal as described above, it takes time M (for example, M = 1 minute) until the signal output is stabilized when the parameter value is changed. For this reason, when the parameter value is changed N times before the signal output enters the allowable range, an adjustment time of M × N or more is required. At present, the adjustment time is about 20 to 30 minutes.

In one aspect, an object of the present invention is to provide a parameter value determination method, a parameter value determination program, and a parameter value determination device that can shorten the adjustment time of a device that performs signal output.

In one aspect, the parameter value determination method is a parameter value determination method for determining a parameter value to be input to an adjustment target device that performs signal output according to the parameter value, and the device that has been an adjustment target in the past New adjustment based on the data of the combination of the parameter value input to the device when the signal output of the device indicates a value in the vicinity of the boundary of the predetermined allowable range and the individual feature amount of the device A model for estimating a parameter value such that the signal output of the target device indicates a value near the boundary of the allowable range from the individual feature amount of the new adjustment target device is set, and the new adjustment target device A correction value for correcting a parameter value estimated using the model so as to make the probability that the signal output of the input signal falls within the allowable range to a predetermined value or more is a parameter predicted within the allowable range. A parameter value is estimated based on the individual feature amount of the new device to be adjusted and the model, and the estimated parameter value is corrected with the correction value. A parameter value determination method in which a computer executes a process of calculating a parameter value to be input to the new device to be adjusted.

The adjustment time of the device that performs signal output can be shortened.

It is a figure showing roughly the composition of the adjustment system concerning one embodiment. It is a figure which shows the hardware constitutions of an adjustment apparatus. It is a functional block diagram of an adjustment apparatus and a product. It is a figure which shows an example of the data structure of log | history DB. It is a figure for demonstrating adjustment of the product of the past adjustment object. It is a figure which shows the example at the time of assuming that the behavior at the time of converging to the boundary of an allowable range is a straight line. It is a figure for demonstrating a prediction error. FIGS. 8A and 8B are diagrams for explaining the probability that the signal output is included in the allowable range when the parameter value is the boundary prediction value. FIG. 9A and FIG. 9B are diagrams for explaining the probability that the signal output is included in the allowable range when the parameter value is corrected with the correction value. It is a figure which shows the example at the time of assuming that the behavior at the time of converging to the boundary of an allowable range is nonlinear.

Hereinafter, an adjustment system according to an embodiment will be described in detail with reference to FIGS.

FIG. 1 schematically shows the configuration of an adjustment system 100 according to the present embodiment. The adjustment system 100 in FIG. 1 includes an adjustment device 10 as a parameter value determination device connected to a product 50 to be adjusted, and a signal detection device 40 that detects a signal output from the product 50. The product 50 to be adjusted is, for example, a device such as an optical transmission device that outputs a signal.

The product 50 includes a signal generator controller 52 and a signal generator 54 as shown in FIG. The signal generator control unit 52 incorporates firmware that causes the signal generator 54 to generate a signal in accordance with the set parameter value. The signal generator 54 generates a signal based on an instruction from the signal generator control unit 52.

The adjustment device 10 searches for a parameter value to be set in the signal generator control unit 52 of the product 50. Specifically, the adjustment device 10 searches for a parameter value that can include the output signal of the product 50 detected by the signal detection device 40 in the allowable range.

FIG. 2 shows the hardware configuration of the adjustment device 10. As shown in FIG. 2, the adjusting device 10 includes a CPU (Central Processing Unit) 90, a ROM (Read Only Memory) 92, a RAM (Random Access Memory) 94, a storage unit (here, HDD (Hard Disk Drive)) 96, An input / output interface 97, a portable storage medium drive 99, and the like are provided. Each component of the adjusting device 10 is connected to a bus 98. In the adjustment device 10, a program (including a parameter value determination program) stored in the ROM 92 or the HDD 96, or a program (including a parameter value determination program) read from the portable storage medium 91 by the portable storage medium drive 99. When executed by the CPU 90, the function of each unit shown in FIG. 3 is realized. FIG. 3 also shows a history DB (database) 22, a model parameter DB 24, a correction value DB 26, and an allowable range DB 28 stored in the HDD 96 of the adjustment apparatus 10.

FIG. 3 shows a functional block diagram of the adjustment device 10 and the product 50. As illustrated in FIG. 3, the adjustment device 10 has functions as a model setting unit 12, a correction value calculation unit 14, an initial value determination unit 16, and a parameter value output unit 18 when the CPU 90 executes a program. ing.

The model setting unit 12 sets a model parameter of a model used for determining an initial value (before correction) of a parameter value to be input to the new product 50 to be adjusted. Specifically, the model setting unit 12 sets model parameters based on adjustment data (final parameter values (final adjustment values) and individual feature values) of adjusted products stored in the history DB 22. Then, the model setting unit 12 stores the set model parameters in the model parameter DB 24. FIG. 4 shows an example of the data structure of the history DB 22. The history DB 22 of FIG. 4 stores individual feature values (X1, X2,...) Of each adjusted product and the final adjustment value (y) of each adjusted product. The individual feature amount is also called an element value. Here, in the present embodiment, in the past adjustment, a predetermined parameter value is set as an initial value, and a signal output is repeated while changing the parameter value every predetermined time as shown in FIG. Then, when the signal output enters the allowable range, the parameter value at that time is stored as the final adjustment value, and the adjustment is terminated. As described above, the adjustment is finished when the signal output enters the allowable range in order to shorten the manufacturing time of the product. Therefore, in the present embodiment, the parameter value when a signal that is just around the allowable range (converged to the boundary of the allowable range) is output is stored in the history DB 22 of FIG. 4 as the final adjustment value. Note that the final adjustment value y varies from product to product as shown in FIG. This variation is caused by differences in individual feature amounts.

The model setting unit 12 is a linear function represented by the following equation (1) based on the individual feature amounts (X1, X2,...) Stored in the history DB 22 and the final adjustment value (y) of each adjusted product. A model constant a ₀ and coefficients a ₁ , a ₂ ,... Are calculated, and the calculation result is stored as a model parameter in the model parameter DB 24.
y = a ₀ + a ₁ × X1 + a ₂ × X2 + (1)

By substituting the individual feature amount (X1, X2,...) Of the new product 50 to be adjusted into the above equation (1), the output signal of the product 50 is most likely to show a value just below the allowable range. A high parameter value y can be determined. Hereinafter, the parameter value y is also referred to as “boundary prediction value”.

The correction value calculation unit 14 calculates a correction value for correcting the parameter value (boundary prediction value) y obtained using the model set by the model setting unit 12 based on the data of the history DB 22. As described above, the boundary prediction value y is a parameter value with the highest possibility that the output signal of the product 50 indicates a value that is just below the allowable range. Therefore, the correction value calculation unit 14 calculates a correction value g for correcting the boundary prediction value y to a parameter value that is most likely to include the signal output within the allowable range. Here, the corrected parameter value y ₀ can be expressed as y ₀ = y + g. The correction value calculation unit 14 stores the calculated correction value g in the correction value DB 26.

The details of the method for calculating the correction value g by the correction value calculation unit 14 will be described later.

The initial value determination unit 16 reads out the model parameters of the model set by the model setting unit 12 from the model parameter DB 24 and reads out the correction values calculated by the correction value calculation unit 14 from the correction value DB 26. Then, the initial value determination unit 16 calculates the boundary predicted value y of the product 50 using the read model parameter and the above equation (1), and corrects the boundary predicted value y with the correction value g to obtain the product 50. An initial value y ₀ of a parameter value suitable for setting to is calculated. The initial value determination unit 16 transmits the determined initial value y ₀ of the parameter value to the parameter value output unit 18. The initial value determination unit 16 can acquire the individual feature amount of the product 50 when the product 50 is connected to the adjustment device 10. The initial value determination unit 16 calculates the initial value of the parameter value based on the model acquisition unit that acquires the model from the model parameter DB 24, the correction value acquisition unit that acquires the correction value from the correction value DB 26, and the model and the correction value. It functions as a calculation unit.

The parameter value output unit 18 outputs the initial value of the parameter value received from the initial value determination unit 16 to the signal generator control unit 52 of the product 50. Further, it is determined whether or not the value of the output signal from the product 50 detected by the signal detection device 40 is within the allowable range stored in the allowable range DB 28. If the value is not within the allowable range, The parameter value is changed and output to the signal generator controller 52 again. The tolerance range DB 28 stores values indicating the tolerance range ([z ₀ , z ₁ ] in the example of FIG. 7).

In the present embodiment, as described above, the initial value determination unit 16 uses the model set by the model setting unit 12 and the correction value g calculated by the correction value calculation unit 14 to adjust the product 50 to be adjusted. Initial values of parameter values for adjustment are determined. In this case, the initial value of the determined parameter value is most likely to be included in the allowable range. For this reason, the parameter value output unit 18 outputs the determined initial value of the parameter value to the product 50, whereby the time for searching for the parameter value included in the allowable range can be shortened. Thereby, the product 50 can be adjusted in a short time.

Next, a correction value calculation method by the correction value calculation unit 14 of the adjustment device 10 of the present embodiment will be described in detail.

In this embodiment, it is assumed that a curve (convergence curve) indicating the relationship between the signal output and the parameter value in the vicinity of the allowable range has linearity. That is, the behavior within the allowable range is predicted by assuming that the behavior when converged to the boundary of the allowable range is a straight line as shown in FIG. In FIG. 6, the behavior within the allowable range can be expressed by the following equation (2).
z = c ₁ × y + c ₂ (2)

Here, c ₁ means sensitivity (predicted value) to the parameter value, and c ₂ means a constant (intercept).

Here, the sensitivity c ₁ has a prediction error, and the boundary prediction value y calculated using the above-described equation (1) also has a prediction error. FIG. 7 shows each prediction error. Each prediction error is assumed to have a normal distribution as shown in FIG. In this case, when the behavior of the new product 50 to be adjusted is estimated using the model of Expression (1), a prediction error indicated by hatching occurs.

In the present embodiment, the correction value calculation unit 14 calculates a correction value g for calculating a value y ₀ that maximizes the probability that the signal output is included in the allowable range.

More specifically, the signal output z is defined by assuming that the prediction error of the parameter value (boundary prediction value) y that converges to the boundary of the allowable range is σ _e ² , the average of the sensitivity c ₁ is c _ave , and the sensitivity prediction error is σ _c ^2. The existence probability of the product 50 to be adjusted with respect to is expressed as a function of the correction value g. Then, a correction value g that maximizes the probability of entering the allowable range is calculated. FIG. 8B is a diagram showing the probability that the signal output is included in the allowable range as the area of the hatched range when the parameter value is the boundary predicted value as shown in FIG. 8A. . 9B shows a hatched range of the probability that the signal output is included in the allowable range when the parameter value is shifted from the boundary predicted value by the correction value g as shown in FIG. 9A. It is a figure shown as an area. Here, the existence probability of the product 50 can be represented by an area of a normal distribution as shown in FIGS. 8B and 9B. In the present embodiment, the correction value g is calculated so that the area indicating the existence probability of the product 50 within the allowable range is maximized. Here, the allowable range is [z ₀ , z ₁ ].

In this case, assuming that c ₁ to N (c _ave , σ _c ² ) and Δz = z ₁ −z ₀ , the average E [Δz] and variance Var [Δz] of Δz are expressed by the following equations (3), (4 ).

Then, g can be obtained by substituting the above equations (3) and (4) into the following equation (5).

In the present embodiment, the correction value calculation unit 14 can calculate the correction value g that can maximize the possibility that the signal output is included in the allowable range by solving the above equation (5).

(Modification)
In the example described above, the curve (convergence curve) indicating the relationship between the signal output near the allowable range and the parameter value is assumed to be linear, but may be assumed to be nonlinear. Assuming non-linearity, as shown in FIG. 10, it is assumed that the above-mentioned linearity is approximated by using the slope of the convergence curve z = f (y) in the boundary predicted value μ _y of the product 50 to be newly adjusted. The method of the case may be used.

Specifically, the following equation (6) in μ _y is approximated with respect to z = f (y).

Then, the average value c _ave of c ₁ and the variance σ _c ² in the above equation (6) are obtained, and the correction value g may be obtained using the above-described linear method.

(How to find the average c _ave and variance σ _c ² (when the convergence curve is a quadratic polynomial))
Here, when the convergence curve is a quadratic polynomial, the average c _{ave of} c ₁ and the variance σ _c ² can be obtained as follows.

The two-dimensional polynomial is z = f (y) = ay ² + by + c, the parameters (a, b, c) have already been estimated, and the mean μ _a , μ _b , variances σ _a ² , σ _b ² are known. Suppose there is. In this case, when f (y; θ) is differentiated by y, f ′ (y) = ay + b. Therefore, the average c _{ave of} c ₁ and the variance σ _c ² can be obtained from the following equations (7) and (8). Note that μ _y is the average of y.

(How to find the average c _ave and variance σ _c ² (when the convergence curve is a high-dimensional polynomial))
When the convergence curve is a high-dimensional polynomial, the average c _{ave of} c ₁ and the variance σ _c ² can be obtained as follows.

The parameter of the function f (y) of the high-dimensional polynomial is θ, and the average μ _θ and the variance σ _θ ² of _θ are estimated from the following equation (9) using neighboring data.
f (y; θ) = Σ _n θ _n y ⁿ (9)

Also, f (y; θ) is differentiated by y to calculate f ′ (y; θ). In this case, f ′ (y; θ) is expressed as a polynomial Σ _n nθ _n y ^{n−1 of} y.

In this case, the average c _{ave of} c ₁ can be expressed by the following equation (10).
c _ave = E [f ′ (μ _y ; θ)] = Σ _n nE [θ _n y ^n-1 ] (10)

In this case, assuming the independence of θ and y,
E [θ _n y ^n-1 ] = E [θ _n ] E [y ^n-1 ] = μθ _n E [y ^n-1 ] (11)
It becomes.

Here, y ^n-1 is expanded to the second order with μ _y , and the average E [y ^n-1 ] is approximated with μ _y , σ _e ² (Delta Method). It becomes like this.

Also, E in order to determine the [y ^n-1], y a ^n-1 and Talor deployed around the mu _y, variance of ^{y n-1 (Var (y} n-1)) and μ _y, σ _e ² Is approximated by the following equation (13).

Using the above equations (12) and (13), the mean and variance of the power expression of an arbitrary random variable can be obtained.

Since σ _c ² can also be expressed as a polynomial in y, it can be expressed as in the following equation (14) using μ _y and σ _e ² in the same manner as described above. Note that θ _n and θ _k (n ≠ k) are independent.

Note that the average and variance of the power representation of θ _n can also be calculated in the same manner as the above equations (12) and (13).

(How to find average c _ave and variance σ _c ² (when the convergence curve is a non-polynomial nonlinear curve))
Even when the convergence curve is a non-polynomial curve, it can be expanded into a polynomial expression by Taylor expansion and applied to the above-described method. For example, expression of the convergence curve is, in the case of f (y) = Ae ^ay, may be handled as a polynomial by Taylor expansion by the following equation (15).

As described above in detail, according to the present embodiment, the model setting unit 12 indicates that the signal output of the product that has been subject to adjustment in the past indicates a value near the boundary of a predetermined allowable range. Based on the combination data (history DB 22 data) of the parameter value input to the product and the individual feature amount, the boundary prediction value y of the new adjustment target product 50 is estimated from the individual feature amount. The model is set, and the correction value calculation unit 14 sets the correction value g for correcting the boundary prediction value y in order to maximize the probability that the signal output of the product 50 falls within the allowable range. Is calculated based on the change in signal output with respect to. Then, the initial value determination unit 16 calculates (estimates) the boundary predicted value y based on the individual feature amount and the model of the product 50, and corrects the calculated boundary predicted value y with the correction value g, whereby the product 50 The initial value y ₀ of the parameter value input to is calculated. Thus, even if there is only a parameter value when the output signal indicates a value near the boundary of the allowable range as data of the product adjusted in the past, the parameter to be input to the new product 50 to be adjusted As an initial value, a parameter value having the maximum probability that the signal output falls within the allowable range can be calculated. Therefore, since the time for searching for the parameter value within the allowable range of the signal output in the product 50 can be shortened, the adjustment time of the product 50 can be shortened. Thereby, manufacturing lead time can be shortened and production efficiency can be improved. Further, since the number of products that can be adjusted can be increased without increasing the number of adjusting devices 10, it is possible to reduce the cost.

In the present embodiment, it is assumed that the change in the signal output with respect to the parameter value predicted within the allowable range is a linear change or a non-linear change, and the correction value calculation unit 14 responds to the change in the signal output. Since the correction value is calculated by the method, an appropriate value corresponding to the behavior within the allowable range can be calculated as the correction value.

In the present embodiment, the correction value calculation unit 14 calculates the correction value by linear approximation when the change in the signal output with respect to the parameter value shows a non-linear change within the allowable range. Thereby, the correction value can be calculated by a simple calculation.

In the present embodiment, the correction value calculation unit 14 calculates the correction value based on the boundary prediction value error (variance) σ _e ² and the sensitivity prediction error (variance) σ _c ^2. An appropriate correction value can be calculated in consideration of the above.

In the above-described embodiment, the correction value calculation unit 14 has described the case where the correction value g is calculated to maximize the probability that the signal output of the product 50 falls within the allowable range. However, the present invention is not limited to this. is not. For example, the correction value calculation unit 14 may calculate a correction value g that has a probability equal to or higher than a predetermined value.

The model setting unit 12 and the correction value calculating unit 14 may execute (update) model setting and correction value calculation every predetermined period, or each time a predetermined number of data is newly added to the history DB 22. It may be executed.

In the above embodiment, the adjustment device 10 has the model setting unit 12 and the correction value calculation unit 14. However, the present invention is not limited to this, and the model setting unit 12 and the correction value calculation unit 14 may be provided by different devices. You may have. That is, the setting of the model and the calculation of the correction value may be performed by another device, and the adjustment device 10 may acquire the model and the correction value from the other device. The separate device may be a device directly connected to the adjustment device 10 or may be a server (cloud server) connected via a network.

Note that the above processing functions can be realized by a computer. In that case, a program describing the processing contents of the functions that the processing apparatus should have is provided. By executing the program on a computer, the above processing functions are realized on the computer. The program describing the processing contents can be recorded on a computer-readable recording medium (except for a carrier wave).

When the program is distributed, for example, it is sold in the form of a portable recording medium such as a DVD (Digital Versatile Disc) or CD-ROM (Compact Disc Read Only Memory) on which the program is recorded. It is also possible to store the program in a storage device of a server computer and transfer the program from the server computer to another computer via a network.

The computer that executes the program stores, for example, the program recorded on the portable recording medium or the program transferred from the server computer in its own storage device. Then, the computer reads the program from its own storage device and executes processing according to the program. The computer can also read the program directly from the portable recording medium and execute processing according to the program. Further, each time the program is transferred from the server computer, the computer can sequentially execute processing according to the received program.

The above-described embodiment is an example of a preferred embodiment of the present invention. However, the present invention is not limited to this, and various modifications can be made without departing from the scope of the present invention.

10 Adjustment device (parameter value determination device)
12 Model setting unit 14 Correction value calculation unit 16 Initial value setting unit (model acquisition unit, correction value acquisition unit, calculation unit)

Claims (13)

A parameter value determination method for determining a parameter value to be input to an apparatus to be adjusted that performs signal output according to a parameter value,
The combination of the parameter value input to the device when the signal output of the device to be adjusted in the past shows a value near the boundary of a predetermined allowable range and the individual feature amount of the device Based on the data, a model is set for estimating a parameter value from the individual feature amount of the new adjustment target device such that the signal output of the new adjustment target device indicates a value near the boundary of the allowable range. ,
A parameter value that is predicted within the allowable range is a correction value that corrects the parameter value estimated using the model in order to make the probability that the signal output of the new device to be adjusted falls within the allowable range. Based on the change in signal output with respect to
A parameter value is estimated based on the individual feature amount of the new adjustment target device and the model, and the parameter value input to the new adjustment target device is corrected by the correction value. To calculate,
A parameter value determination method, wherein a computer executes the process. 2. The parameter value determination according to claim 1, wherein in the process of calculating the correction value, a correction value that maximizes a probability that a signal output of the new device to be adjusted falls within the allowable range is calculated. Method. Assuming that the change in signal output with respect to the parameter value predicted within the tolerance is a linear change or a non-linear change;
3. The parameter value determination method according to claim 1, wherein, in the process of calculating the correction value, the correction value is calculated by a method according to a change in the signal output. When the change in the signal output with respect to the parameter value predicted within the allowable range is a non-linear change,
The parameter value determination method according to claim 3, wherein in the process of calculating the correction value, the correction value is calculated by linearly approximating the nonlinear change. In the process of calculating the correction value, the correction value is calculated based on the estimation error of the parameter value estimated using the model and the prediction error of the change in the signal output with respect to the parameter value predicted within the allowable range. 5. The parameter value determining method according to claim 1, wherein the parameter value is calculated. A parameter value determination program for determining a parameter value to be input to an apparatus to be adjusted that performs signal output according to a parameter value,
The combination of the parameter value input to the device when the signal output of the device to be adjusted in the past shows a value near the boundary of a predetermined allowable range and the individual feature amount of the device Based on the data, a model is set for estimating a parameter value from the individual feature amount of the new adjustment target device such that the signal output of the new adjustment target device indicates a value near the boundary of the allowable range. ,
A parameter value that is predicted within the allowable range is a correction value that corrects the parameter value estimated using the model in order to make the probability that the signal output of the new device to be adjusted falls within the allowable range. Based on the change in signal output with respect to
A parameter value is estimated based on the individual feature amount of the new adjustment target device and the model, and the parameter value input to the new adjustment target device is corrected by the correction value. To calculate,
A parameter value determination program which causes a computer to execute processing. A parameter value determination device that determines a parameter value to be input to an adjustment target device that performs signal output according to a parameter value,
The combination of the parameter value input to the device when the signal output of the device to be adjusted in the past shows a value near the boundary of a predetermined allowable range and the individual feature amount of the device A model for estimating a parameter value set based on data so that a signal output of a new adjustment target device indicates a value in the vicinity of the boundary of the allowable range from an individual feature amount of the new adjustment target device. A model acquisition unit to acquire;
Using the model in order to make the probability that the signal output of the new device to be adjusted falls within the allowable range, calculated based on the change in the signal output with respect to the parameter value predicted within the allowable range A correction value acquisition unit for acquiring a correction value for correcting the estimated parameter value;
A parameter value is estimated based on the individual feature amount of the new adjustment target device and the model, and the parameter value input to the new adjustment target device is corrected by the correction value. A calculation unit for calculating
A parameter value determination device comprising: The parameter value determining device according to claim 7, further comprising a model setting unit for setting the model. The parameter value determination device according to claim 7 or 8, further comprising a correction value calculation unit that calculates the correction value. 10. The parameter value determination device according to claim 9, wherein the correction value calculation unit calculates a correction value that maximizes a probability that a signal output of the new device to be adjusted falls within the allowable range. The correction value calculation unit assumes that the change in the signal output with respect to the parameter value predicted within the allowable range is a linear change or a non-linear change, and performs the correction in a method according to the change in the signal output. The parameter value determination apparatus according to claim 9 or 10, wherein a value is calculated. When the change in the signal output with respect to the parameter value predicted within the allowable range is a non-linear change,
The parameter value determining apparatus according to claim 11, wherein the correction value calculating unit calculates the correction value by linearly approximating the nonlinear change. The correction value calculation unit calculates the correction value based on an estimation error of a parameter value estimated using the model and a prediction error of a change in signal output with respect to a parameter value predicted within the allowable range. The parameter value determination device according to any one of claims 9 to 12, wherein

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