Information processing method and information processing apparatus

Abstract

To provide an information processing method and the like that can quickly acquire the optimal acceleration condition by using a result of an acceleration test acquired in advance.SOLUTION: An information processing method according to an embodiment is to estimate an acceleration test condition for a target electronic component having characteristics deteriorated with time, and the information processing method includes: executing an acceleration test using the acceleration test condition including a plurality of load factors, on the plurality of target electronic components, acquiring measurement data including the tendency of change in leakage current for each of the plurality of target electronic components, and optimizing the acceleration test condition by using Bayesian optimization processing on the basis of the measurement data.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] FIELD An embodiment of the present invention relates to an information processing method and an information processing device. [Background technology]

[0002] One method for evaluating the reliability and lifespan of electronic components in a short period of time is to apply a voltage at a temperature above room temperature and calculate the failure life based on the change in insulation resistance. Other methods have been proposed, such as performing tests under specified accelerated test conditions to accurately estimate the time to failure in a short period of time, and optimizing material processing conditions using Bayesian optimization. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-191911 [Patent Document 2] Japanese Patent Application Laid-Open No. 2000-131363 Summary of the Invention [Problem to be solved by the invention]

[0004] Taking multilayer ceramic capacitors as an example, if temperature and voltage are used as accelerated test conditions, the number of patterns becomes enormous. Therefore, it is difficult to find test conditions that can quickly estimate failure times and other factors within an acceleration range that does not deviate from the failure modes in actual use.

[0005] The problem to be solved by the present disclosure is to realize an information processing method and information processing device that can acquire test conditions that enable the failure time of an electronic component to be estimated in a short time, more quickly and with higher accuracy than conventional methods. [Means for solving the problem]

[0006] An information processing method according to an embodiment is an information processing method for estimating accelerated test conditions for target electronic components having characteristics that deteriorate over time, and includes performing an accelerated test on a plurality of the target electronic components using accelerated test conditions that include complex load factors, obtaining measurement data that includes a change trend in the deterioration characteristics of leakage current for each of the plurality of target electronic components, and optimizing the accelerated test conditions using Bayesian optimization processing based on the measurement data. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of an information processing system according to an embodiment. [Figure 2] FIG. 2 is a diagram showing an example of an experimental device for measuring data used in accelerated test conditions. [Figure 3] FIG. 3 is a diagram showing an example of a multilayer ceramic capacitor as a target electronic component. [Figure 4] FIG. 4 is a flowchart showing the flow of the optimization process of the accelerated test conditions performed by the information processing apparatus according to the embodiment. [Figure 5] FIG. 5 is a diagram showing an example of the change over time in leakage current (leakage current characteristics) of each multilayer ceramic capacitor. [Figure 6] FIG. 6 is a graph showing a portion of the leakage current characteristics of the multilayer ceramic capacitor shown in FIG. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, an information processing system, an information processing device, and an information processing method according to embodiments will be described with reference to the drawings. Note that parts with the same reference numerals perform similar operations, and redundant explanations will be omitted as appropriate. The following embodiments do not limit the disclosed technology. Furthermore, each embodiment can be combined as appropriate within the scope of not causing contradictions in the processing content.

[0009] Generally, the cause of failure of electronic components over time is often electrical, such as a decrease in insulation resistance. Therefore, when using electronic components in the market, it is important to conduct accelerated testing to determine their service life. Accelerated testing, also known as accelerated aging testing, is a test in which a product is placed under harsh conditions and intentionally deteriorates to verify its lifespan. By multiplying the failure time obtained from the accelerated testing by a known acceleration factor, it is possible to estimate the service life in a specified environment without having to wait for actual time to pass.

[0010] 1 is a diagram illustrating an example of the configuration of an information processing system S according to an embodiment. The information processing system S uses Bayesian optimization to perform optimization processing of accelerated test conditions for target electronic components.

[0011] In the following, for the sake of concreteness, the target electronic component will be a multilayer ceramic capacitor, but the target electronic component is not limited to a multilayer ceramic capacitor and may be any electronic component that deteriorates over time with use, such as other types of capacitors or LEDs.

[0012] In the following, for the sake of specificity, the conditions used in the accelerated test (accelerated test conditions) will be taken as an example to be temperature and voltage. However, the accelerated test conditions are not limited to this example, and may include, for example, multiple load factors such as humidity, temperature cycles, or various combinations of these loads in addition to (or instead of) temperature and voltage.

[0013] As shown in Fig. 1, the information processing system S includes an experimental device 1 and an information processing device 2. The experimental device 1 performs an accelerated experiment on a plurality of multilayer ceramic capacitors as target electronic components. The information processing device 2 performs an optimization process for the accelerated test conditions using measurement data obtained from the experimental device 1. The specific configurations of the experimental device 1 and the information processing device 2 will be described below.

[0014] As shown in FIG. 1, the information processing device 2 includes a processor 20 , a main storage device 21 , an auxiliary storage device 23 , a communication interface 25 , and a device interface 27 .

[0015] 1 includes one of each component, it may include multiple of the same component. Furthermore, the software may be installed on multiple computers, and each of the multiple computers may execute the same or different parts of the software. In this case, the information processing device 2 may be configured with one or multiple computers installed on the cloud or within a facility.

[0016] The processor 20 is an electronic circuit including a control device and an arithmetic device of the information processing device 2. The processor 20 executes arithmetic processing based on data and software (programs) input from each device, etc., in the internal configuration of the information processing device 2, and outputs the arithmetic results and control signals to each device, etc.

[0017] Specifically, the processor 20 realizes the functions of the acquisition unit 200 and the Bayesian optimization calculation unit 202 by reading and executing a program stored in the main storage unit 21 or the auxiliary storage unit 23 or the like.

[0018] The acquiring unit 200 acquires measurement data based on data measured by the experimental device 1. Here, the measurement data is information including at least the change over time in leakage current (leakage current characteristics) for each combination of temperature and voltage for each multilayer ceramic capacitor during the accelerated test.

[0019] The acquisition unit 200 also acquires an optimization model of accelerated test conditions, for example, from the main storage device 21. Here, the optimization model of accelerated test conditions is an evaluation function whose input value x includes at least accelerated test conditions (temperature, voltage) and whose output value is a predetermined objective variable y (for example, a change trend in degradation characteristics such as leakage current). Examples of the optimization model of accelerated test conditions will be described in detail later.

[0020] The Bayesian optimization calculation unit 202 uses the measurement data acquired by the acquisition unit 200 to perform optimization processing of the accelerated test conditions for the multilayer ceramic capacitor.

[0021] That is, the Bayesian optimization calculation unit 202 uses the measurement data as prior data and iteratively performs Bayesian updating using an acquisition function from a predictive distribution obtained using Gaussian process regression as an index to search for optimal accelerated test conditions. The specific processing contents of the Bayesian optimization calculation unit 202 will be described in detail later.

[0022] The main memory device 21 is a storage device that stores instructions to be executed by the processor 20, various data, etc. Information stored in the main memory device 21 is read by the processor 20.

[0023] The auxiliary storage device 23 is a storage device other than the main storage device 21 .

[0024] In addition, the storage device for storing various data used in the information processing device 2 of this embodiment may be realized by the main storage device 21 or the auxiliary storage device 23, or may be realized by an internal memory built into the processor 20.

[0025] The main storage device 21 and the auxiliary storage device 23 also store information related to an optimized model of accelerated test conditions. The main storage device 21 and the auxiliary storage device 23 store, as a database, the accelerated test conditions for each multilayer ceramic capacitor obtained by the optimization process of the accelerated test conditions.

[0026] The communication interface 25 is an interface for connecting to a communication network wirelessly or by wire, and can also exchange information with an external device connected via the communication network.

[0027] The device interface 27 is an interface such as a USB (Universal Serial Bus) that directly connects to an output device (a display device, a speaker that outputs sound, a printer, etc.), an input device, and an external device.

[0028] Fig. 2 is a diagram showing an example of the configuration of the experimental device 1. As shown in Fig. 2, the experimental device 1 includes a plurality of multilayer ceramic capacitors 10 as target electronic components, a thermostatic chamber 12, a plurality of protective resistors 13, a power supply 15, and a logger 16.

[0029] The plurality of multilayer ceramic capacitors 10 are connected in parallel to a power supply 15 and stored in a thermostatic chamber 12. It is desirable that the dimensions, specified temperature, specified voltage, capacitance, etc. of the plurality of multilayer ceramic capacitors 10 be the same.

[0030] In this embodiment, a multilayer ceramic capacitor having dimensions (1608: 1.6 mm x 0.8 mm x 0.8 mm), rated voltage (50 V.DC), specified temperature (125°C), capacitance (0.1 μF), and electrode layer spacing (up to 10 μm) is used as an example.

[0031] 3 is a cross-sectional view illustrating an example of the configuration of a multilayer ceramic capacitor 10. As shown in FIG. 3, the multilayer ceramic capacitor 10 has external electrodes 100 made of, for example, nickel (Ni) or copper (Cu), internal electrodes 101 made of, for example, nickel (Ni), and a ceramic dielectric 102. As a material for the ceramic dielectric 102, for example, barium titanate (BaTiO3) can be used as the dielectric. Furthermore, trace amounts of additive elements such as manganese (Mn), magnesium (Mg), and calcium (Ca) can be added to the barium titanate (BaTiO3) of the ceramic dielectric 102.

[0032] Returning to Fig. 2, the thermostatic chamber 12 is a device that controls the temperature as an accelerated test condition. A plurality of multilayer ceramic capacitors 10 are placed inside the thermostatic chamber 12. The thermostatic chamber 12 controls the temperature of the environment in which the plurality of multilayer ceramic capacitors 10 are placed in accordance with a set temperature, thereby maintaining the set temperature.

[0033] The plurality of protective resistors 13 are each a resistor of, for example, 10 kΩ, and are connected in series to the plurality of multilayer ceramic capacitors 10 outside the thermostatic chamber 12. The plurality of protective resistors 13 are provided to prevent overcurrent from flowing in the event that dielectric breakdown occurs in the multilayer ceramic capacitor 10 during the accelerated test.

[0034] The power supply 15 applies a voltage as an accelerated test condition to the plurality of multilayer ceramic capacitors 10 in accordance with the set value.

[0035] The logger 16 is a voltage measuring instrument that measures and accumulates the voltage drop between two points on either side of each of the multiple protective resistors 13 at a predetermined timing. The voltage data measured and accumulated by the logger 16 is read out by the acquisition unit 200 of the information processing device 2 at a predetermined timing.

[0036] (Optimization of accelerated test conditions) Next, the optimization process of the accelerated test conditions executed by the information processing system S will be described.

[0037] Fig. 4 is a flowchart showing an example of the flow of optimization processing of accelerated test conditions executed by the information processing system S. Note that Fig. 4 is merely an example, and in actual optimization processing of accelerated test conditions, predetermined processes (steps) can also be executed in parallel as necessary.

[0038] As shown in FIG. 4, first, a plurality of multilayer ceramic capacitors 10 are prepared as target electronic components and set in the experimental device 1 (step S1).

[0039] The experimental device 1 starts the accelerated test on the plurality of multilayer ceramic capacitors 10 (step S2). For example, if the target electronic component is a multilayer ceramic capacitor with a specified temperature of 125°C and a specified voltage of 50 V.DC, the experimental device 1 restricts the load conditions to 100°C to 200°C for the temperature and 100 V.DC to 200 V.DC for the voltage, thereby executing the test within a range that does not deviate from the failure mode of actual use. Note that, as standard accelerated test conditions, for example, a temperature of the maximum operating temperature and an applied voltage of twice the rated voltage can be adopted.

[0040] During the accelerated test, the logger 16 measures and stores the voltage drop of each protective resistor 13 at a predetermined timing. The acquisition unit 200 reads out the data (voltage drop value) stored in the logger 16 at a predetermined timing, and uses this to acquire measurement data including the current accelerated test conditions (temperature and voltage) and the change over time in leakage current of each multilayer ceramic capacitor (leakage current characteristics) (step S3).

[0041] The acquisition unit 200 acquires an optimization model of the accelerated test conditions (step S4). The optimization model of the accelerated test conditions may be any evaluation function as long as it includes at least the temperature and voltage as the accelerated test conditions in the input value x and has the change tendency of the leakage current as the objective variable y.

[0042] FIG. 5 is a diagram showing an example of the change over time in leakage current (leakage current characteristics) of each multilayer ceramic capacitor. The leakage current characteristics of each multilayer ceramic capacitor shown in FIG. 5 are acquired by the acquisition unit 200 in step S3. Furthermore, the dielectric breakdown time Ti (the time until the dielectric breakdown point) of each multilayer ceramic capacitor 10 can be acquired from the leakage current characteristics Ci (where i is the multilayer ceramic capacitor number from 1 to 20) of each multilayer ceramic capacitor shown in FIG. 5. The optimization model for accelerated test conditions can also include the dielectric breakdown time Ti and the variation (standard deviation) σ of the dielectric breakdown time Ti in the input value x. Note that the dielectric breakdown time Ti is an example of a failure time.

[0043] FIG. 6 is a diagram excerpting a portion of the leakage current characteristics of the multilayer ceramic capacitor shown in FIG. 5. As shown in FIG. 6, the leakage current characteristics of the multilayer ceramic capacitor can be used to obtain the slope mi (where i is a multilayer ceramic capacitor number ranging from 1 to 20) of the leakage current characteristics up to dielectric breakdown for each multilayer ceramic capacitor 10. The optimization model for accelerated test conditions can also include the slope mi up to dielectric breakdown in the input value x. Note that the slope mi of the leakage current characteristics up to dielectric breakdown is an example of the slope of the characteristics up to failure.

[0044] Furthermore, the optimization model for the accelerated test conditions can also include, as input values ​​x, the accelerated test time and physical parameters related to the multilayer ceramic capacitor (grain size, distance between electrode layers, etc.).

[0045] The Bayesian optimization calculation unit 202 executes Bayesian optimization processing using the measurement data acquired by the acquisition unit 200 and the optimized model of the accelerated test conditions (step S5).

[0046] That is, the Bayesian optimization calculation unit 202 calculates a predictive distribution by Gaussian process regression using prior data (data consisting of the change trends of leakage current characteristics when an accelerated test is performed under accelerated test conditions as input values) based on the measurement data acquired by the acquisition unit 200 (step S501).

[0047] The Bayesian optimization calculation unit 202 calculates an acquisition function from the calculated predictive distribution, and determines the next candidate point (accelerated test condition) that maximizes (or minimizes) the objective variable y (the change tendency of the leakage current).

[0048] The experimental device 1 starts the accelerated test on the plurality of multilayer ceramic capacitors 10 based on the newly determined next candidate point (accelerated test condition), and the processes of steps S2 to S5 are repeatedly executed.

[0049] That is, in the optimization process of the accelerated test conditions, an analysis is performed to search for accelerated test conditions that maximize or minimize the objective variable y (the tendency of change in leakage current) based on the input value x, which includes the accelerated test conditions. Note that the input values ​​are normalized according to a predetermined method when used in the analysis.

[0050] Thereafter, the processes of steps S2 to S5 are repeatedly executed until the preset optimum conditions are satisfied (step S6), and as a result, optimized accelerated test conditions are acquired.

[0051] The optimized accelerated test conditions finally obtained are suitable test conditions that can be utilized, and can therefore be compiled into a database.

[0052] As described above, the information processing device 2 according to the embodiment is an information processing device that executes information processing to estimate accelerated test conditions for multilayer ceramic capacitors 10 as target electronic components having characteristics that deteriorate over time, and includes an acquisition unit 200 and a Bayesian optimization calculation unit 202. The acquisition unit 200 executes accelerated tests on a plurality of multilayer ceramic capacitors 10 using accelerated test conditions that include at least temperature and voltage, which are composite load factors, and acquires measurement data including the change trend of leakage current for each of the plurality of multilayer ceramic capacitors 10. The Bayesian optimization calculation unit 202 optimizes the accelerated test conditions using Bayesian optimization processing based on the measurement data.

[0053] Therefore, according to the information processing device 2 of the embodiment, accelerated test conditions that enable estimation of failure times of electronic components in a short time can be obtained more quickly and accurately than conventional methods, without having to perform accelerated tests using a huge number of temperature and voltage combinations. As a result, the workload and costs involved in accelerated tests can be reduced.

[0054] The information processing described in each of the above embodiments can also be realized by a program executable by a computer. That is, it is possible to store a program that realizes the transmission method described in each of the above embodiments in a memory, read the program from the memory using a processing circuit of a computer, and configure the transmission system or transmission method described in each of the above embodiments by using software and hardware resources in cooperation with each other.

[0055] Although several embodiments (and variations) of the present invention have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be embodied in various other forms, and various omissions, substitutions, modifications, and combinations can be made without departing from the spirit of the invention. These embodiments and variations thereof are included within the scope and spirit of the invention, and are also included in the inventions and their equivalents as defined in the claims. [Explanation of symbols]

[0056] 1. Experimental equipment 2. Information processing equipment (※There is no caption on the drawing) 10 Multilayer ceramic capacitors 12 Temperature bath 13 Protective resistor 15 Power supply 16 Logger 20 processors 21 Main storage 23 Auxiliary storage device 25 Communication Interface 27 Device Interface 100 external electrode 101 Internal electrode 102 Ceramic Dielectrics 200 Acquisition Department 202 Bayesian Optimization Calculation Unit S Information Processing System

Claims

1. 1. An information processing method for estimating accelerated test conditions for a target electronic component having characteristics that deteriorate over time, comprising: performing an accelerated test using accelerated test conditions including a composite load factor on a plurality of the target electronic components, and acquiring measurement data including a change trend in degradation characteristics of leakage current for each of the plurality of target electronic components; optimizing the accelerated test conditions using Bayesian optimization processing based on the measurement data; An information processing method comprising:

2. The accelerated test conditions are within a range that does not deviate from the failure mode of the target electronic component in actual use and does not exceed the limits of the constituent materials of the target electronic component. The information processing method according to claim 1 .

3. Iteratively performing the Bayesian optimization process to optimize the accelerated test conditions. The information processing method according to claim 1 .

4. The objective variable used in the Bayesian optimization process is a function that includes at least temperature and voltage as the complex load factors as inputs. The information processing method according to claim 1 .

5. the objective variable is a function including, as an input, at least one of the failure times of the plurality of target electronic components, the variation in the failure times, and the slope of the characteristics leading up to failure; The information processing method according to claim 4.

6. An information processing device that performs information processing to estimate accelerated test conditions for a target electronic component having characteristics that deteriorate over time, an acquisition unit that executes an accelerated test using accelerated test conditions including a composite load factor on the plurality of target electronic components, and acquires measurement data including a change trend in degradation characteristics of leakage current for each of the plurality of target electronic components; a calculation unit that optimizes the accelerated test conditions using Bayesian optimization processing based on the measurement data; An information processing device comprising:

Images