JP2024073187A - Inspection method for press button, production method for electronic apparatus, and program - Google Patents

Abstract

To provide an inspection method for a press button in which determination accuracy can be enhanced, a production method for an electronic apparatus, and a program.SOLUTION: An inspection method comprises: a step for acquiring load waveform data which indicates a relationship between a stroke position of a press button and a depression load; a step for determining whether the press button is in a normal state, on the basis of the load waveform data; and a step for notifying a user of abnormality of the press button when the press button is in an abnormal state. The step for determining whether the press button is in the normal state or abnormal state, includes: inputting the load waveform data as input waveform data, to an auto encoder which has been pre-trained using previously acquired pieces of load waveform data from a plurality of normal press buttons as training data, to acquire output waveform data output from the auto encoder; and determining whether the press button is in the normal state or abnormal state, on the basis of a difference between the input waveform data and the output waveform data.SELECTED DRAWING: Figure 4

Description

This disclosure relates to a method for inspecting push buttons, a method for manufacturing electronic devices, and a program.

Keyboards of electronic devices such as PCs or keys of electronic musical instruments are provided with push buttons that users can press with their hands to operate them. When manufacturing electronic devices or electronic musical instruments, the keystroke feel felt by the user when pressing the push button may be inspected to determine whether the keyboard or key is of good quality. Automating the inspection of push buttons is also being considered.

For example, Patent Document 1 describes a tactile inspection method that uses data that a person judges to be normal as a standard, and uses the degree of deviation from the operating force that can be placed at a stroke position with the tactile characteristics of the standard as a judgment index to determine the degree of agreement.

JP 2006-292454 A

The tactile inspection method described in Patent Document 1 leaves room for improvement in terms of accuracy.

This disclosure provides a push button inspection method, an electronic device manufacturing method, and a program with improved judgment accuracy.

A method for inspecting a push button according to one aspect of the present disclosure includes:
A method for inspecting a push button, comprising the steps of:
acquiring load waveform data indicating a relationship between a stroke position of the push button and the pressing load;
determining whether the push button is normal or abnormal based on the load waveform data;
If the push button is abnormal, notifying the user that the push button is abnormal;
Including,
The step of determining whether the push button is normal or abnormal includes:
inputting the load waveform data as input waveform data into an autoencoder that has been previously trained using the load waveform data of a plurality of normal push buttons that have been previously acquired as training data, and acquiring output waveform data that is output from the autoencoder;
determining whether the push button is normal or abnormal based on a difference between the input waveform data and the output waveform data;
including.

A method for manufacturing an electronic device according to one aspect of the present disclosure,
A method for manufacturing an electronic device, comprising:
providing an input device including a plurality of push buttons;
testing the push buttons of each of the input devices using the testing method described above;
attaching the input device, the plurality of push buttons of which have been determined to be normal in the inspecting step, to the electronic device;
including.

A program according to one aspect of the present disclosure includes:
The above-mentioned inspection method is executed by a computer.

The present disclosure provides a push button inspection method, an electronic device manufacturing method, and a program with improved judgment accuracy.

FIG. 1 is a block diagram showing an overview of an inspection system for carrying out an inspection method according to a first embodiment. Graph showing a sample load waveform FIG. 1 is a block diagram showing a schematic configuration of an autoencoder according to an embodiment of the present invention. 1 is a flowchart for explaining an inspection method according to a first embodiment. Graph showing an example of input waveform data and output waveform data Graph showing the difference between the input waveform data value and the output waveform data value at each stroke position in the data of FIG. 5A. Graph showing another example of input waveform data and output waveform data. Graph showing the difference between the input waveform data value and the output waveform data value at each stroke position in the data of FIG. 6A . Graph showing another example of input waveform data and output waveform data. Graph showing the difference between the input waveform data value and the output waveform data value at each stroke position in the data of FIG. 7A Graph showing another example of input waveform data and output waveform data. Graph showing the difference between the input waveform data value and the output waveform data value at each stroke position in the data of FIG. 8A . Graph showing another example of input waveform data and output waveform data. Graph showing the difference between the input waveform data value and the output waveform data value at each stroke position in the data of FIG. 9A . FIG. 13 is a diagram showing an example of an electronic device manufactured by the manufacturing method according to the second embodiment; A flowchart for explaining a method of manufacturing an electronic device according to a second embodiment.

(Background to this disclosure)
Electronic devices such as PCs use input devices such as keyboards and mice. Keyboards and mice are equipped with push buttons that allow a user to input data to the electronic device by pressing them with their fingers. By inspecting the feel of the push buttons when pressed, it is possible to determine whether the keyboard or mouse is a good product or a defective product.

Conventionally, to determine whether a keyboard or mouse is a good product, a sensory inspection is performed in which an inspector presses a push button to check for the presence of abnormalities. In addition, as in the inspection method of Patent Document 1, a tactile inspection method has been proposed in which data obtained when a switch is pressed and judged to be normal by a person is used as a standard, and the degree of deviation from the operating force at a stroke position with a characteristic tactile feel of the standard is used as a judgment index to indicate the degree of agreement.

However, conventional sensory inspections by inspectors are dependent on the skills of the inspectors, leading to a problem of large variability in judgment results. In addition, the tactile inspection method described in Patent Document 1 has the problem that although the measurement result data falls within the range of reference data values, it is difficult to detect data that includes abnormalities that would result in a defective product. As a result, there is an issue that it is not possible to improve the accuracy of judgments as to whether or not a product is passable.

The inventor(s) therefore devised a push button inspection method, electronic device manufacturing method, and program with improved judgment accuracy, resulting in the following invention.

(Embodiment 1)
[overall structure]
FIG. 1 is a block diagram showing an outline of an inspection system 1 for carrying out an inspection method according to a first embodiment.

The inspection system 1 is a system for inspecting keyboard keys (hereinafter referred to as push buttons) used in PCs, mouse buttons used in PCs, or keys of electronic musical instruments. In this embodiment, inspecting push buttons means obtaining the load relative to the stroke position when the push button is pressed, and judging whether the push button is normal or abnormal based on the obtained load.

As shown in FIG. 1, the inspection system 1 includes, for example, an actuator 2, a sensor 3, a control unit 4, and a notification unit 5. The configuration of the inspection system 1 is not limited to these, and some components may be omitted, or additional components may be included.

Actuator 2 is used to press the push button during testing.

The sensor 3 detects the load when the push button is pressed by the actuator 2. In this embodiment, the load refers to the magnitude of the force required to press the push button. The magnitude of the force required to press the push button is hereafter referred to as the "pressing load." The sensor 3 outputs the detected pressing load as analog data, or converts it to digital data by an A/D converter (not shown), to the control unit 4.

The control unit 4 acquires load waveform data based on the pressing load detected by the sensor 3, and determines whether the push button is normal or abnormal based on the load waveform data.

The control unit 4 can be realized using semiconductor elements, and can be configured with various processors such as a microcomputer, CPU, MPU, GPU, DSP, FPGA, ASIC, etc. The control unit 4 can also realize predetermined functions by reading data and programs stored in a recording medium (not shown) and performing various arithmetic processing.

The control unit 4 includes, for example, a calculation unit 6 that acquires load waveform data, and an autoencoder 7 that outputs output waveform data when the load waveform data acquired by the calculation unit 6 is input as input waveform data.

The calculation unit 6 acquires load waveform data generated based on the pressing load detected by the sensor 3. When the pressing load from the sensor 3 is analog data, the calculation unit 6 acquires the load waveform data by accepting the analog input and converting it to digital data by an A/D converter (not shown). Figure 2 is a graph showing a sample of a load waveform. When a push button on a keyboard is pressed, the magnitude of the pressing load changes as the key sinks, i.e., as the stroke position becomes deeper. The load waveform shown in Figure 2 is a graph showing the relationship between the stroke of the push button and the pressing load. The calculation unit 6 calculates the load waveform data for generating a load waveform based on the load detected by the sensor 3.

As shown in Figure 2, the pressing load increases as the stroke deepens up to stroke position st1, and indicates a peak load. After that, from stroke position st1 to stroke position st2, the pressing load decreases as the stroke deepens, and indicates a return load at stroke position st2. As the stroke deepens further, the pressing load starts to rise again and becomes larger until it reaches the deepest position of the stroke (stroke position st3). The load waveform of a push button such as a keyboard key generally forms a curve like the one shown in Figure 2.

The calculation unit 6 calculates the load waveform data represented as a graph shown in FIG. 2 based on the pressing load detected by the sensor 3 as described above. In this embodiment, the load waveform data refers to data showing the relationship between the stroke position of the push button and the pressing load at each stroke position. For ease of explanation, the load waveform data will be described using the load waveform shown in FIG. 2. Note that the load waveform data can be a collection of discrete values represented by multiple stroke positions and a load value for each stroke position.

Figure 3 is a block diagram showing a schematic configuration of the autoencoder 7 of this embodiment. As shown in Figure 3, the autoencoder 7 receives the load waveform data calculated by the calculation unit 6 as input waveform data, and outputs output waveform data.

The autoencoder 7 is trained in advance with load waveform data of multiple normal push buttons acquired in advance as training data. In other words, the autoencoder 7 is a machine learning model that is trained unsupervised using load waveform data of normal push buttons. It is advisable to train the autoencoder 7 in advance with load waveform data of, for example, approximately 200 normal push buttons. In general, a large amount of data must be trained to build a machine learning model. The inventors have confirmed that by using the autoencoder 7, normality/abnormality can be accurately determined, as described below, even when training is performed with a very small amount of load waveform data.

The input waveform data input to the autoencoder 7 is composed of a multidimensional column vector arranged in a time series. The autoencoder 7 includes an encoder 71 and a decoder 72. The encoder 71 and the decoder 72 are each composed of a neural network having multiple intermediate layers. In the encoder 71, the number of output nodes is smaller than the number of input nodes. Therefore, the encoder 71 performs dimensional compression of the input waveform data to generate compressed data. In the decoder 72, the number of output nodes is larger than the number of input nodes, and the number of output nodes is the same as the number of dimensions of the column vector of the input waveform data. Therefore, when the decoder 72 receives the compressed data output from the encoder 71, it performs dimensional restoration to generate output waveform data with the same number of dimensions as the input waveform data. In the neural networks of the encoder 71 and the decoder 72, learning is performed so that the output waveform data outputs the same value as the input waveform data.

When normal input waveform data is input to a trained autoencoder 7, normal output waveform data is output from the autoencoder 7. That is, the input waveform data and output waveform data for the autoencoder 7 match. On the other hand, even if abnormal (abnormal) input waveform data is input to the autoencoder 7, normal output waveform data is output from the autoencoder 7. Since only normal input waveform data is used when the autoencoder 7 is trained, when abnormal input waveform data is input, output waveform data that has been changed to normal waveform data is output. In other words, if there is an abnormality in the input waveform data, an error occurs between the input waveform data and the output waveform data.

The calculation unit 6 compares the input waveform data to the autoencoder 7 with the output waveform data from the autoencoder 7, and calculates the difference between the value of the input waveform data and the value of the output waveform data at each stroke position included in the waveform data. If the absolute value of the difference between the value of the input waveform data and the value of the output waveform data at any stroke position is greater than a predetermined threshold, the calculation unit 6 can determine that the input load waveform data is abnormal. This is because, if the absolute value of the difference between the value of the input waveform data and the value of the output waveform data is greater than a predetermined threshold, a deviation has occurred between the input waveform data and the output waveform data, and therefore it can be estimated that the input load waveform data was abnormal.

The control unit 4 outputs the result of the determination of whether the push button is normal or abnormal to the notification unit 5. For example, if the push button is determined to be abnormal, the notification unit 5 can notify the user of the abnormality.

The notification unit 5 may be, for example, a device capable of displaying images, such as a liquid crystal display or an organic EL display. Alternatively, the notification unit 5 may be a speaker or the like capable of notifying the user of an abnormality by voice.

[Inspection method]
Next, a description will be given of a method for inspecting a push button in the inspection system 1. Fig. 4 is a flowchart for explaining the inspection method according to the first embodiment.

First, in step S11, the control unit 4 acquires load waveform data. The pressing load when the push button to be inspected is pressed is detected by the sensor 3, and the calculation unit 6 of the control unit 4 acquires the load waveform data based on the detected pressing load. The calculation unit 6 may acquire the load waveform data based on the pressing load of the push button measured in advance, or may acquire the load waveform data using the pressing load measured in real time.

In step S12, the calculation unit 6 inputs the acquired load waveform data to the autoencoder 7 as input waveform data. In step S13, the autoencoder 7 generates and outputs output waveform data by compressing and restoring the input waveform data. In step S14, the calculation unit 6 calculates the difference between the input waveform data and the output waveform data at each stroke position included in the waveform data, and calculates the difference between the value of the input waveform data and the value of the output waveform data at each stroke position.

Figure 5A is a graph showing an example of input waveform data and output waveform data. In Figure 5A, the curve shown by the solid line is the input waveform data, and the curve shown by the dashed line is the output waveform data. Note that in the example of Figure 5A, the curve shown by the input waveform data and the curve shown by the output waveform data roughly match. Figure 5B is a graph showing the difference between the values of the input waveform data and the output waveform data at each stroke position in the data of Figure 5A. The dashed line in Figure 5B indicates a predetermined threshold value, which in the example of Figure 5B is 0.05 N.

In step S14, the calculation unit 6 determines whether the push button being inspected is normal or abnormal based on the difference between the input waveform data and the output waveform data at each stroke position of the push button. In this embodiment, the difference between the input waveform data and the output waveform data indicates the absolute value of the difference between the value of the input waveform data and the value of the output waveform data. More specifically, in this embodiment, the calculation unit 6 calculates the absolute value of the difference between the value of the input waveform data and the value of the output waveform data at each scroll position of the push button. The calculation unit 6 determines that the push button is abnormal if the absolute value of the difference exceeds a predetermined threshold, and determines that the push button is normal if the absolute value of the difference is equal to or less than the predetermined threshold.

As described above, in the example of FIG. 5A, the curve indicated by the input waveform data and the curve indicated by the output waveform data are roughly the same. When input waveform data such as that of FIG. 5A is shown, as shown in FIG. 5B, the absolute value of the difference is less than a predetermined threshold value (0.05 N) at all stroke positions. Therefore, the calculation unit 6 determines that the push button indicating this waveform data is normal.

Figure 6A is a graph showing another example of input waveform data and output waveform data. Figure 6B is a graph showing the difference between the value of the input waveform data and the value of the output waveform data at each stroke position in the data of Figure 6A. In Figure 6A, there is a portion where the input waveform data and the output waveform data deviate from each other between the stroke position of about 1.2 mm and about 1.7 mm. In other words, there is a portion where the input waveform data and the output waveform data do not clearly overlap between the stroke position of about 1.2 mm and about 1.7 mm. As shown in Figure 6B, the absolute value of the difference between the value of the input waveform data and the value of the output waveform data is a maximum of about 0.07 N between the stroke position of about 1.2 mm and about 1.7 mm, exceeding the threshold value of 0.05 mm. Therefore, the calculation unit 6 determines that the push button showing this waveform data is abnormal.

When input waveform data such as that shown in Figure 6A is displayed, an abnormal noise occurs when the push button is pressed. When inspecting such a defect in a noisy factory or the like, it is difficult for an inspector to determine that it is abnormal. However, when the push button is inspected using the inspection method of this embodiment, it can be accurately determined that it is abnormal.

Figure 7A is a graph showing another example of input waveform data and output waveform data. Figure 7B is a graph showing the difference between the value of the input waveform data and the value of the output waveform data at each stroke position in the data of Figure 7A. In Figure 7A, the stroke position is approximately 0.3 mm, and there is a protruding portion in the input waveform data. As shown in Figure 7B, at the stroke position of approximately 0.3 mm, the absolute value of the difference between the value of the input waveform data and the value of the output waveform data is approximately 0.06 N, which exceeds the threshold value of 0.05 mm. Therefore, the calculation unit 6 determines that the push button showing this waveform data is abnormal.

When input waveform data such as that shown in Figure 7A is displayed, there is an odd sensation when pressing the push button. It is difficult for an inspector to determine that such a defect is abnormal during continuous work. When the push button is inspected using the inspection method of this embodiment, it can be accurately determined that it is abnormal.

Figure 8A is a graph showing another example of input waveform data and output waveform data. Figure 8B is a graph showing the difference between the values of the input waveform data and the output waveform data at each stroke position in the data of Figure 8A. In Figure 8A, when looking at only the input waveform data, it is close to normal waveform data, but when the input waveform data and the output waveform data are compared, it can be seen that there are many parts where the input waveform data and the output waveform data do not overlap, and the difference is large over the entire stroke. As shown in Figure 8B, the absolute value of the difference between the values of the input waveform data and the output waveform data exceeds the threshold value of 0.05 N in parts over the entire stroke, and is a maximum of 0.20 N. Therefore, the calculation unit 6 determines that the push button showing this waveform data is abnormal.

When input waveform data such as that shown in Figure 8A is displayed, the drop load of the push button (see Figure 2) is smaller than that of a normal push button, and the push button feels heavier when pressed than a normal push button.

Figure 9A is a graph showing another example of input waveform data and output waveform data. Figure 9B is a graph showing the difference between the input waveform data value and the output waveform data value at each stroke position in the data of Figure 9A. In Figure 9A, the stroke position is about 1.0 mm, and there is a protruding portion in the input waveform data. Also, in Figure 9A, there is a large deviation between the input waveform data and the output waveform data. As shown in Figure 9B, there are portions over the entire stroke where the absolute value of the difference between the input waveform data value and the output waveform data value exceeds the threshold value of 0.05 N, and in particular, at a stroke position of about 1.0 mm, the absolute value of the difference is about 0.3 N, which is larger than other portions. Therefore, the calculation unit 6 determines that the push button showing this waveform data is abnormal.

As described above, in step S14 of FIG. 4, the calculation unit 6 determines whether the push button is normal or abnormal based on the input waveform data and output waveform data shown in FIG. 5A to FIG. 9A.

If the calculation unit 6 determines in step S14 that the push button is normal, the inspection process ends. If the calculation unit 6 determines in step S14 that the push button is abnormal, the process proceeds to step S15, where the calculation unit 6 outputs a notification of the abnormality to the notification unit 5, and the inspection process ends.

[effect]
According to the above-mentioned embodiment, it is possible to provide a method for inspecting a push button with improved judgment accuracy. In the above-mentioned embodiment, the autoencoder is trained in advance using the load waveform data of a normal push button. When the trained autoencoder receives the load waveform data of a normal push button, it outputs the input waveform data as is, and when the trained autoencoder receives the load waveform data of an abnormal push button, it outputs the complemented waveform data so as to become the normal waveform data. Therefore, when the difference between the input waveform data and the output waveform data to the autoencoder exceeds a predetermined threshold, it is possible to judge that the push button to be inspected is abnormal. Since the autoencoder is trained with the load waveform data of a plurality of normal push buttons, it is possible to make a judgment taking into consideration the variation in the pressing load seen in the load waveform data of a normal push button. Therefore, it is possible to improve the judgment accuracy.

In the above embodiment, an example of determining whether a push button (key) of a keyboard used in an electronic device or the like is normal or abnormal has been described, but the present invention is not limited to this. For example, the inspection method of this embodiment can also be applied to mouse push buttons used in an electronic device or keys of a keyboard instrument.

In addition, in the above-described embodiment, an example was described in which data showing the relationship between the stroke position of the push button and the pressing load at each stroke position was used as the load waveform data, but this is not limited to this. For example, it is also possible to determine whether a push button is normal or abnormal by using analog waveform data showing the relationship between the pressing load and the stroke position.

In the above-described embodiment, the absolute value of the difference between the pressing load of the input waveform data and the pressing load of the output waveform data at each stroke position is calculated, and if the absolute value of the difference exceeds a predetermined threshold value, the push button is determined to be abnormal; however, this is not limiting. For example, it may be determined whether the push button is normal or abnormal based on the correlation between a function indicating the input waveform data and a function indicating the output waveform data. Also, instead of comparing the difference for each stroke position with a threshold value, it may be determined that the push button is abnormal if the sum of the differences for each stroke position or the sum of the squares of the differences for each stroke position exceeds a predetermined threshold value.

In the above embodiment, an example has been described in which the load waveform data of a normal push button is learned by an autoencoder, but this is not limiting. A model learned by a machine learning algorithm other than the autoencoder may also be used.

In the above embodiment, an example has been described in which, if a push button is determined to be abnormal, the notification unit 5 notifies the abnormality, but this is not limiting. For example, if the push button is normal, the notification unit 5 may be notified that the push button is normal, and if the push button is abnormal, the notification unit 5 may be notified that the push button is abnormal.

The above-described embodiment can also be applied to a program. The above-described embodiment can also be recorded on a recording medium as a program.

(Embodiment 2)
A second embodiment will be described with reference to Figures 10 and 11. In the second embodiment, the same or equivalent configurations as those in the first embodiment will be denoted by the same reference numerals. In the second embodiment, descriptions that overlap with those in the first embodiment will be omitted.

In the second embodiment, a method for manufacturing an electronic device having an input device inspected by the inspection method described in the first embodiment is described.

Figure 10 is a diagram showing an example of an electronic device manufactured by the manufacturing method of embodiment 2. Figure 11 is a flowchart for explaining the manufacturing method of the electronic device according to embodiment 2.

In the second embodiment, a method for manufacturing an electronic device 10 having an input device shown in FIG. 10 will be described. In the example of FIG. 10, the input device is a keyboard 20 including a plurality of push buttons (keys). The input device is not limited to the keyboard 20, and may be any device having one or a plurality of push buttons. An example of a device having a push button is a keyboard panel of a PC. Alternatively, an example of a device having a push button is a home appliance having a push button such as a television or a robot vacuum cleaner, or a power strip having a push button. Alternatively, the input device may be a pointing device 30 including a push button or a keyboard of an electronic musical instrument. The electronic device 10 is, for example, a notebook PC. In this embodiment, the push buttons included in the input device are judged to be normal or abnormal by the inspection method described in the first embodiment, and an electronic device 10 equipped with an input device in which all the push buttons are normal is manufactured.

A method for manufacturing the electronic device 10 will be described with reference to FIG. 11. In the following description, an example in which the input device is a keyboard 20 will be described.

In step S21, a keyboard 20 is prepared. The keyboard 20 includes one or more push buttons (keys).

Next, in step S22, all push buttons included in the keyboard 20 prepared in step S21 are inspected using the inspection method described in embodiment 1.

If all of the push buttons included in the keyboard 20 inspected in step S22 are normal, proceed to step S24, attach the keyboard 20 to the electronic device 10, and the electronic device is completed.

If the keyboard 20 inspected in step S22 contains a push button determined to be abnormal, the keyboard 20 is not attached to the electronic device 10 as a defective product, and the process returns to step S21 to prepare another keyboard 20.

[effect]
According to the above-described embodiment, it is possible to provide a manufacturing method for electronic devices with improved inspection accuracy for push buttons. Furthermore, since all push buttons of the keyboard 20 can be inspected in a short time compared to manual inspection by an inspector, the time required for manufacturing can be shortened.

In the above embodiment, the electronic device 10 is a notebook computer equipped with an input device, but the electronic device 10 is not limited to this. The electronic device 10 may be any device that can detect the on and off states of a push button and output a signal in response to the on and off state of the push button. More specifically, the electronic device 10 may include a device itself, such as a keyboard, a mouse, or an electronic musical instrument, that includes a board on which a microcomputer is mounted.

(Overview of the embodiment)
(1) A method of inspecting a push button according to one aspect of the present disclosure includes the steps of acquiring load waveform data indicating a relationship between a stroke position of the push button and a pressing load, determining whether the push button is normal or abnormal based on the load waveform data, and notifying the user if the push button is abnormal. The step of determining whether the push button is normal or abnormal includes inputting the load waveform data as input waveform data into an autoencoder that has been trained in advance using load waveform data of a plurality of normal push buttons that have been acquired in advance as learning data, acquiring output waveform data that is output from the autoencoder, and determining whether the push button is normal or abnormal based on a difference between the input waveform data and the output waveform data.

(2) In the inspection method of (1), the step of determining whether the push button is normal or abnormal may include calculating the absolute value of the difference between the input waveform data and the output waveform data, determining that the push button is abnormal if the absolute value of the difference exceeds a predetermined threshold, and determining that the push button is normal if the absolute value of the difference is equal to or less than the predetermined threshold.

(3) In the inspection method of (1) or (2), the difference between the input waveform data and the output waveform data is the difference between the value of the input waveform data and the value of the output waveform data at each stroke position of the push button, and the step of determining whether the push button is normal or abnormal may include determining that the push button is abnormal if the absolute value of the difference at at least one stroke position exceeds a predetermined threshold value.

(4) A method for manufacturing an electronic device according to one aspect of the present disclosure includes the steps of: preparing an input device including one or more push buttons; inspecting each push button of the input device using any one of the inspection methods (1) to (3); and attaching the input device, the one or more push buttons of which are determined to be normal in the inspection step, to the electronic device.

(5) In the method for manufacturing an electronic device of (4), the input device may be configured as a keyboard.

(6) In the method for manufacturing an electronic device according to (4) or (5), the electronic device may be a notebook computer.

(7) A program according to one aspect of the present disclosure causes a computer to execute any one of the inspection methods (1) to (3).

This disclosure can be applied to the inspection of devices that include push buttons.

REFERENCE SIGNS LIST 1 Inspection system 2 Actuator 3 Sensor 4 Control unit 5 Notification unit 6 Calculation unit 7 Autoencoder 10 Electronic device 20 Keyboard (input device)
30 Pointing device 71 Encoder 72 Decoder

Claims (7)

A method for inspecting a push button, comprising the steps of:
acquiring load waveform data indicating a relationship between a stroke position of the push button and the pressing load;
determining whether the push button is normal or abnormal based on the load waveform data;
a step of notifying the user that the push button is abnormal if the push button is abnormal;
Including,
The step of determining whether the push button is normal or abnormal includes:
inputting the load waveform data as input waveform data into an autoencoder that has been previously trained using the load waveform data of a plurality of normal push buttons that have been previously acquired as training data, and acquiring output waveform data that is output from the autoencoder;
determining whether the push button is normal or abnormal based on a difference between the input waveform data and the output waveform data;
including,
Inspection method. The step of determining whether the push button is normal or abnormal includes:
calculating an absolute value of a difference between the input waveform data and the output waveform data, and judging that the push button is abnormal if the absolute value of the difference exceeds a predetermined threshold, and judging that the push button is normal if the absolute value of the difference is equal to or less than the predetermined threshold;
including,
The inspection method according to claim 1 . the difference between the input waveform data and the output waveform data is a difference between a value of the input waveform data and a value of the output waveform data at each stroke position of the push button,
the step of determining whether the push button is normal or abnormal includes determining that the push button is abnormal when an absolute value of the difference in at least one stroke position exceeds the predetermined threshold value;
The inspection method according to claim 2. A method for manufacturing an electronic device, comprising:
Providing an input device including one or more push buttons;
testing each of the push buttons of the input device using the testing method of any one of claims 1 to 3;
attaching the input device, the one or more push buttons of which have been determined to be normal in the inspecting step, to the electronic device;
including,
Manufacturing method of electronic devices. The input device is configured by a keyboard.
The method for manufacturing an electronic device according to claim 4 . The electronic device is a notebook computer.
The method for manufacturing an electronic device according to claim 4 . A program for causing a computer to execute the inspection method according to any one of claims 1 to 3.

Images