Component evaluation device and component evaluation method

Abstract

A component evaluation device (10) is provided with: an information acquisition unit (11) that acquires information relating to a failure of a component after the component is used; a failure rate calculation unit (12) that calculates the rate of failure of the component over time on the basis of the information acquired by the information acquisition unit (11); and a quality evaluation unit (13) that evaluates the quality of a component of the same type as the component on the basis of the failure rate calculated by the failure rate calculation unit (12).

Description

Technical Field

[0001] The present invention relates to a component evaluation device and a component evaluation method for evaluating the quality of components. Background Art

[0002] As such an apparatus, there is conventionally known an apparatus that compares quality data obtained by quality inspection of mounting substrates produced in the past with quality data obtained by quality inspection of mounting substrates currently being produced to evaluate the quality of mounting substrates (see, for example, Patent Document 1). In the apparatus described in Patent Document 1, when the defect rate calculated based on the current quality data exceeds a predetermined defect rate calculated based on the past quality data, production is temporarily suspended.

[0003] However, in the device described in Patent Document 1, production is not interrupted until the defective rate calculated based on current quality data exceeds a predetermined defective rate calculated based on past quality data, so it is difficult to evaluate the quality of parts in advance.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: Japanese Patent Application Publication No. 2007-053264 (JP 2007-053264 A). Summary of the invention

[0007] A component evaluation device of one technical solution of the present invention comprises: an information acquisition unit, which acquires information related to a failure of the component after the component is used; a failure rate calculation unit, which calculates the failure rate of the component over time based on the information acquired by the information acquisition unit; and a quality evaluation unit, which evaluates the quality of the same type of component as the component based on the failure rate calculated by the failure rate calculation unit.

[0008] A component evaluation method of another technical solution of the present invention includes the following steps executed by a computer: an information acquisition step of acquiring information related to a failure of the component after the component is used; a failure rate calculation step of calculating the failure rate of the component over time based on the information acquired in the information acquisition step; and a quality evaluation step of evaluating the quality of a component of the same type as the component based on the failure rate calculated in the failure rate calculation step. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The objects, features and advantages of the present invention will be further clarified through the following description of the embodiments in conjunction with the accompanying drawings.

[0010] Figure 1This is a block diagram schematically showing an example of the overall configuration of a component evaluation system including a component evaluation device according to an embodiment of the present invention.

[0011] Figure 2 Is used to illustrate the Figure 1 A diagram of the failure information managed by the parts evaluation device.

[0012] Figure 3 Is used to illustrate the Figure 1 A graph showing the normal range of failure rates of parts over time managed by a parts evaluation device.

[0013] Figure 4 Is used to illustrate the Figure 1 A diagram of the parts evaluation device troubleshooting information.

[0014] Figure 5 It is shown by Figure 1 A flowchart of an example of a normal range setting process executed by a component evaluation device.

[0015] Figure 6 It is shown by Figure 1 A flowchart of an example of quality evaluation processing performed by a component evaluation device. DETAILED DESCRIPTION

[0016] The following reference Figure 1 to Figure 6 The embodiment of the present invention is described. The component evaluation device of the embodiment of the present invention evaluates the quality of specific components mounted on products such as vehicles, especially the failure rate of each component after the product is manufactured and used. In the life cycle of products such as vehicles from manufacturing to scrapping, various components will fail over time. If the occurrence of such a failure is normal, the failed component can be repaired or replaced individually. If it is abnormal, fundamental measures such as changing the design are required.

[0017] However, the occurrence of such a fault varies depending on the type of component, the period of use, etc., so it is difficult to evaluate in advance whether the occurrence of the fault is normal or abnormal. For example, a fault such as a malfunction of a catalyst in a vehicle component is relatively difficult to occur, and even if it occurs about 0.01% after a specified period of use, it is abnormal. In contrast, a fault such as a vibration of the steering wheel is relatively easy to occur, and even if it is 1%, it is normal. Therefore, in this embodiment, the component evaluation device is configured as follows, so that a reference value of the fault occurrence rate as the period of use passes is pre-set for each component, thereby enabling the quality evaluation of the same type of components of the same type as the component to be performed in advance.

[0018] Figure 11 is a block diagram schematically showing an example of the overall configuration of a component evaluation system 100 including a component evaluation device (hereinafter referred to as a device) 10 according to an embodiment of the present invention. Figure 1 As shown, the component evaluation system 100 includes an apparatus 10 and an information input terminal 20 installed in a shop or the like that sells or repairs products such as vehicles. The apparatus 10 and the information input terminal 20 are connected to each other via a communication network 30 including a LAN (local area network) or a WAN (wide area network) such as the Internet so as to be able to communicate with each other.

[0019] The device 10 is composed of a computer including a CPU (processor), a ROM (read-only memory), a RAM (memory), other peripheral circuits, etc. The device 10 has an information acquisition unit 11, a failure rate calculation unit 12, and a quality evaluation unit 13 as a functional structure of the processor, and has an information storage unit 14 as a functional structure of the memory. That is, the processor of the device 10 functions as the information acquisition unit 11, the failure rate calculation unit 12, and the quality evaluation unit 13, and the memory of the device 10 functions as the information storage unit 14. The device 10 can be configured as a single server device, a distributed server device, or a distributed virtual server device set up in a cloud environment.

[0020] The information input terminal 20 is composed of, for example, a personal computer, a tablet terminal, or other device that can be connected to the communication network 30 and is installed in a store that sells or repairs products such as vehicles. The store staff or the like inputs product information such as product specifications, manufacturing location, and start of use, as well as fault information such as faulty parts and fault time when a product fails, into the information input terminal 20. The product information and fault information input into the information input terminal 20 are transmitted to the device 10 via the communication network 30.

[0021] In the product information, as the classification information required to classify each product according to the type of product, for example, information such as model, model year, sales place (destination), manufacturing plant (manufacturing place) is included. Hereinafter, products with the same model, model year, destination, manufacturing place, etc. contained in the classification information are referred to as products of the same "machine type". In other words, each component mounted on multiple machine types becomes the object of quality evaluation. In the product information, as the information required to determine the start date of use of each product according to the type of product, information such as manufacturing date, factory date, sales date, delivery date (delivery date) is also included. The product information of each product is managed in association with identification information such as the vehicle identification number used to determine each product. The input of product information is not limited to stores, and can also be carried out at the manufacturing place such as a manufacturing plant, the place of use after the product is delivered, etc. In this case, the device for inputting product information is also called an information input terminal 20.

[0022] The fault information includes information such as the general name of the faulty component (e.g., a catalyst, a steering wheel, etc.), the component number, etc., as information required to identify the faulty component that is the cause of the product failure. The component number used to identify each component includes, for example, a plurality of character strings, and a portion of the character strings (e.g., the first two digits, etc.) represent a large classification of the component and are equivalent to the general name of the component. The fault information includes information such as the repair acceptance date when the repair request is received at a shop that repairs the product, and the fault occurrence date when the user notices the faulty state of the product. The fault occurrence date may be a date determined by the self-diagnosis function of the product. The fault information of each product is also managed in association with identification information such as the vehicle identification number, like the product information. The input of the fault information may also be performed by the user of the product himself. In this case, the user device that inputs the product information is also referred to as the information input terminal 20. The self-diagnosis function and the communication function are mounted on the product. In the case where the fault information is sent directly from the product to the device 10, the product itself is also included in the information input terminal 20.

[0023] The information acquisition unit 11 of the device 10 acquires product information sent from the information input terminal 20 when a product equipped with each component is manufactured, and failure information sent from the information input terminal 20 when each product is used and fails. The product information and failure information acquired by the information acquisition unit 11 are associated with identification information such as a vehicle identification number and stored in the information storage unit 14.

[0024] Figure 2 2 is a diagram for explaining the fault information managed by the device 10, and shows an example of the fault information for each model related to a specific component (such as a catalyst device, a steering wheel, etc.). Figure 2 As shown, the failure rate calculation unit 12 counts the total number of products of each model (in Figure 2 In the example, it is the total number of units sold) and the total number of failures over time. The total number of failures over time is the total number of failures over time starting from a specific time point such as the manufacturing date of each product. Figure 2 In the example, the statistics are calculated in months. Figure 2 In the example, regarding a specific component of model A, 1 failure occurs within 1 month from the date of manufacture, 2 failures occur within 2 months from the date of manufacture, and 3 failures occur within 3 months from the date of manufacture.

[0025] The failure rate calculation unit 12 also calculates the failure rate of each model over time based on the total number of products of each model and the total number of failures over time. Figure 2In the example, the failure rate of a specific component of model A is calculated to be 0.001% from the manufacturing date to 1 month later, 0.002% from the manufacturing date to 2 months later, and 0.003% from the manufacturing date to 3 months later.

[0026] The quality evaluation unit 13 evaluates the quality of the same type of parts as the parts for the new model based on the failure rate over time calculated for each model by the failure rate calculation unit 12. More specifically, the quality evaluation unit 13 calculates the average value, standard deviation (σ value), and sum of the average value and standard deviation (+1σ value) of the failure rate over time of all past models based on the failure rate over time of each past model.

[0027] Past models are models that have been manufactured and used at the time when the quality evaluation of the new model is performed, and product information and failure information have been collected, and the failure rate calculation unit 12 calculates the failure rate over time. The past models can be all models including the new model, or all models except the new model. The past models can also be all models except models with abnormal failure conditions of the parts of the evaluation object and models that actually need to be addressed by design changes. After the new model is manufactured and used, product information and failure information are collected, and the failure rate calculation unit 12 calculates the failure rate over time, the quality evaluation of the parts of the new model is performed. In addition, it is performed in the same period as the period for calculating the failure rate of the past models, for example, in months.

[0028] exist Figure 2 In the example, the average value of the failure rate of a specific component over time for past models (all models) is calculated to be 0.001% from the date of manufacture to 1 month, 0.002% from the date of manufacture to 2 months, and 0.003% from the date of manufacture to 3 months. The σ value is calculated to be 0.0001% from the date of manufacture to 1 month, 0.0002% from the date of manufacture to 2 months, and 0.0003% from the date of manufacture to 3 months. The +1σ value is calculated to be 0.0011% from the date of manufacture to 1 month, 0.0022% from the date of manufacture to 2 months, and 0.0033% from the date of manufacture to 3 months.

[0029] Figure 3 1 is a diagram for explaining the normal range of the failure rate of the components managed by the device 10 over time. Figure 3As shown in FIG. 1 , the quality evaluation unit 13 sets the +1σ value of the failure rate of the previous model over time as the upper limit of the normal failure rate over time, and evaluates the quality of the same type of parts mounted on the new model based on the set upper limit. More specifically, it is determined whether the failure rate of the new model over time calculated by the failure rate calculation unit 12 is predicted to exceed the set upper limit of the normal failure rate over time.

[0030] For example, the quality evaluation unit 13 calculates the increase rate of the failure rate of the new model calculated by the failure rate calculation unit 12 at time points t1 to t2, estimates the failure rate at a subsequent time point t3 based on the calculated increase rate, and determines whether it exceeds the upper limit of the normal failure rate. Alternatively, the change rate of the increase rate of the failure rate at time points t1 to t2 is calculated, and the increase rate of the failure rate at subsequent time points t2 to t3 and the failure rate at time point t3 are estimated based on the calculated change rate, and determines whether it exceeds the upper limit of the normal failure rate. In this way, based on the failure rate of past models, the upper limit of the normal failure rate over time is set and the quality evaluation of the parts of the new model is performed, thereby being able to evaluate in advance whether the new model is a model that requires countermeasures.

[0031] Figure 4 1 is a diagram for explaining the troubleshooting information of the device 10, and shows an example of the frequency distribution of the trouble occurrence rate after a predetermined use period calculated by the trouble rate calculation unit 12 for each past model with respect to a specific component. Figure 4 In the example, the frequency distribution of the failure rate follows a normal distribution. Figure 4 As shown, after the quality evaluation unit 13 calculates the average value (first average value), σ value (first σ value) and +1σ value (first +1σ value) of the failure rate for all past models, the models whose failure rate exceeds the first +1σ value are excluded from the past models. In this way, when the models whose failure rate of specific parts is relatively higher than that of other models are excluded, the variance of the frequency distribution of the failure rate becomes smaller. The quality evaluation unit 13 can also calculate the average value (second average value), σ value (second σ value) and +1σ value (second +1σ value) of the failure rate for the remaining past models after excluding the models exceeding the first +1σ value, and set the second +1σ value as the upper limit of the normal failure rate. In this case, the evaluation accuracy of the new model based on the upper limit of the normal failure rate can be improved.

[0032] Such elimination of models may be repeated until the frequency distribution of the failure rate satisfies a predetermined condition. For example, the variance (σ2) or the size of the standard deviation (|σ|) of the frequency distribution of the failure rate, and the Shannon Entropy of the deviation of the frequency distribution of the failure rate may be less than a predetermined value as a predetermined condition.

[0033] Figure 5 This is a flowchart showing an example of the normal range setting process executed by the device 10 . Figure 5 The processing is performed when the quality evaluation of specific parts of a new model is carried out, and at least before the first evaluation of the new model. Figure 5 As shown, first in step S1, past failure information of all models stored in the information storage unit 14 is read. Next, in step S2, based on the information obtained in step S1, the failure occurrence rate of each model in each predetermined period is calculated for a specific component to be evaluated.

[0034] Next, in step S3, in each specified period, it is determined whether the frequency distribution of the failure rate calculated in step S2 satisfies the specified conditions. When step S3 is negative (S3: No), the process proceeds to step S4, and the first average value, first σ value, and first +1σ value of the failure rate calculated in step S2 are calculated, and the models whose failure rate exceeds the first +1σ value are excluded, and the process returns to step S3. When step S3 is positive (S3: Yes), the process proceeds to step S5, and the average value (second average value), σ value (second σ value), and +1σ value (second +1σ value) of the failure rate calculated in step S2 for each specified period are calculated. Next, in step S6, the +1σ value for each specified period calculated in step S5 is set as the upper limit of the normal failure rate for each specified period, and the process ends.

[0035] Figure 6 1 is a flowchart showing an example of the quality evaluation process executed by the device 10 . Figure 6 The processing in Figure 5 After the normal range setting process, it is repeated at a specified cycle. Figure 6As shown, first in step S10, regarding the new model of the evaluation object, it is determined whether new fault information about the specific parts of the evaluation object has been obtained from the information input terminal 20. When step S10 is negative (S10: No), the processing ends. When step S10 is positive (S10: Yes), the process proceeds to step S11, the fault information of the new model stored in the information storage unit 14 is read, and the failure rate of the specific parts of the evaluation object in each specified period is calculated. For example, if five months after the start of the manufacture of the new model, new fault information is obtained that the specific parts of the evaluation object have failed three months after the manufacturing date, etc., only the failure rate three months after the manufacturing date among the failure rates in each specified period is updated.

[0036] Next, in step S12, the failure occurrence rate of the new model per predetermined period calculated in step S11 is compared with the failure occurrence rate of the new model per predetermined period in step S11. Figure 5 The upper limit value of the normal failure rate for each specified period set in the normal range setting process (step S6) is compared to determine whether it is predicted to exceed the upper limit value. For example, 5 months after the start of manufacturing of a new model, the increase rate of the failure rate is calculated based on the failure rate 4 months and 5 months after the start of manufacturing, and based on this, the failure rate 6 months after the start of manufacturing is estimated to determine whether it exceeds the upper limit value of the normal failure rate. When step S12 is negative (S12: No), the process ends. When step S12 is positive (S12: Yes), it is notified that countermeasures such as design changes of specific parts of the new model may need to be taken, and the process ends. For example, notification can be made by sending a notification to a pre-registered email address.

[0037] In this way, for new products, by monitoring the change in the failure rate over time in each specified period and evaluating whether it is normal, the quality of specific parts in new products can be evaluated in advance ( Figure 6 In addition, by performing a relative evaluation based on the failure rate of each past model, it is possible to appropriately evaluate the new model ( Figure 5 Steps S1 to S6, Figure 6 In addition, by excluding models whose failure rate exceeds (the first +1σ value) in the past, the evaluation accuracy can be further improved ( Figure 5 Steps S3 to S4).

[0038] The above-described embodiment has the following effects.

[0039] (1) The device 10 comprises: an information acquisition unit 11, which acquires information related to failure of each component after the product equipped with the component is used; a failure rate calculation unit 12, which calculates the failure rate of each component over time based on the information acquired by the information acquisition unit 11; and a quality evaluation unit 13, which evaluates the quality of the same type of components as each component based on the failure rate calculated by the failure rate calculation unit 12. Figure 1 ). That is, for a specific component, the failure rate of a new product over time is evaluated based on the failure rate of past products over time. In this way, for a new product, the failure rate over time is monitored, in other words, the change in the failure rate over time is monitored, and whether it is normal is evaluated, thereby enabling the quality evaluation of specific components in the new product to be carried out in advance, and necessary countermeasures such as design changes can be taken.

[0040] (2) Parts installed in multiple models ( Figure 2 , Figure 3 The failure rate calculation unit 12 calculates the failure rate of each past model ( Figure 5 The quality evaluation unit 13 evaluates the quality of the same type of parts installed in the new model based on the failure rate of each past model calculated by the failure rate calculation unit 12 ( Figure 6 ). Among multiple models, there are models where the failure rate of specific parts is relatively higher than that of other models. For such models, countermeasures such as design changes may be required after sales start. By making a relative evaluation based on the failure rate of each past model, it is possible to appropriately evaluate the possibility that the new model is a model that requires such a countermeasure.

[0041] (3) The quality evaluation unit 13 sets an upper limit value of a normal failure rate based on the failure rate of each past model, and evaluates the quality of the same type of parts installed in the new model based on the set upper limit value. Figure 2 , Figure 3 , Figure 5 , Figure 6 ). This makes it easy to evaluate.

[0042] (4) The quality evaluation unit 13 calculates the average value and σ value of the failure occurrence rate for each model, and sets the sum of the calculated average value and σ value (+1σ value) as the upper limit value ( Figure 2 , Figure 5 ). This can improve the evaluation accuracy.

[0043] (5) The quality evaluation unit 13 calculates a first average value and a first σ value of the failure rate of each past model, and after excluding the failure rate that exceeds the sum of the calculated first average value and the first σ value (first + 1σ value), calculates a second average value and a second σ value of the failure rate of each past model, and sets the sum of the calculated second average value and the second σ value (second + 1σ value) as the upper limit value ( Figure 4 , Figure 5 ). This can further improve the evaluation accuracy.

[0044] In the above embodiment, products with the same specifications such as model, model year, destination, and manufacturing place are regarded as the same model, and the quality evaluation of the same parts of the new model is performed based on the failure rate of the past models. However, the quality evaluation of the same parts is not limited to this. For example, the quality evaluation of the same parts (the same parts) of the new product can also be performed based on the failure rate of the past products with the same specifications.

[0045] In the above embodiment, an example of using the failure rate in months is described, but the failure rate over time is not limited to this. For example, the failure rate in days, weeks, or months can also be used. Alternatively, a physical quantity equivalent to the working time of the product can be used as a reference for the passage of time. For example, in the case of evaluating vehicle parts, the driving distance of the vehicle can be used as a reference for the passage of time, and the failure rate for each specified driving distance can be used.

[0046] In the above, the present invention is described as a component evaluation device, but the present invention can also be used as a component evaluation method. That is, the component evaluation method includes the following steps executed by a computer: information acquisition steps S1 and S10 for acquiring information related to failures of the component after the component is used; failure rate calculation steps S2 and S11 for calculating the failure rate of the component over time based on the information acquired in the information acquisition steps S1 and S10; quality evaluation step S12 (S2 and S11) for evaluating the quality of the same type of component as the component based on the failure rate calculated in the failure rate calculation steps S2 and S11. Figure 5 , Figure 6 ).

[0047] One or more of the above-described embodiments and modifications may be arbitrarily combined, and modifications may be combined with each other.

[0048] By adopting the present invention, the quality evaluation of parts can be carried out in advance.

[0049] The present invention has been described above in conjunction with the preferred embodiments, but it should be understood by those skilled in the art that various modifications and changes can be made without departing from the scope of the disclosure of the claims set forth below.

Claims

1. A component evaluation device (10), characterized in that: have: An information acquisition unit (11) that acquires information related to a failure of a component after the component is used; A failure rate calculation unit (12) that calculates the failure rate of the component over time based on the information acquired by the information acquisition unit (11); as well as A quality evaluation unit (13) evaluates the quality of a component of the same type as the component based on the failure rate calculated by the failure rate calculation unit (12).

2. The component evaluation device (10) according to claim 1, characterized in that: The components are installed in multiple models. The failure rate calculation unit (12) calculates the failure rate for each past model. The quality evaluation unit (13) evaluates the quality of the same type of parts mounted on the new model based on the failure occurrence rate of each past model calculated by the failure rate calculation unit (12).

3. The component evaluation device (10) according to claim 2, characterized in that: The quality evaluation unit (13) sets an upper limit value of a normal failure rate based on the failure rate of each of the previous models, and evaluates the quality of the same type of parts mounted on the new model based on the set upper limit value.

4. The component evaluation device (10) according to claim 3, characterized in that: The quality evaluation unit (13) calculates an average value and a standard deviation of the failure occurrence rate of each of the past models, and sets the sum of the calculated average value and the standard deviation as the upper limit value.

5. The component evaluation device (10) according to claim 3, characterized in that: The quality evaluation unit (13) calculates a first mean value and a first standard deviation of the failure rate of each of the past machine models, and after excluding the failure rate exceeding the sum of the calculated first mean value and the first standard deviation, calculates a second mean value and a second standard deviation of the failure rate of each of the past machine models, and sets the sum of the calculated second mean value and the second standard deviation as the upper limit value.

6. The component evaluation device (10) according to claim 5, characterized in that: The quality evaluation unit (13) repeats the elimination until the frequency distribution of the failure occurrence rate calculated by the failure rate calculation unit (12) satisfies a predetermined condition.

7. The component evaluation device (10) according to any one of claims 1 to 6, characterized in that: The quality evaluation unit (13) reports the quality evaluation results of the same type of parts.

8. A component evaluation method, characterized in that: The process comprises the following steps executed by a computer: An information acquisition step of acquiring information related to a failure of a component after the component is used; A failure rate calculation step of calculating the failure rate of the component over time based on the information acquired in the information acquisition step; as well as A quality evaluation step of evaluating the quality of a component of the same type as the component based on the failure occurrence rate calculated in the failure rate calculation step.

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