Component evaluation device and component evaluation method

Abstract

To perform quality evaluation of components at an early stage.SOLUTION: A component evaluation device 10 includes: an information acquisition unit 11 which acquires information about a failure of a component after the use of the component; a failure rate calculation unit 12 which calculates a failure occurrence rate of the component over time on the basis of the information acquired by the information acquisition unit 11; and a quality evaluation unit 13 which evaluates the quality of the same kind of component as the component on the basis of the failure occurrence rate calculated by the failure rate calculation unit 12.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

[0002] Conventionally, one known device of this type is one that compares quality data obtained by quality inspection of previously produced mounted boards with quality data obtained by quality inspection of currently produced mounted boards to evaluate the quality of the boards (see, for example, Patent Document 1). In the device described in Patent Document 1, when the defect rate determined from the current quality data exceeds a predetermined defect rate determined from the past quality data, production is temporarily halted. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2007-53264 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, with the device described in Patent Document 1, production is not interrupted until the defect rate determined from current quality data exceeds a predetermined defect rate determined from past quality data, making it difficult to perform early quality evaluation of parts. [Means for solving the problem]

[0005] A part evaluation device according to one aspect of the present invention includes an information acquisition unit that acquires information regarding failures of the part after the part has been used, a failure rate calculation unit that calculates a failure rate of the part over time based on the information acquired by the information acquisition unit, and a quality evaluation unit that evaluates the quality of a like part that is the same type as the part, based on the failure rate calculated by the failure rate calculation unit.

[0006] A part evaluation method that is another aspect of the present invention includes an information acquisition step executed by a computer, which acquires information regarding failures of the part after use of the part, a failure rate calculation step of calculating a failure rate of the part over time based on the information acquired in the information acquisition step, and a quality evaluation step of evaluating the quality of a like part that is the same type as the part, based on the failure rate calculated in the failure rate calculation step. Effect of the Invention

[0007] According to the present invention, the quality of parts can be evaluated at an early stage. [Brief description of the drawings]

[0008] [Figure 1] 1 is a block diagram showing an example of an overall configuration of a component evaluation system including a component evaluation device according to an embodiment of the present invention. [Diagram 2] 2 is a diagram for explaining failure information managed by the part evaluation device of FIG. 1; [Diagram 3] 2 is a diagram for explaining a normal range of a component failure occurrence rate over time, which is managed by the component evaluation device of FIG. 1; [Figure 4] 2 is a diagram for explaining the elimination of failure information by the component evaluation device of FIG. 1; [Diagram 5] 4 is a flowchart showing an example of a normal range setting process executed by the component evaluation device of FIG. 1. [Figure 6] 4 is a flowchart showing an example of a quality evaluation process executed by the part evaluation device of FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, an embodiment of the present invention will be described with reference to Figs. 1 to 6. A part evaluation device according to an embodiment of the present invention evaluates the quality of a specific part mounted on a product such as a vehicle, in particular the failure rate of each part after the product is manufactured and used. During the life cycle of a product such as a vehicle from its manufacture to its disposal, failures occur in each part as time passes. If the occurrence of such failures is normal, it is sufficient to repair or replace the failed parts individually, but if it is abnormal, a fundamental response such as a design change is required.

[0010] However, since the occurrence of such a failure varies depending on the type of part and the period of use, it is difficult to evaluate early on whether the occurrence of the failure is normal or abnormal. For example, among vehicle parts, a failure such as a malfunction of a catalytic converter is relatively unlikely to occur, and even if it occurs at about 0.01% after a certain period of use, it is abnormal, whereas a failure such as steering judder occurs relatively easily, and even at about 1% it is normal. Therefore, in this embodiment, a part evaluation device is configured as follows so that a reference value of the failure occurrence rate with the passage of the period of use is set in advance for each part, so that the quality evaluation of the same type of part can be performed early.

[0011] Fig. 1 is a block diagram showing an example of the overall configuration of a part evaluation system 100 including a part evaluation device (hereinafter, device) 10 according to an embodiment of the present invention. As shown in Fig. 1, the part evaluation system 100 includes the device 10 and an information input terminal 20 provided in a store or the like that sells and repairs products such as vehicles. The device 10 and the information input terminal 20 are connected to each other so as to be able to communicate with each other via a communication network 30 that includes a WAN (Wide Area Network) such as a LAN (Local Area Network) or the Internet.

[0012] The device 10 includes a computer having a CPU (processor), a ROM, a RAM (memory), other peripheral circuits, and the like. The device 10 has an information acquisition unit 11, a failure rate calculation unit 12, and a quality evaluation unit 13 as the functional configuration of the processor, and has an information storage unit 14 as the functional configuration 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 may be configured as a single server device, may be configured as a distributed server device, or may be configured as a distributed virtual server device provided on a cloud environment.

[0013] The information input terminal 20 is composed of a device connectable to the communication network 30, such as a personal computer or tablet terminal provided in a store or the like that sells and repairs products such as vehicles. Product information relating to the product specifications, place of manufacture, and start time of use, and failure information relating to failed parts and the time of failure when the product breaks down, etc. are input into the information input terminal 20 by store staff or the like. The product information and failure information input into the information input terminal 20 are transmitted to the device 10 via the communication network 30.

[0014] The product information includes, for example, model, year, place of sale (destination), and manufacturing plant (manufacturing site) as classification information required to classify each product according to the type of product. Hereinafter, products with the same model, year, destination, manufacturing site, and the like included in the classification information are referred to as products of the same "model". In other words, each part installed in a plurality of models is subject to quality evaluation. The product information also includes information on the start of use, such as the manufacturing date, shipping date, sales date, and delivery date (handover date), as information on the start of use required to identify the start of use of each product according to the type of product. The product information of each product is managed in association with identification information such as a vehicle number for identifying each product. The input of product information may be performed not only at a store but also at a manufacturing site such as a manufacturing plant or a place of use after delivery of the product. In this case, the device for inputting the product information is also referred to as the information input terminal 20.

[0015] The failure information includes information such as the general name of the failed part (e.g., catalytic converter, steering, etc.) and the part number, which are necessary information for identifying the failed part that is the cause of the product failure. The part number for identifying each part includes, for example, a plurality of character strings, and a part of the character string (e.g., the upper two digits, etc.) indicates a major classification of the part and corresponds to the general name of the part. The failure information includes information such as the repair acceptance date when the repair request was accepted at a shop or the like that repairs the product, and the failure occurrence date when the user or the like noticed the product's failure state, as information on the time of failure required for identifying the time when the product failed. The failure occurrence date may be a date and time specified by the self-diagnosis function of the product. The failure information of each product is also managed in association with identification information such as the vehicle number, like the product information. The user of the product may input the failure information, and in this case, the user device that inputs the product information is also referred to as the information input terminal 20. When the product is equipped with a self-diagnosis function and a communication function and the product directly transmits the failure information to the device 10, the product itself is also included in the information input terminal 20.

[0016] The information acquisition unit 11 of the device 10 acquires product information transmitted from the information input terminal 20 when a product equipped with each part is manufactured, and failure information transmitted from the information input terminal 20 when a failure occurs during use of each product. 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 are stored in the information storage unit 14.

[0017] FIG. 2 is a diagram for explaining the failure information managed by the device 10, and shows an example of failure information for each model for a specific part (for example, a catalytic converter, a steering wheel, etc.). As shown in FIG. 2, the failure rate calculation unit 12 counts up the total number of products for each model (total number of units sold in the example of FIG. 2) and the total number of failures over time based on the product information and failure information acquired by the information acquisition unit 11. The total number of failures over time is the total number of failures over time from a specific point in time such as the manufacturing date of each product, and is counted on a monthly basis in the example of FIG. 2. In the example of FIG. 2, for a specific part of model A, one failure occurred within one month from the manufacturing date, two failures occurred within two months from the manufacturing date, and three failures occurred within three months from the manufacturing date.

[0018] The failure rate calculation unit 12 further calculates the failure occurrence rate over time for each model based on the total number of products for each model and the total number of failures over time. In the example of Fig. 2, the failure occurrence rate for a specific part of model A is calculated to be 0.001% for one month after the manufacturing date, 0.002% for two months after the manufacturing date, and 0.003% for three months after the manufacturing date.

[0019] The quality evaluation unit 13 evaluates the quality of a similar part of a new model, which is the same type as the specific part, based on the failure occurrence rate over time for each model calculated 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 past failure occurrence rates over time for all models, based on the past failure occurrence rates over time for each model.

[0020] The past models are models that have already been manufactured and used at the time of performing quality evaluation of the new model, and product information and failure information have been collected, and the failure rate calculation unit 12 has calculated the failure rate over time. The past models may be all models including the new model, or all models excluding the new model. The past models may be all models excluding models in which the failure occurrence situation of the evaluated parts was abnormal or models in which measures such as design changes were actually required. The quality evaluation of the parts for the new model is performed after the new model is manufactured and used, product information and failure information are collected, and the failure rate over time is calculated by the failure rate calculation unit 12. In addition, the quality evaluation is performed at the same time as the calculation of the failure rate of the past models, for example, on a monthly basis.

[0021] In the example of Figure 2, the average failure rate over time for a specific part in past models (all models) is calculated as 0.001% for one month after the manufacturing date, 0.002% for two months after the manufacturing date, and 0.003% for three months after the manufacturing date. The σ value is calculated as 0.0001% for one month after the manufacturing date, 0.0002% for two months after the manufacturing date, and 0.0003% for three months after the manufacturing date. The +1σ value is calculated as 0.0011% for one month after the manufacturing date, 0.0022% for two months after the manufacturing date, and 0.0033% for three months after the manufacturing date.

[0022] Fig. 3 is a diagram for explaining the normal range of the failure occurrence rate of a part over time, which is managed by the device 10. As shown in Fig. 3, the quality evaluation unit 13 sets +1σ value of the failure occurrence rate over time of the past model as the upper limit of the normal failure occurrence rate over time, and evaluates the quality of the same type of part mounted on the new model based on the set upper limit. More specifically, it is determined whether or not the failure occurrence rate over time of the new model calculated by the failure rate calculation unit 12 is predicted to exceed the set upper limit of the normal failure occurrence rate over time.

[0023] For example, the quality evaluation unit 13 calculates the increase rate of the failure incidence rate of the new model calculated by the failure rate calculation unit 12 from time t1 to t2, estimates the failure incidence rate at a subsequent time t3 based on the calculated increase rate, and judges whether or not it exceeds the upper limit of the normal failure incidence rate. Alternatively, the change rate of the increase rate of the failure incidence rate from time t1 to t2 may be calculated, and based on the calculated change rate, the increase rate of the failure incidence rate from time t2 to t3 and the failure incidence rate at time t3 may be estimated, and judged whether or not it exceeds the upper limit of the normal failure incidence rate. In this way, by setting the upper limit of the normal failure incidence rate over time based on the failure incidence rate of the past model and performing quality evaluation of the parts for the new model, it is possible to evaluate early whether the new model is a model that requires measures.

[0024] FIG. 4 is a diagram for explaining the exclusion of failure information by the device 10, and shows an example of a frequency distribution of failure incidence rates after a predetermined period of use calculated for each past model by the failure rate calculation unit 12 for a specific part. In the example of FIG. 4, the frequency distribution of the failure incidence rates follows a normal distribution. As shown in FIG. 4, 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 incidence rates for all past models, and then excludes models whose failure incidence rates exceed the first +1σ value from the past models. In this way, by excluding models whose failure incidence rates of specific parts are relatively higher than other models, the variance of the frequency distribution of the failure incidence rates becomes smaller. The quality evaluation unit 13 may calculate the average value (second average value), the σ value (second σ value), and the +1σ value (second +1σ value) of the failure occurrence rate for the remaining past models excluding the models exceeding the first +1σ value, and set the second +1σ value as the upper limit of the normal failure occurrence rate. In this case, the evaluation accuracy of a new model based on the upper limit of the normal failure occurrence rate can be improved.

[0025] Such exclusion of models may be repeated until the frequency distribution of the failure rate satisfies a predetermined condition. For example, the variance (σ 2The predetermined condition may be that the magnitude of the standard deviation (|σ|), or the Shannon entropy, which indicates the variation in the frequency distribution of the failure occurrence rate, is equal to or less than a predetermined value.

[0026] Fig. 5 is a flow chart showing an example of a normal range setting process executed by the device 10. The process of Fig. 5 is executed when performing a quality evaluation of a specific part for a new model, and is executed at least before the first evaluation of the new model is performed. As shown in Fig. 5, 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 acquired in step S1, the failure occurrence rate for each model for the specific part to be evaluated for each predetermined period is calculated.

[0027] Next, in step S3, it is determined whether or not the frequency distribution of the failure occurrence rate calculated in step S2 satisfies a predetermined condition for each predetermined period. If the result in step S3 is negative, the process proceeds to step S4, where the first average value, the first σ value, and the first +1σ value of the failure occurrence rate calculated in step S2 are calculated, models whose failure occurrence rate exceeds the first +1σ value are excluded, and the process returns to step S3. If the result in step S3 is positive, the process proceeds to step S5, where the average value (second average value), σ value (second σ value), and +1σ value (second +1σ value) of the failure occurrence rate for each predetermined period calculated in step S2 are calculated. Next, in step S6, the +1σ value for each predetermined period calculated in step S5 is set to the upper limit value of the normal failure occurrence rate for each predetermined period, and the process ends.

[0028] FIG. 6 is a flow chart showing an example of a quality evaluation process executed by the device 10. The process of FIG. 6 is repeatedly executed at a predetermined cycle after the normal range setting process of FIG. 5. As shown in FIG. 6, first, in step S10, it is determined whether or not new failure information on a specific part of the evaluation target is acquired from the information input terminal 20 for a new model to be evaluated. If the result in step S10 is negative, the process is terminated. If the result in step S10 is positive, the process proceeds to step S11, where failure information on the new model stored in the information storage unit 14 is read, and the failure occurrence rate for each predetermined period for the specific part to be evaluated is calculated. For example, if failure information is newly acquired in which a specific part to be evaluated has failed three months after the date of manufacture, etc., of the failure occurrence rates for each predetermined period, only the failure occurrence rate three months after the date of manufacture, etc., is updated.

[0029] Next, in step S12, the failure occurrence rate for each predetermined period of the new model calculated in step S11 is compared with the upper limit of the normal failure occurrence rate for each predetermined period set in the normal range setting process (step S6) of FIG. 5, and it is determined whether or not it is predicted to exceed the upper limit. For example, 5 months after the start of production of the new model, the increase rate of the failure occurrence rate is calculated based on the failure occurrence rates 4 months and 5 months after the start of production, and the failure occurrence rate 6 months after the start of production is estimated based on the increase rate, and it is determined whether or not it will exceed the upper limit of the normal failure occurrence rate. If the result in step S12 is negative, the process is terminated. If the result in step S12 is positive, a notice is given that there is a possibility that measures such as design changes of specific parts for the new model will be required, and the process is terminated. The notice can be given, for example, by sending a notice to an email address registered in advance.

[0030] In this way, by monitoring the change over time in the failure occurrence rate for each predetermined period for a new product and evaluating whether it is normal or not, it is possible to perform an early quality evaluation of specific parts in the new product (steps S10 to S12 in FIG. 6). Also, by performing a relative evaluation based on the past failure occurrence rates for each model, it is possible to appropriately evaluate the new model (steps S1 to S6 in FIG. 5, steps S10 to S12 in FIG. 6). Also, by excluding models with a failure occurrence rate exceeding (first +1σ value) from among the past models, it is possible to further improve the evaluation accuracy (steps S3 to S4 in FIG. 5).

[0031] According to the embodiment described above, the following advantageous effects are achieved. (1) The device 10 includes an information acquisition unit 11 that acquires information about failures of each part after use of a product equipped with the parts, a failure rate calculation unit 12 that calculates the failure rate of each part over time based on the information acquired by the information acquisition unit 11, and a quality evaluation unit 13 that evaluates the quality of the same kind of parts as each part based on the failure rate calculated by the failure rate calculation unit 12 (FIG. 1). That is, for a specific part, based on the failure rate of a past product over time, it is evaluated whether the failure rate of a new product over time is normal or not. In this way, by monitoring the failure rate of a new product over time, in other words, the change in the failure rate over time, and evaluating whether it is normal or not, it is possible to perform a quality evaluation of a specific part in the new product at an early stage and take necessary measures such as design changes.

[0032] (2) A part is mounted on a plurality of models (FIGS. 2 and 3). The failure rate calculation unit 12 calculates the past failure rate for each model (FIG. 5). The quality evaluation unit 13 evaluates the quality of the same kind of part mounted on a new model based on the past failure rate for each model calculated by the failure rate calculation unit 12 (FIG. 6). Among the plurality of models, there may be a model in which the failure rate of a particular part is relatively higher than other models, and for such a model, measures such as design changes may be required after the start of sales. By performing a relative evaluation based on the past failure rate for each model, it is possible to appropriately evaluate the possibility that the new model is a model that requires such measures.

[0033] (3) The quality evaluation unit 13 sets an upper limit of the normal failure rate based on the past failure rate for each model, and evaluates the quality of the same kind of parts installed in the new model based on the set upper limit (Figs. 2, 3, 5, and 6). This makes the evaluation easier.

[0034] (4) The quality evaluation unit 13 calculates the average value and σ value of the past failure occurrence rate for each model, and sets the sum of the calculated average value and σ value (+1σ value) as the upper limit (FIGS. 2 and 5). This makes it possible to improve the evaluation accuracy.

[0035] (5) The quality evaluation unit 13 calculates a first average value and a first σ value of the past failure occurrence rates for each model, excludes failure occurrence rates that exceed 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 past failure occurrence rates for each model, and sets the calculated sum of the second average value and the second σ value (second +1σ value) as the upper limit (FIGS. 4 and 5). This can further improve the evaluation accuracy.

[0036] In the above embodiment, products with the same specifications such as model, year, destination, and manufacturing location are regarded as the same model, and the quality evaluation of the same parts for a new model is performed based on the failure occurrence rate of the past model, but the quality evaluation of the same parts is not limited to this. For example, the quality evaluation of the same parts (same parts) for a new product may be performed based on the failure occurrence rate of past products with the same specifications.

[0037] In the above embodiment, an example in which a failure occurrence rate is used on a monthly basis has been described, but the failure occurrence rate over time is not limited to this. For example, a failure occurrence rate on a daily, weekly, or monthly basis may be used. Alternatively, a physical quantity equivalent to the operating time of a product may be used as the criterion for the passage of time. For example, when evaluating vehicle parts, the vehicle mileage may be used as the criterion for the passage of time, and the failure occurrence rate for each predetermined distance traveled may be used.

[0038] Although the present invention has been described above as a part evaluation device, the present invention can also be used as a part evaluation method. That is, the part evaluation method includes information acquisition steps S1 and S10 executed by a computer to acquire information about failures of the part after the part has been used, failure rate calculation steps S2 and S11 to calculate the failure rate of the part over time based on the information acquired in the information acquisition steps S1 and S10, and a quality evaluation step S12 to evaluate the quality of a part of the same type as the part based on the failure rate calculated in the failure rate calculation steps S2 and S11 (FIGS. 5 and 6).

[0039] The above description is merely an example, and the present invention is not limited to the above-mentioned embodiment and modifications, provided that the characteristics of the present invention are not impaired. It is also possible to arbitrarily combine one or more of the above-mentioned embodiment and modifications. [Explanation of symbols]

[0040] 10 component evaluation device (device), 11 information acquisition unit, 12 failure rate calculation unit, 13 quality evaluation unit, 14 information storage unit, 20 information input terminal, 30 communication network, 100 component evaluation system

Claims

1. an information acquisition unit that acquires information regarding a failure of a part after the part has been used; a failure rate calculation unit that calculates a failure rate of the component over time based on the information acquired by the information acquisition unit; a quality evaluation unit that evaluates a quality of a homogeneous part that is the same type as the part, based on the failure occurrence rate calculated by the failure rate calculation unit.

2. 2. The component evaluation apparatus according to claim 1, The part is installed in a plurality of models, The failure rate calculation unit calculates the failure occurrence rate for each model in the past, the quality evaluation unit evaluates quality of the same type of part installed in a new model based on the past failure occurrence rates for each model calculated by the failure rate calculation unit.

3. 3. The component evaluation apparatus according to claim 2, the quality evaluation unit sets an upper limit of a normal failure occurrence rate based on the past failure occurrence rate for each model, and evaluates the quality of the same type of part installed in the new model based on the set upper limit.

4. 4. The component evaluation apparatus according to claim 3, the quality evaluation unit calculates an average value and a standard deviation of the past failure occurrence rates for each model, and sets the calculated sum of the average value and the calculated standard deviation as the upper limit value.

5. 4. The component evaluation apparatus according to claim 3, the quality evaluation unit calculates a first average value and a first standard deviation of the past failure occurrence rates for each model, excludes failure occurrence rates that exceed the calculated sum of the first average value and the first standard deviation, calculates a second average value and a second standard deviation of the past failure occurrence rates for each model, and sets the calculated sum of the second average value and the second standard deviation as the upper limit value.

6. A method for implementing the present invention using a computer an information acquisition step of acquiring information regarding a failure of the part after the part is used; a failure rate calculation step of calculating a failure rate of the component over time based on the information acquired in the information acquisition step; a quality evaluation step of evaluating a quality of a homogeneous part that is the same type as the part, based on the failure occurrence rate calculated in the failure rate calculation step.

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