JP5017943B2 - FAILURE ANALYSIS SUPPORT DEVICE, FAILURE ANALYSIS SUPPORT PROGRAM, AND RECORDING MEDIUM CONTAINING FAILURE ANALYSIS SUPPORT PROGRAM - Google Patents

Description

  The present invention relates to a failure analysis support device, a failure analysis support method, a failure analysis support program, and a recording medium on which a failure analysis support program is recorded, and in particular, quality in a manufacturing process for manufacturing a predetermined product through a plurality of steps. The present invention relates to a failure analysis support apparatus, a failure analysis support method, a failure analysis support program, and a recording medium on which a failure analysis support program is recorded, which can identify a cause of failure for improvement.

Conventional methods for identifying the cause of failure include, for example, Japanese Patent Application Laid-Open No. 2005-251925 (Patent Document 1), Japanese Patent Application Laid-Open No. 2004-288743 (Patent Document 2), and Japanese Patent No. 2985505 (Patent Document 3). Is disclosed. According to Patent Document 1, a problematic parameter is identified from a correlation between a wafer in-plane distribution tendency of a defective semiconductor device on a wafer and a feature amount related to time series data of manufacturing parameters. According to Patent Document 2, a feature amount is calculated from a wafer defect distribution, and the wafers are classified. Moreover, according to Patent Document 3, a system that receives information from the output unit of the failure diagnosis device and displays information on the estimated failure location of the product and information on the failure occurrence frequency or occurrence probability of the estimated failure location. Disclosure.
JP 2005-251925 (Summary) JP 2004-288743 A (summary) Japanese Patent No. 2985505 (Claim 1)

  Conventional estimation of the cause of failure has been performed as described above. In Patent Document 1, a defective pattern is used for determining a defect at a position on a wafer. In general, there can be a plurality of causes for causing one defect. In Patent Document 2, since individual defects are not distinguished, there is a problem that it is not possible to classify defective portions generated from different causes, and it takes time to analyze the cause of the defect. According to Patent Document 3, since defects are classified based only on the occurrence frequency of defects, it is not possible to deal with individual defects, and there is a problem that it takes time to analyze defects as described above.

  For example, there may be a case where a single failure cause causes many failures, and it is efficient to preferentially deal with such failure causes. However, even with the same defect type, there are multiple causes of defects, and a defect that occurs due to a continuously existing defect cause and a defect that exists only temporarily and that occurs due to a defect cause that occurs less frequently are mixed. There is a case. As described above, when defects caused by different defect causes are mixed, it becomes more difficult to analyze the cause.

  The present invention has been made paying attention to the above-described problems, and is a failure analysis support device, a failure analysis support method, a failure analysis support program, and a failure analysis support program capable of efficiently analyzing the cause of a failure. An object of the present invention is to provide a recording medium on which is recorded.

  The defect analysis support apparatus according to the present invention analyzes the cause of a defect in a manufacturing process for manufacturing a product through a plurality of processes. The defect analysis support apparatus includes a measurement value collection unit that collects predetermined measurement values related to defects from an inspection machine provided in at least one of a plurality of processes, and a defect designation unit that specifies defects to be analyzed. The temporal change detection means for detecting the degree of temporal change of the measurement value for the measurement value collected by the measurement value collection means with respect to the fault designated by the fault designation means, and the fault designated by the fault designation means Storage means for storing the degree of change of the measured value detected by the temporal change detection means in association with each other.

  Since the defect and the degree of change of the related measurement value are stored in association with each other, if the degree of change is designated, only the defect corresponding to the degree of change is output. For example, it becomes possible to extract only measured values excluding sudden fluctuations in which the cause of the failure is not known when analyzing the failure. Therefore, it is possible to analyze the cause of the failure except for sudden fluctuations that are difficult to analyze.

  As a result, a failure analysis support device that can efficiently analyze the cause of failure can be provided.

  Preferably, it includes a spatial change detection means for detecting a change according to a measurement position of the measurement value with a degree of change for the measurement value collected by the measurement value collection means for the defect designated by the defect designation means, The storage means stores the defect designated by the defect designation means and the degree of change in the measured value detected by the spatial change detection means in association with each other.

  More preferably, it includes a designation unit that designates the degree of change, and an output unit that outputs a defect having the degree of change designated by the designation unit from the degree of change in the measurement value stored in the storage unit. .

  This defect may include the type of product defect.

  The output means may include a Pareto chart output means for outputting the type of failure in a Pareto chart.

  Further, the designating means may designate the degree of change in the measured value by the suddenness degree, or by the spatial suddenness degree or the temporal suddenness degree.

  Furthermore, you may make it make a user select the suddenness degree designated with a designation | designated means.

  In addition, the predetermined measured value regarding the defect may be determined in advance by a product, or may be determined in advance by a defect location and a defect type.

  According to another aspect of the present invention, a defect analysis support method for analyzing a cause of a defect in a manufacturing process for manufacturing a product through a plurality of processes is performed by using an inspection machine provided in at least one of the plurality of processes. Collecting a predetermined measurement value related to the cause of, a step of specifying a defect to be analyzed, a step of detecting a degree of temporal change of the collected measurement value for the specified defect, Storing the specified defect and the degree of temporal change of the measurement value in association with each other.

  In still another aspect of the present invention, a failure analysis support program causes a computer to execute the failure analysis support method.

  The defect analysis support program may be recorded on a computer-readable recording medium.

  An embodiment of the present invention will be described below with reference to the drawings. FIG. 1 is a diagram showing a configuration around an electronic component mounting apparatus to which a failure analysis support apparatus according to the present invention is applied. Referring to FIG. 1, electronic component mounting apparatus 10 includes a printing process, a mounting process, and a reflow process arranged from the upstream side to the downstream side of the substrate on which the electronic component is mounted. Each process is connected by a conveyor, a robot, and other transfer devices. Each process is provided with an apparatus for performing the process.

  In the printing process, a printing machine 11 for printing solder on the land of the substrate and a post-printing inspection machine 12 for performing an inspection after printing are provided. In the mounting process, a mounter 13 for mounting a component on a substrate and a post-mount inspection machine 14 for performing an inspection after mounting are provided. In the reflow process, a reflow furnace 15 for soldering component terminals to the lands and a post-reflow inspection machine 16 for performing an inspection after soldering are provided.

  The printing machine 11, the post-printing inspection machine 12, the mounter 13, the post-mounting inspection machine 14, the reflow furnace 15, and the post-reflow inspection machine 16 are each connected to the failure analysis support apparatus 20 via the network 17.

  The post-printing inspection machine 12 measures inspection data such as printed solder measurement values and inspection results, for example, print area data, using a measuring instrument (not shown). From the mounter 13, apparatus information regarding the use head, the use nozzle and the use feeder of the mounter 13, the post-mount inspection machine 14, the inspection data after the mount by the mounter 13, and the post-reflow inspection machine 16 from the post-reflow inspection Inspection data indicating the results is input to the defect analysis support device 20. The inspection machines 12, 14, and 16 in each process include a measuring instrument such as a sensor and an inspection device that inspects the appearance and the like.

  Here, the defect includes a defect type and a defective part. The defect type includes a bridge (solder adheres so as to short-circuit the electrodes of the component), a wetting defect (solder and land, or solder and There is a defect in the connection with the electrode of the component), fillet abnormality (the amount of solder is too much or too little, and the contour line when the solder is viewed from the cross section is not a clean mountain shape), and There are no parts (no parts exist).

  Next, the configuration of the failure analysis support apparatus 20 will be described. FIG. 2 is a functional block diagram showing the configuration of the failure analysis support apparatus 20. Referring to FIG. 2, defect analysis support apparatus 20 is a computer having a CPU (not shown), and includes control unit 21 that controls the entire apparatus, line information collection unit 22 that is controlled by control unit 21, A defect extraction unit 23, a suddenness calculation unit 24, and a display unit 25 are included. The defect analysis support apparatus 20 is connected to the line information database 27.

  The line information collection unit 22 functions as a measurement value collection unit, obtains the determination result of the good / bad substrate and the measurement value from the inspection machines 12, 14, 16, and stores these data in the line information database 27 in association with each other. . The defect extraction unit 23 functions as a defect designating unit that designates a defect location from the line information database 27. The suddenness degree calculation unit 24 extracts necessary data from the line information part 27 and calculates the degree of abnormality (suddenness degree) of each measurement value for each defective portion. The display unit 25 displays information on the degree of sudden occurrence of each defect.

  Here, the degree of failure occurrence will be described. FIG. 3 is a diagram for explaining the degree of change according to the measurement position of a defect designated by the defect extraction unit 23, that is, the degree of spatial suddenness of the defect. Referring to FIG. 3, it is assumed that the same substrates are produced in large numbers in order, and by chance, a failure occurs in substrate 30c among substrates 30a-30e. Here, in the same parts shown in black, the parts 31, 32, etc. are normal, but it is assumed that only the part 33 is defective. Here, the parts 31, 32, 33, etc. are the same part type.

In this case, the calculation of the spatial suddenness is performed as follows. m is the number of parts of the same type as the defective part, x (i) is the measured value of the defective part and the same type of part, f is the number of the defective part, and set A is {x (1), x (2),... x (m)}
Spatial suddenness = (x (f) −μ1) / σ1 (1)
It is represented by Note that μ1 is an average of the set A, and σ1 is a standard deviation of the entire set A.

  μ1 and σ1 may be calculated by removing the element x (f) from the set A.

Next, a change according to the degree of temporal change of the measurement value, that is, calculation of the temporal suddenness will be described. FIG. 4 is a diagram for explaining the temporal suddenness. With reference to FIG. 4, the same board | substrate is produced in large numbers in order, Among the board | substrates 40a-40e, the same components are provided in the same location so that it may be enclosed with the thick black dotted line. Of these, it is assumed that a defect has occurred in any of the components 41a to 41e. Specifically, the measurement value of the part at the same location as the defective part is represented by the degree of abnormality of the defective substrate with respect to the distribution of the measurement value of the entire lot.

In this case, the temporal suddenness is calculated as follows. n is the number of substrates produced in the lot, k is the serial number of the substrates (k = 1, 2,... n), and x (k) is the measured value at the substrate k where the defect occurred. , F is the number of a defective part, and set B is {x (1), x (2),... X (n)},
Temporal suddenness = (x (f) −μ2) / σ2 (2)
It is represented by Note that μ2 is an average of the set B, and σ2 is a standard deviation of the set B.

  μ2 and σ2 may be calculated by excluding the element x (f) from the set B.

  Next, a specific processing procedure of the defect analysis support apparatus 20 will be described. FIG. 5 is a flowchart showing an operation performed by the control unit 21 of the failure analysis support apparatus 20 shown in FIG. Referring to FIG. 5, first, the line information collection unit 22 collects the pass / fail judgment results and measurement values of the inspection target substrates from the inspection machines 12, 14, and 16 and stores them in the line information database 27 (step S <b> 11, hereinafter “ Step is omitted). Here, the inspection content and the measurement value related to the cause of the defect measured by each of the inspection machines 12, 14, and 16 are determined in advance. Next, the defect extraction unit 23 designates the defect to be analyzed by designating the defect occurrence substrate and the defect occurrence component (S12). Specifically, the defect occurrence substrate and the defect occurrence component are designated. Next, the same type of parts as the defective parts on the defective board are extracted (S13). The measured values of the same type of parts as the defective parts on the defective board are read (S14). The degree of suddenness of the measured value of the defective part with respect to the distribution of the measured value of the same kind part is calculated for the defective board (S15). In this way, the spatial suddenness is calculated.

  Next, the measured value of the part at the same location as the defective part in the entire lot is read (S16). For the measured values of the parts at the same location as the defective parts, the degree of sudden occurrence of the defective substrate with respect to the distribution of the measured values of the entire lot is calculated (S17). In this way, the temporal suddenness is calculated.

  Thereafter, the failure to be analyzed is associated with the spatial suddenness degree, temporal suddenness degree, and failure type, and stored in the line information database 27 (S18). Therefore, the line information database 27 functions as a storage unit. If necessary, the next defect is designated (YES in S19, S12). These processes are calculated by the suddenness calculation unit 24.

  In this way, the degree of change in measured values related to defects that affect quality is observed, and the measured values are stored in association with the spatial and temporal suddenness. It is possible to distinguish between those that are caused by the degree or degree of temporal suddenness and those that are not. Therefore, it is possible to determine whether each failure is a sudden failure or a tendency failure, and it is understood that there is a failure cause that causes a trend failure before a large number of failures occur regarding potential failures.

  In addition, it is possible to classify defects from a temporal and spatial viewpoint, and even if the same number of defects is concentrated in time, it can be determined that it is sudden in time. On the other hand, if it occurs continuously but occurs at the same location, it can be determined that it is spatially sudden.

  The control unit 21 functions as a temporal change detection unit and a spatial change detection unit.

  Next, measurement values used for calculating the degree of sudden occurrence will be described. For example, in the solder printing process, the amount of solder deviation, the solder area, and the transfer rate (the area of the printed solder with respect to the mask opening area) are used. Note that the volume may be used instead of the area if measurement is possible.

  Further, the amount of component displacement is used in the mounting process, and the fillet length is used in the reflow process.

  Next, the same component type (same type component) described in S13 will be described. The same component type is not necessarily limited to components having the same shape and the same dimensions, but may be similar shapes. Specifically, part type information is assigned to each part to be inspected in the inspection information, and a part having the same part type as the defective part is selected. Alternatively, for each part to be inspected in the inspection information, information on the shape of the part is given, and a part having the same shape and size as the defective part is selected.

  In the solder printing process, the mask opening corresponds to one component. That is, the solder area is measured for each mask opening. In many cases, the mask opening is rectangular, and in this case, the vertical length and the horizontal length are the shape information.

  For example, the following method can be considered when searching for the same component type. Search for items with the same vertical and horizontal lengths. In this case, each may have a width. Search for the long side and the short side with the same length. In this case, it includes the case of matching by rotating. In this case, a width may be given. Moreover, you may search for the thing with the same aspect ratio.

  In the mounting process, the shape of the component may be a rectangle circumscribing the entire component or a rectangle circumscribing the portion excluding the terminals. Even in this case, the subsequent processing is the same as in the case of the solder printing step.

  Next, a determination example using individual measurement values will be described. In the above formula (1) or (2), if the absolute value of the suddenness is ≧ 3, it is determined as sudden. This is because, assuming that the distribution of measured values is a normal distribution, the probability of taking such a value is 0.3% or less, so there is no problem even if such a determination is made. It should be noted that the value that is determined to be sudden is not limited to 3.

  In addition, defects that are not determined to be sudden are classified as tendency defects.

  Next, an example of determining the failure of one defect will be described. There are a plurality of measured values for each defect, and each can have a suddenness value. If it is desired to express the degree of sudden occurrence of one defect with one numerical value, the following method can be considered.

  (1) The maximum value of all measured values is adopted as the suddenness.

  (2) The measurement value to be used is determined for each defective type, and the maximum value is adopted among them. For example, if the defect type is a bridge, the measurement value related to the defect is the solder area of the solder printing process, and if the defect type is component displacement, the measurement value related to the defect is the solder value of the solder printing process. The amount of displacement and the amount of component displacement in the mounting process.

  (3) An interface for the user to select a measurement value may be provided, and the degree of abnormality of the selected measurement value may be employed.

Further, as a method for determining whether or not there is a sudden failure based on the suddenness of the measured value, the following method may be used.
(1) When there are a plurality of measurement values, if there is even one sudden measurement value, the defective portion is classified as a failure due to a sudden failure cause.

  (2) The determination may be made using only one of a spatial sudden failure and a temporal sudden failure.

  Next, a description will be given of extraction of a defective portion after the defect and the suddenness degree are related and stored as described above. FIG. 6 is a flowchart showing a defective portion extraction process performed by the control unit 21. Referring to FIG. 6, in extracting a defective portion, first, a range of the suddenness degree to be extracted is designated (S21). As a method for specifying the range, a range that is more abnormal than a certain threshold or a range that is not abnormal is specified. It should be noted that it may be divided into areas in advance and selected from them. Thereafter, a Pareto chart is created in the designated range (S22). A defect is extracted based on the Pareto chart (S23), and the cause is analyzed (S24). As described above, the control unit 21 functions as a designation unit.

  The range of the degree of suddenness may be specified interactively by the user via the display unit 25.

  Next, the Pareto diagram described in S22 of FIG. 6 will be described. FIG. 7 is a diagram showing the display unit 25 on which a Pareto diagram is displayed. Referring to FIG. 7, the display unit 25 includes a Pareto diagram display unit 51 and a lower part of the Pareto diagram display unit 51. , Three buttons of “sudden failure” and “progressive failure” are displayed. In this state, when the user presses the “sudden failure” button, the Pareto chart is displayed only with the failure determined to be the sudden failure. Similarly, when the “progress tendency” button is pressed, a Pareto chart is created and displayed only with the defects that are not determined to be sudden failures and are determined to be tendency failures.

  FIG. 8 shows another example of the display unit that displays the Pareto chart. Referring to FIG. 8, in this example, blanks 53a and 53b are provided for the user to specify the range (threshold value) for each of the spatial suddenness and the temporal suddenness. As this threshold value, for example, it is possible to input n times the standard deviation σ. In this figure, 3.0σ is input as the spatial suddenness and 2.0σ is input as the temporal suddenness. On the right side, the radio button allows the user to select “above”, “below”, or “all”. In addition, a button for selecting either AND / OR is also provided at the bottom, and the user can select either the spatial suddenness, the temporal suddenness, or both as required. A Pareto chart of a desired range can be displayed by selecting and specifying a necessary range. Thus, the display unit 25 functions as an output unit, a Pareto diagram output unit, and a selection unit.

  Next, still another display example of the Pareto chart will be described. FIG. 9 is a diagram showing a display example of still another Pareto chart. Referring to FIG. 9, in this example, under the Pareto diagram display unit 51, “spatial tendency failure”, “spatial sudden failure”, “temporal sudden failure”, “temporal sudden failure”, and “overall” A button for selecting one of the buttons is provided. When the user presses the “poor spatial tendency” button, a Pareto chart is created and displayed only by the faults that are determined to be poor spatial trends. Similarly for other buttons, a Pareto chart is created only by the defect corresponding to the pressed button.

  As described above, according to this embodiment, since the defect data and the data indicating whether it is a spatial sudden failure or the temporal sudden failure are associated and stored, the user can Simply enter the information you need to identify defects, and the corresponding Pareto chart will be displayed. In general, there are many cases where the cause of the failure is not known even if the sudden failure is analyzed. For example, the user can exclude the sudden failure and display the Pareto chart.

  As a result, it is possible to provide a failure analysis support apparatus that allows the user to efficiently analyze the cause of failure.

  In general, potential defects cause tendency defects before they occur frequently, so if you catch a trend defect, you can take measures to prevent future defects from occurring. it can.

  In addition, even if it is determined that the trend is poor based on the number of defects, it can be determined whether it is abrupt in terms of time and space, and more prominent defects (defects that can occur widely in time and space). Can be identified.

  In the above embodiment, the case where the defect analysis support apparatus is applied to the electronic component mounting apparatus has been described. However, the present invention is not limited to this, and analysis of defects in any manufacturing process in which a product is manufactured through a plurality of processes. You may apply to.

  Moreover, in the said embodiment, although the case where the Pareto chart was displayed was demonstrated, it is not restricted to this, For example, you may display the list | wrist of a sudden failure.

  In the above embodiment, the case where the component defect determination device is the dedicated device has been described. However, the present invention is not limited to this, and the component failure determination device is a general-purpose personal computer. May be operated by the program. In this case, the program may be provided on a recording medium such as an optical disk or a hard disk, or may be downloaded from a server on the network via a network.

  As mentioned above, although embodiment of this invention was described with reference to drawings, this invention is not limited to the thing of embodiment shown in figure. Various modifications and variations can be made to the illustrated embodiment within the same range or equivalent range as the present invention.

It is a block diagram which shows the whole structure of an electronic component mounting apparatus. It is a block diagram which shows the structure of a defect analysis assistance apparatus. It is a figure for demonstrating a spatial suddenness degree. It is a figure for demonstrating a temporal suddenness degree. It is a flowchart which shows the operation | movement which the control part of a defect analysis assistance apparatus performs. It is a flowchart which shows the content of a defect location extraction process. It is a figure which shows an example of a Pareto diagram. It is a figure which shows the other example of a Pareto diagram. It is a figure which shows the further another example of a Pareto diagram.

Explanation of symbols

10 electronic component mounting apparatus, 11 printing machine, 12 post-printing inspection machine, 13 mounter, 14 post-mounting inspection machine, 15 reflow furnace, 16 post-reflow inspection machine, 17 network, 20 defect analysis support device, 21 control unit, 22 line Information collection unit, 23 defect extraction unit, 24 suddenness calculation unit, 25 display unit, 27 line information database.

Claims (12)

A defect analysis support device for analyzing defects in a manufacturing process for manufacturing a product through a plurality of processes,
A measurement value collecting means for collecting a predetermined measurement value related to the defect from an inspection machine provided in at least one of the plurality of steps;
A defect designating means for designating a defect to be analyzed;
Temporal change detecting means for detecting the degree of temporal change of the measured values collected by the measured value collecting means for the parts at the same location as the defective parts in a plurality of products with respect to the defects designated by the defect designating means; ,
Depending on the measurement position of the measurement value collected by the measurement value collection means for a plurality of parts of the same type as the part type of the defect occurrence part on the predetermined product where the defect has occurred with respect to the defect designated by the defect designation means Spatial change detection means for detecting the degree of change,
Storage means for storing the defect designated by the defect designation means and the degree of change in the measured value detected by the temporal change detection means and the spatial change detection means in association with each other;
The failure analysis support device is a failure analysis support device that analyzes a failure based on the failure stored by the storage unit and the degree of change in the measured value. Designating means for designating the degree of change of the measured value;
The failure analysis support apparatus according to claim 1, further comprising: an output unit that outputs a defect having a degree of change designated by the designation unit from the degree of change of the measurement value stored in the storage unit. The defect analysis support apparatus according to claim 2, wherein the defect includes a type of defect of the product. The defect analysis support apparatus according to claim 3, wherein the output unit includes a Pareto diagram output unit that outputs the type of defect in a Pareto diagram. 5. The defect analysis support apparatus according to claim 2, wherein the designating unit designates a degree of change of the measurement value by an abrupt degree indicating a sudden abnormality degree of the measurement value. 6. The failure analysis support apparatus according to claim 5, wherein the designation unit designates the degree of change of the measurement value by the spatial suddenness degree or the temporal suddenness degree. The failure analysis support apparatus according to claim 5, further comprising selection means for allowing a user to select the degree of suddenness designated by the designation means. The defect analysis support apparatus according to claim 1, wherein the predetermined measurement value related to the defect is predetermined by the product. The failure analysis support apparatus according to claim 1, wherein the predetermined measurement value related to the failure is determined in advance by a failure location and a failure type. The defect analysis support apparatus according to any one of claims 1 to 9, wherein the same kind of part as the part type of the defective part includes a similar part. A failure analysis support program for causing a computer to execute a failure analysis support method for analyzing a cause of a failure in a manufacturing process of manufacturing a product through a plurality of steps,
The failure analysis support method includes a step of collecting a predetermined measurement value related to a cause of a failure from an inspection machine provided in at least one of a plurality of steps;
Specifying the defect to be analyzed;
Detecting a degree of temporal change in collected measurement values for parts in the same location as a defect occurrence part in a plurality of products for a specified defect;
Detecting a degree of change according to the measurement position of the collected measurement values for a plurality of parts of the same type as the part type of the defect occurrence part on the predetermined product in which the defect has occurred with respect to the specified defect;
Storing the specified defect in association with the degree of change in measurement value according to time and measurement position,
The failure analysis support method is a failure analysis support program for analyzing a failure based on a stored failure and a degree of change in a measured value . A computer-readable recording medium on which the failure analysis support program according to claim 11 is recorded.

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