Method and apparatus for adjusting a pass / fail determination condition for an inspection object

Abstract

Disclosed is a method and apparatus for adjusting a good or not good determination condition for an inspection object. The method for adjusting the good or not good determination condition can include a step of obtaining measurement values of a structure of a plurality of inspection objects; a step of comparing error values of the measurement values with respect to a structure design value with a predetermined reference value, and determining good or not good for the plurality of inspection objects, respectively; a step of identifying one or more inspection objects in which a determination error occurs among the plurality of inspection objects; a step of generating and outputting an inspection result chart including the number of the plurality of inspection objects based on the error values, the reference value, and the number of one or more inspection objects in which the determination error occurs; a step of updating the reference value based on a graph form input on the inspection result chart, so as to reduce the determination error; and a step of comparing the error values with the updated reference value, and determining good or not good for the plurality of inspection objects, respectively, again.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to a method and apparatus for adjusting a condition for determining whether an inspection object is good or not. BACKGROUND

[0002] Manufacturers endeavor to eliminate defective products in the production process, assembly process, intermediate process, and final assembly process of products. In this process, the manufacturers use various inspection systems to determine whether the products are good (i.e., whether they are good (GOOD) or not (NG)).

[0003] According to one embodiment, an inspection system measures a structure of an inspection object, determines whether the measured value is within a range set in advance, and thus can determine whether the corresponding inspection object is good or not. For example, the inspection system irradiates light to the inspection object, receives light reflected from the inspection object, and obtains image data of the inspection object. In addition, the inspection system obtains a measured value of the inspection object based on the obtained image data, and derives an inspection result of determining whether the inspection object is good (GOOD) or not (NG) based on the measured value and a reference value set in advance.

[0004] In the inspection result derived by the inspection system, there can be a determination error of determining an actually good inspection object as not good (False Call) or determining an actually not good inspection object as good (Escape). In order to eliminate such a determination error, the reference value for the determination of whether the inspection object is good or not can be changed. However, in the past, the measured value of the inspection object was simply displayed as a number on a display of the inspection system, and the reference value was also directly inputted as a numerical value by a user. Thus, when the user wants to change the reference value, there is a problem that the measured value displayed on the display needs to be confirmed and the reference value needs to be inputted as a new numerical value one by one. SUMMARY

[0005] Technical Problem to be Solved

[0006] The present disclosure provides a method and apparatus capable of displaying an inspection result of an inspection object in a graphic manner and more conveniently adjusting a reference value for determining whether the inspection object is good or not.

[0007] In addition, the present disclosure provides a method and apparatus capable of displaying an inspection result of an inspection object, a result of determining whether the inspection object is good or not, and a result of auditing the determination of whether the inspection object is good or not in a visual manner.

[0008] In addition, the present disclosure provides a method and apparatus capable of displaying a change in a result of determining whether an inspection object is good or not and a result of auditing the determination of whether the inspection object is good or not after a reference value is adjusted in a visual manner.

[0009] In addition, the present disclosure provides a method and apparatus capable of more intuitively and conveniently implementing a user input for reducing a determination error of whether an inspection object is good or not.

[0010] Technical Solution

[0011] One aspect of the present disclosure provides a method for adjusting a good or not good judgment condition of an inspection object in a good or not good judgment device including a database, a processing section, a user input section, and an output section. The method of an exemplary embodiment includes: a step of obtaining, by means of the processing section, measured values of a structure of a plurality of inspection objects from the database; a step of comparing, by means of the processing section, error values of the measured values with respect to a design value of the structure with a predetermined reference value, and judging each of the plurality of inspection objects as good or not good; a step of identifying, by means of the processing section, one or more inspection objects in which a judgment error occurs among the plurality of inspection objects; a step of generating, by means of the processing section, an inspection result chart including the number of the plurality of inspection objects based on the error values, the reference value, and the number of the one or more inspection objects in which the judgment error occurs, and outputting the inspection result chart through the output section; a step of updating, by means of the processing section, the reference value according to a graph form input through the user input section on the inspection result chart so as to reduce the number of the one or more inspection objects in which the judgment error occurs; and a step of comparing, by means of the processing section, the error values with the updated reference value, and judging each of the plurality of inspection objects as good or not good again. The judgment error includes a first error in which an inspection object judged as good is identified as not good, and a second error in which an inspection object judged as not good is identified as good.

[0012] Inventive Effects

[0013] According to at least one embodiment of the present disclosure, an inspection result of an inspection object and a reference value are displayed in a graphic manner, and the displayed reference value can be adjusted according to a graph form input of a user. In addition, an inspection result of an inspection object can be updated based on the re-set reference value, and the updated inspection result can be displayed in a graphic manner. As a result, a user can more efficiently and simply adjust a reference value for good or not good judgment of an inspection object.

[0014] According to at least one embodiment of the present disclosure, a chart displaying an inspection result of an inspection object, a good or not good judgment result, and an audit result of the good or not good judgment can be output, and a user can make an input intended to reduce a good or not good judgment error on the output chart. In addition, a change in the audit result of the good or not good judgment based on a user input is displayed on the chart in a visual manner. As a result, a user can more conveniently and intuitively confirm whether or not a good or not good judgment error is reduced.

[0015] According to at least one embodiment of the present disclosure, when a structure of an inspection object is measured and a good or not good judgment is made according to a reference value before update, even if the reference value is updated according to a user input, a good or not good judgment of the inspection object can be made again with the updated reference value without re-measuring the structure of the inspection object. As a result, a good or not good judgment after reference value update can be rapidly performed. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 FIG. 1 is a diagram schematically showing an inspection system that determines an inspection object as a good product or a defective product according to an embodiment of the present disclosure.

[0017] Figure 2 FIG. 2 is a diagram schematically showing a configuration of a measurement device that measures a structure of an inspection object according to an embodiment of the present disclosure.

[0018] Figure 3 FIG. 3 is a block diagram schematically showing a detailed configuration of a good-bad determination device that determines whether an inspection object is good according to an embodiment of the present disclosure.

[0019] Figure 4 FIG. 4 is a diagram showing a list of inspection results including a determination error according to an embodiment of the present disclosure.

[0020] Figure 5 FIG. 5 is a diagram schematically showing an inspection result chart that shows a good-bad determination result and a determination review result according to an embodiment of the present disclosure.

[0021] Figure 6 FIG. 6 is a diagram showing a reference value update on an inspection result chart according to an embodiment of the present disclosure.

[0022] Figure 7 FIG. 7 is a diagram showing an inspection result chart in which a part of a region is enlarged according to an embodiment of the present disclosure.

[0023] Figure 8 FIG. 8 is a diagram showing an inspection result chart that shows a good-bad determination result and a determination review result according to an embodiment of the present disclosure.

[0024] Figure 9 FIG. 9 is a diagram showing an inspection result chart in which a reference value is updated according to an embodiment of the present disclosure.

[0025] Figure 10 FIG. 10 is a sequence diagram showing a method of adjusting a good-bad determination condition for an inspection object according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0026] Embodiments of the present disclosure are examples cited for the purpose of illustrating the present disclosure. Embodiments of the present disclosure can be implemented in various forms, and are not to be construed as being limited to the embodiments suggested below or specific descriptions of these embodiments.

[0027] The term "unit" used in the present specification means a software, a hardware constituent element such as an FPGA (field-programmable gate array), an ASIC (application specific integrated circuit). However, the "unit" is not limited to the hardware and the software. The "unit" can be constituted so as to be located in an addressable storage medium, or can be constituted so as to make one or more processors operate. Therefore, as one example, the "unit" includes a software constituent element, an object-oriented software constituent element, a constituent element such as a class constituent element and a task constituent element, a processor, a function, a property, a program, a subprogram, a program code segment, a driver, firmware, a microcode, a circuit, data, a database, a data structure, a table, an array, and a variable. The constituent element and the function provided in the "unit" can be combined with a smaller number of constituent elements and "units", or can be separated into additional constituent elements and "units".

[0028] All the technical and scientific terms used in the present specification have meanings that are commonly understood by a person skilled in the art to which the present disclosure pertains, unless otherwise defined. All the terms used in the present specification are selected for the purpose of more clearly explaining the present disclosure, not for the purpose of limiting the scope of the present disclosure.

[0029] As long as not differently mentioned, the singular form of the expression described in the present specification also includes the plural form of the expression, and the same applies to the singular form of the expression described in the claims.

[0030] The expressions "first", "second", and the like used in various embodiments of the present disclosure are used only for distinguishing a plurality of constituent elements from each other, and not for defining the order or importance of the corresponding constituent elements.

[0031] The expressions such as "include" and "have" used in the present specification should be understood as open-ended terms that include the possibility of including other elements unless specifically mentioned otherwise in the statement or article in which the corresponding expression is used.

[0032] In the present specification, the expression "based on" is used to describe one or more factors that affect a determination or a judgment action or an action described in the statement in which the corresponding expression is used, and the expression does not exclude additional factors that affect the determination or the judgment action or the action.

[0033] In the present specification, when referring to a certain constituent element "connected to" or "joined to" another constituent element, it is understood that the certain constituent element can be directly connected to or joined to the other constituent element, or there can be a new other constituent element between the certain constituent element and the other constituent element.

[0034] Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. For the same constituent elements on the drawings, the same reference numerals are used, and repeated description of the same constituent elements is omitted.

[0035] Figure 1 FIG. 1 is a diagram schematically showing an inspection system 10 that determines whether an inspection object is a good product or a defective product, according to an embodiment of the present disclosure.

[0036] The inspection system 10 of an embodiment of the present disclosure can determine whether a plurality of inspection objects 20 are good products or defective products, respectively, and, according to the determination result, can be branched to a good product storage device 30 or a defective product storage device 40. Here, the inspection object 20 can be any manufactured product having a three-dimensional structure manufactured according to a predetermined design standard. For example, the inspection object 20 can be a printed circuit board (PCB) to which an electronic component is attached.

[0037] The inspection system 10 can include a measurement device 100, a good-bad determination device 120, a determination review device 140, and a branching device 160. In addition, the inspection system 10 can include a network 180 that performs connection and communication between the measurement device 100, the good-bad determination device 120, the determination review device 140, and the branching device 160. As shown in FIG. 1, the inspection object 20 can be transferred to the good product storage device 30 or the defective product storage device 40 along the arrow direction through the measurement device 100, the determination review device 140, and the branching device 160. Figure 1

[0038] According to an embodiment, the inspection system 10 can be installed at a back end of a manufacturing platform that manufactures the inspection object 20 or a processing platform that processes the inspection object 20. At this time, the inspection system 10 can determine whether the manufactured or processed inspection object 20 is manufactured according to a predetermined design standard. In addition, the inspection system 10 can branch the good inspection object 20 to the good product storage device 30 and the defective inspection object 20 to the defective product storage device 40 according to the determination result.

[0039] ​The measurement device 100 can generate a measurement value that measures the structure (e.g., a three-dimensional structure) of the inspection object 20. According to one embodiment, the measurement device 100 can measure the structure of the inspection object 20 using light. For example, the measurement device 100 can irradiate structured light to the inspection object 20, receive light reflected from the inspection object 20, and can generate image data of the inspection object 20 based on the received light. In addition, the measurement device 100 can generate a measurement value that measures the structure of the inspection object 20 based on the image data. The measurement value generated by the measurement device 100 can be transmitted to the good-bad determination device 120 through the network 180. For the configuration and operation of the measurement device 100, refer to Figure 2 A more detailed description will be made.

[0040] The good-bad determination device 120 can determine whether the inspection object 20 is good or bad. The good-bad determination device 120 determines whether the measurement value generated by the measurement device 100 is within a predetermined range, and thus can determine the good or bad of the inspection object 20. According to one embodiment, the good-bad determination device 120 can calculate an error value between the measurement value of the structure of the inspection object 20 and a design value. The good-bad determination device 120 can determine the inspection object 20 whose error value is below a predetermined reference value as good (Good), and determine the inspection object 20 whose error value exceeds the predetermined reference value as bad (NG).

[0041] According to one embodiment, the good-bad determination device 120 can determine a part of the inspection object 20 whose error value is below the predetermined reference value (i.e., good) as a warning (Warning). For example, when the error value of the inspection object 20 is within a predetermined range close to the predetermined reference value, the good-bad determination device 120 can determine the corresponding inspection object 20 as a warning.

[0042] The determination review device 140 can determine whether there is an error in the good-bad determination of the inspection object 20 by the good-bad determination device 120. For example, there is a case where the inspection object 20 determined as good by the good-bad determination device 120 is actually bad (Escape). In addition, there is a case where the inspection object 20 determined as bad by the good-bad determination device 120 is actually good (False Call). Such a determination error can occur when the reference value used for the good-bad determination by the good-bad determination device 120 is set improperly. For example, when the predetermined reference value compared with the error value is set high, the good-bad determination device 120 can determine the inspection object 20 that is actually bad as good, and the determination review device 140 can determine that such a good determination is an error. In addition, when the predetermined reference value compared with the error value is set low, the good-bad determination device 120 can determine the inspection object 20 that is actually good as bad, and the determination review device 140 can determine that such a bad determination is an error.

[0043] The determination auditing device 140 can be embodied using a device capable of determining whether the test object 20 is actually good or not. As one example, the determination auditing device 140 can include a device capable of measuring the structure of the test object 20 more precisely. As another example, the determination auditing device 140 can include a device capable of confirming the electrical characteristics of the test object 20.

[0044] According to one embodiment, the determination auditing device 140 can determine whether an error of determination is made for a part of the test objects 20 for which the good-or-not determination is made by means of the good-or-not determination device 120. For example, the determination auditing device 140 can determine whether an error of determination is made for the test objects 20 determined as warning or not good by the good-or-not determination device 120. At this time, efficiency can be improved compared to the case where it is determined whether an error of determination is made for all the test objects.

[0045] According to another embodiment, the determination auditing device 140 can also determine whether an error of determination is made for all the test objects 20 for which the good-or-not determination is made by means of the good-or-not determination device 120. At this time, accuracy can be improved compared to the case where it is determined whether an error of determination is made for a part of the test objects. The result of the audit by the determination auditing device 140 can be transmitted to the good-or-not determination device 120 through the network 180.

[0046] According to still another embodiment, the determination auditing device 140 can estimate the good error value range of the good test objects 20 from the distribution of the measured error values, and additionally, can estimate the not-good error value range of the not-good test objects 20.

[0047] The error value of the physical property of the product produced according to the given production process can have a given probability distribution. The error value of the good test object 20 produced through the given process, for example, can have a good error value distribution represented as a Gamma distribution curve. The error value of the not-good test object 20 occurring due to a problem outside the process, for example, can have a not-good error value distribution represented as a Normal distribution curve.

[0048] The determination auditing device 140 can determine at least one probability distribution curve that best fits the distribution of the measured error values, and can regard the probability distribution curve closest to the origin among the determined probability distribution curves as the good error value distribution, and the remaining probability distribution curves (if any) can be regarded as the not-good error value distribution.

[0049] On the other hand, in a graph of such a good error value distribution curve and a bad error value distribution curve, the vertical axis is the number of samples of the test object which is a natural number, and thus, in probability, there is one or more samples of the test object only in a range of the horizontal axis where the value of the vertical axis is one or more, and if it exceeds the range of the horizontal axis, it is considered that there is less than one sample of the test object, in other words, it is considered that there is none. Depending on the situation, the user can consider only an error value range in which the number of samples of the test object is a predetermined number or more as a meaningful error value range. Depending on the situation, the user can consider only a range in which a predetermined percentage of samples of the test object included in the samples of the test object subjected to the test (for example, 99.5% of the samples of the test object in order of small error values) as a meaningful error value range.

[0050] According to such an observation, in the good error value distribution curve or the bad error value distribution curve, the user can respectively estimate a good error value range or a bad error value range which is considered to be meaningful. Depending on the situation, it can not be possible to obtain a meaningful bad error value distribution, and thus, it can not be possible to estimate a meaningful bad error value range.

[0051] Specifically, the determination and review device 140 estimates a good error value distribution from the distribution of the given sample error values using a predetermined probability distribution function, and if necessary, it can also estimate a bad error value distribution. At this time, the determination and review device 140 can estimate a good error value range in which the number of samples is one or more, for example, in the good error value distribution, and can estimate a bad error value range in which the number of samples is one or more, for example, in the bad error value distribution if there is one.

[0052] In a case where the estimated good error value range and the bad error value range partially overlap, the determination and review device 140 can respectively newly estimate a shortened good error value range and a bad error value range, taking into account a place where the good error value distribution and the bad error value distribution overlap each other.

[0053] If two or more bad error value distributions are estimated, the determination and review device 140 can newly estimate a consolidated bad error value range so as to be able to include all of the bad error value ranges respectively estimated from the bad error value distributions.

[0054] The determination and review device 140 can judge whether there is an error in the good determination of the test object 20 by the good determination device 120 based on the estimated good error value range, and additionally, based on the bad error value range if there is one.

[0055] For example, in a case where the reference value for the pass / fail determination is within the good error value range, if the error value of a certain inspection object 20 is greater than the reference value but within the good error value range, the determination auditing device 140 can determine that it is a second type of false call in which the inspection object 20 is actually good although it is determined to be bad based on the reference value, and can determine that the current reference value is too strict.

[0056] For example, in a case where the reference value for the pass / fail determination is within the good error value range, if the error value of a certain inspection object 20 is greater than the reference value but within the good error value range, the determination auditing device 140 can determine that it is a second type of false call in which the inspection object 20 is actually good although it is determined to be bad based on the reference value, and can determine that the current reference value is too strict.

[0057] Therefore, in a case where the reference value for the pass / fail determination is within the good error value range, the error value is the number of inspection objects 20 that are within the good error value range and greater than the reference value, or in a case where the reference value for the pass / fail determination is within the bad error value range or exceeds the range, the error value is the number of inspection objects 20 that are within the bad error value range and less than the reference value, the determination auditing device 140 can determine the number of inspection objects in which determination errors occur.

[0058] The determination result of the determination auditing device 140 can be transmitted to the pass / fail determination device 120 through the network 180. In addition, the good error value distribution and the good error value range estimated by the determination auditing device 140 can also be transmitted to the pass / fail determination device 120 through the network 180. Additionally, the bad error value distribution and the bad error value range estimated by the determination auditing device 140 can also be transmitted to the pass / fail determination device 120 through the network 180.

[0059] In this way, even if the precise re-inspection is not actually performed for the sample determined to be bad, the determination auditing device 140 can identify the inspection object 20 in which determination errors are strongly estimated from the error value distribution detected in the sample at the initial stage of production, and can determine the appropriateness of the reference value.

[0060] The good-bad determination device 120 of one embodiment of the present disclosure can adjust the good-bad determination condition for the test object 20 so as to reduce the number of test objects 20 that are determined to be false calls by the determination review device 140. The good-bad determination device 120 can update the reference value for comparison with the error value on the basis of the good-bad determination result for the test object 20 generated by the good-bad determination device 120 and the determination review result for the test object 20 generated by the determination review device 140. For example, when it is determined by means of the determination review device 140 that a false call occurs in at least a part of the test object 20, the good-bad determination device 120 can increase the reference value for comparison with the error value. In addition, when it is determined by means of the determination review device 140 that an escape occurs in at least a part of the test object 20, the good-bad determination device 120 can decrease the reference value for comparison with the error value.

[0061] The good-bad determination device 120 can update the reference value for comparison with the error value in accordance with a user input. The good-bad determination device 120 can display the good-bad determination result, the determination review result, and the reference value for the test object 20 in a graphical manner. The user can provide a graphical input for adjusting the reference value to the good-bad determination device 120 on the basis of the good-bad determination result and the determination review result displayed in a graphical manner so as to reduce the number of test objects in which a false call occurs. The good-bad determination device 120 can update the reference value in response to the graphical input of the user.

[0062] The good-bad determination device 120 can compare the updated reference value with the error value and determine again whether the test object 20 is good or bad. In addition, the good-bad determination device 120 can identify whether a false call occurs in the re-determination result for the test object 20 on the basis of the determination review result for the test object 20 generated by the determination review device 140, which represents whether the test object 20 is actually good or bad. Thus, the good-bad determination device 120 can display the good-bad re-determination result for the test object 20, the updated reference value, and the number of test objects in which a false call occurs in a graphical manner.

[0063] The good-bad determination device 120 can be embodied with a computing device such as a server computer, a personal computer, a laptop computer, a smartphone, or a tablet, for example. The configuration and operation of the good-bad determination device 120 are described in more detail with reference to Figures 3 to 10

[0064] The sorting device 160 can sort the test object 20 to the good product storage device 30 or the bad product storage device 40. The sorting device 160 can sort the good test object 20 and the bad test object 20 to the good product storage device 30 and the bad product storage device 40, respectively, on the basis of the re-determination result in the good-bad determination device 120.​

[0065] Network 180 is capable of connecting and communicating with measuring device 100, good / bad judgment device 120, judgment and verification device 140, and distribution device 160. Network 180 can be implemented using wired networks such as Local Area Network (LAN), Wide Area Network (WAN), or Value Added Network (VAN); or all types of wireless networks such as mobile radio communication network, satellite communication network, Bluetooth, Wibro (Wireless Broadband Internet), and HSDPA (High Speed ​​Downlink Packet Access).

[0066] exist Figure 1 In the illustration of the inspection system 10, each device is shown as an independent configuration, but this disclosure is not limited thereto. At least a portion of the configuration of one of the devices, namely the good / bad determination device 120, the determination review device 140, and the diversion device 160, can be integrated into the other devices. According to one embodiment, at least a portion of the configuration of the determination review device 140 can be integrated into the good / bad determination device 120. For example, the configuration of the determination review device 140, which determines whether a good / bad determination error is made by estimation from the error value distribution, can be reflected in the good / bad determination device 120.

[0067] Figure 2 This is a diagram schematically showing the configuration of a measuring device 200 for measuring the structure of an inspection body according to one embodiment of this disclosure. According to various embodiments, Figure 2 The measuring device 200 may include Figure 1 All technical features of the measuring device 100. For example... Figure 2 As shown, the measuring device 200 includes an illumination unit 210, an imaging unit 220, and an image processing unit 230.

[0068] The illumination unit 210 illuminates patterned light onto the inspection object 22, which is part of the inspection body 20, to measure it. For example, the inspection body 20 is a printed circuit board, and the inspection object 22 is solder formed on the printed circuit board or an electronic component mounted on the printed circuit board. However, the inspection body 20 and the inspection object 22 of this disclosure are not limited to these, and can be any manufactured product with a three-dimensional structure.

[0069] In one embodiment, the illumination unit 210 includes a light source 211 that generates light, a grating element 212 that converts the light from the light source 211 into patterned light, a grating transfer mechanism 213 that performs pitch transfer of the grating element 212, and a projection lens 214 that projects the patterned light converted by the grating element 212 onto the object under inspection 22. For example, in order to achieve phase shift of the patterned light, the grating element 212 can be transferred only a predetermined distance (e.g., 2π / N; where N is a natural number greater than 2) at a time by means of the grating transfer mechanism 213, such as a PZT actuator.

[0070] like Figure 2 As shown, two lighting units 210 can be provided. However, the lighting units 210 of this disclosure are not limited to this, and one or more can be provided. When two or more lighting units 210 are provided, the multiple lighting units 210 can be installed at predetermined angles along the circumferential direction or a virtual polygonal plane, or installed at predetermined intervals along a direction perpendicular to the inspection body 20.

[0071] The imaging unit 220 can receive light reflected from the object being inspected 22 and obtain image data of the object being inspected 22. The imaging unit 220 can be implemented using a CCD (charge coupled device) camera or a CMOS (complementary metal oxide semiconductor) camera, but is not necessarily limited to these. The imaging unit 220 can be mounted at an upper position perpendicular to the object being inspected 20.

[0072] The image processing unit 230 processes the image data acquired by the imaging unit 220 to generate measurement values ​​of the structure of the inspection object 22. For example, the image processing unit 230 measures the horizontal length, vertical length, height, area, volume, etc. of the inspection object 22 from the image data of the inspection object 22. The measurement values ​​generated by the image processing unit 230 can be stored in the storage unit 232 of the image processing unit 230, or transmitted to the goodness determination device 120 by means of the communication unit 234.

[0073] Figure 3 This is a block diagram illustrating the detailed configuration of a good / bad determination device 300 for determining whether an inspection object is good or bad, according to one embodiment of this disclosure. According to various embodiments, Figure 3 The goodness determination device 300 may include Figure 1 All technical features of the device 160 for determining whether it is in good working order. For example... Figure 3 As shown, a good or bad determination device 300 according to an embodiment of the present disclosure includes a communication unit 310, an input / output unit 320, a processing unit 330, and a database 340.

[0074] The communication unit 310 can be used with other devices, for example, with Figure 1 The measuring device 100, the judgment and verification device 140, and the diversion device 160 communicate with each other. In the communication unit 310, the lower-level components used to communicate with these devices can be integrated into a single hardware device.

[0075] The input / output unit 320, configured for interaction with a user, includes a user input unit 322 and an output unit 324. The user input unit 322 can receive input from the user related to the "good or bad" determination. For example, the user input unit 322 can receive input for adjusting the reference value used in the "good or bad" determination, input for displaying the "good or bad" determination result, and input for selecting any one of the "good or bad" determination results. The user input unit 322 may include a keyboard, mouse, touchpad, touchscreen, etc.

[0076] The output unit 324 provides the user with output related to the goodness or badness determination. For example, the output unit 324 may display the goodness or badness determination result of the inspection body 20, the reference value used in the goodness or badness determination, etc. The output unit 324 may include LCD (liquid crystal display), LED (light emitting diode) display, OLED (organic light emitting diode) display, etc.

[0077] The processing unit 330 can process data related to the goodness / badness determination. The processing unit 330 includes a goodness / badness determination unit 332, a determination result generation unit 334, and a determination benchmark adjustment unit 336. Furthermore, the database 340, used to store data related to the goodness / badness determination, includes design value DB342, measurement value DB344, error value DB346, benchmark value DB348, determination result DB350, and determination review result DB352.

[0078] Design values ​​for all inspected objects 22 of the inspection body 20 are stored in design value DB342. For example, when the inspection body 20 is a PCB (printed circuit board), the lateral and longitudinal lengths of the solder pads formed on the PCB, the volume and area of ​​the solder placed on the solder pads, the height of the electronic components placed on the solder pads from the solder pads, etc., can be stored as design values ​​in design value DB342.

[0079] Measurement values ​​DB344 stores measurement values ​​for all inspection objects 22 related to inspection body 20. The measurement values ​​stored in measurement value DB344 can correspond to the design values ​​stored in design value DB342. According to one embodiment, the measurement values ​​for inspection body 20 can be obtained by means of... Figure 2The measurement values generated by the measurement device 200 can be stored in the measurement value DB 344 via the communication section 234 of the measurement device 200 and the communication section 310 of the good-bad determination device 300.

[0080] The good-bad determination section 332 can calculate error values of the measurement values of the inspection objects 22 of the inspection body 20 with respect to the design values. The good-bad determination section 332 calculates the difference between the design values of the inspection objects 22 of the inspection body 20 stored in the design value DB 342 and the measurement values of the inspection objects 22 of the inspection body 20 stored in the measurement value DB 344 as the error values. The calculated error values can be stored in the error value DB 346.

[0081] The good-bad determination section 332 can determine whether the structure of the inspection body 20 satisfies a predetermined criterion. The good-bad determination section 332 can compare the error values stored in the error value DB 346 with the criterion values stored in the criterion value DB 348 to determine the good or bad of the inspection body 20. According to one embodiment, the good-bad determination section 332 can determine the inspection body 20 as good when the error value of the inspection object 22 of the inspection body 20 is below the criterion value of the corresponding inspection object 20, and can determine the inspection body 20 as bad when the corresponding error value exceeds the corresponding criterion value. For example, when the criterion value of the longitudinal length of the solder pad of the inspection body 20 is set to 0.5 mm, the good-bad determination section 332 determines the inspection body 20 having an error value of 0.6 mm for the longitudinal length of the solder pad as bad, and determines the inspection body 20 having an error value of 0.4 mm as good. The good-bad determination results generated by the good-bad determination section 332 can be stored in the determination result DB 350.

[0082] In the determination review result DB 352, the determination review results representing whether there is an error in the good-bad determination of the inspection objects 22 of the inspection body 20 by the good-bad determination section 332 are stored. When an error occurs in the good-bad determination of the inspection objects 22, as the determination review result of the corresponding inspection object 22, "determination error" can be displayed. The determination error includes a first type (Escape) in which the inspection object 22 determined as good by the good-bad determination section 332 is actually bad, and a second type (False call) in which the inspection object 22 determined as bad by the good-bad determination section 332 is actually good.

[0083] According to one embodiment, the determination review results stored in the determination review result DB 352 can be Figure 1The determination review device 140 generates. The communication section 310 can receive the determination review result generated by the determination review device 140 and store it in the determination review result DB 352. In addition, the good error value distribution estimated by the determination review device 140, the good error value range, the bad error value distribution (if any), and the bad error value range (if any) can also be stored in the determination review result DB 352 through the communication section 310 of the good-bad determination device 300.

[0084] The determination result generation section 334 can generate a check result chart representing the number of the test objects 20 based on the error values. According to one embodiment, the check result chart is a two-dimensional chart, and the horizontal axis can represent the error values, and the vertical axis can represent the number of the test objects 20 having the corresponding error values. In addition, the determination result generation section 334 can display a GUI (graphical user interface) object that can be moved by the user's operation as a reference value on the check result chart. For example, the GUI object displaying the reference value can have a shape of a bar, an arrow, a line, a dot, a quadrangle, or the like.

[0085] The determination result generation section 334 can display the good-bad determination result of the test objects 20 on the check result chart. According to one embodiment, the determination result generation section 334 can display good, warning, and bad as the good-bad determination result on the check result chart. For example, the determination result generation section 334 displays a region where the error values are below the reference value as good and a region where the error values exceed the reference value as bad on the check result chart. In addition, the determination result generation section 334 displays a predetermined region where the error values are close to the reference value as warning on the check result chart. At this time, a boundary of the region corresponding to the warning can be displayed on the check result chart. In addition, according to one embodiment, the determination result generation section 334 can display the number of the test objects 20 corresponding to good, warning, and bad, respectively, on the check result chart.

[0086] The determination result generation section 334 can display the review result of the good-bad determination result on the check result chart. According to one embodiment, the determination result generation section 334 can display the first type (Escape) of error and the second type (False call) of error as the determination review result on the check result chart. For example, the determination result generation section 334 displays a region where the test objects 20 judged as actually good belong to among the region where the error values exceed the reference value as the first type (Escape) of error on the check result chart. In addition, the determination result generation section 334 displays a region where the test objects 20 judged as actually bad belong to among the region where the error values are below the reference value as the second type (False call) of error on the check result chart.

[0087] According to one embodiment, the determination error such as the first type of error, the second type of error can be judged by the precision inspection of the determination review device 140. The determination review device 140 can include a device capable of more precisely measuring the structure of the inspection body 20 or a device capable of measuring the electrical characteristics of the inspection body 20. The determination review device 140 more precisely measures the structural electrical characteristics of the inspection body 20, so that it can judge whether the inspection body 20 is actually good or bad. As a result, the determination review device 140 can discriminate the inspection body 20 that is actually bad among the inspection bodies 20 determined to be good, and the inspection body 20 that is actually good among the inspection bodies 20 determined to be bad.

[0088] According to another embodiment, the determination error can be judged from the error value distribution by means of the estimation of the determination review device 140. The determination review device 140 can decide at least one probability distribution curve matching the error value distribution of the inspection body 20 measured by the measurement device 100, regard the probability distribution curve closest to the origin among the decided probability distribution curves as a good error value distribution, and regard the remaining probability distribution curves, if any, as bad error value distributions. The determination review device 140 can estimate a good error value range from the good error value distribution, and estimate a bad error value range, if any, from the bad error value distributions. In addition, the determination review device 140 can discriminate the inspection body 20 in which the determination error occurs among the inspection bodies 20 based on the good error value range and the bad error value range, if any.

[0089] According to the foregoing embodiment, the determination review device 140 judges whether the determination error is good or bad from the error value distribution by estimation, and the determination result generation section 334 identifies the inspection body 20 in which the determination error occurs based on whether the determination error judged by the determination review device 140 is good or bad, but the present disclosure is not limited thereto. For example, the determination result generation section 334 can be embodied to directly judge whether the determination error is good or bad from the error value distribution by estimation, and identify the inspection body 20 in which the determination error occurs.

[0090] According to one embodiment, the determination result generation section 334 can decide the candidate reference value so that the reference value can be updated. The determination result generation section 334 can decide at least one candidate reference value so that the number of the inspection bodies 20 in which the determination error occurs is reduced or minimized. For example, the determination result generation section 334 can decide the candidate reference value so that the area corresponding to the error of the first type (Escape) or the error of the second type (False call) is reduced or eliminated by means of the reference value being updated to the candidate reference value. The determination result generation section 334 can display the decided at least one candidate reference value on the inspection result chart. For example, the candidate reference value can be marked with a dot, a line, a quadrangle, an arrow, or the like.

[0091] According to one embodiment, the determination result generating section 334 can determine the candidate reference value based on the good error value range and the bad error value range (if any) of the test object 20 estimated by the determination review device 140. When there is a bad error value range, the determination result generating section 334 can determine the candidate reference value among values that are greater than or equal to the maximum value of the good error value range, less than or equal to the minimum value of the bad error value range, or equal to the maximum value of the good error value range. When there is no bad error value range, the determination result generating section 334 can determine the candidate reference value among values that are greater than or equal to the maximum value of the good error value range.

[0092] According to one embodiment, the user can select a predetermined area on the test result chart by using the user input section 322. The determination result generating section 334 can enlarge the selected predetermined area in response to the user input received by the user input section 322, and output the enlarged predetermined area by the output section 324. For example, the enlarged predetermined area can be output in a manner that covers the test result chart.

[0093] According to one embodiment, the determination result generating section 334 can generate a test result list including at least one of the measurement value, the error value, the good / bad determination result, and the determination error review result of the test object 20. The determination result generating section 334 can output the test result chart and the test result list by the output section 324. The user can confirm the test result chart and the test result list by the output section 324.

[0094] According to one embodiment, the user can select a certain test object 20 in the test result list by using the user input section 322. The determination result generating section 334 can display the error value of the selected test object 20 on the test result chart in response to the user input received by the user input section 322. For example, the error value of the selected test object 20 can be indicated by a dot, a line, a quadrangle, an arrow, or the like. According to another embodiment, when there is no input from the user regarding the selection of the test object 20, the test object 20 for which the good / bad determination was most recently performed can be automatically selected. In this case, the error value of the test object 20 for which the good / bad determination was most recently performed can be displayed on the test result chart.

[0095] The determination reference adjustment section 336 can update the reference value in accordance with an input received from the user through the user input section 322. According to one embodiment, the determination reference adjustment section 336 can receive a graphical input from the user that moves the position of the GUI object representing the reference value on the inspection result chart. For example, as the user input section 322, the user can use a mouse to click on the movable bar-shaped GUI object representing the reference value on the inspection result chart and drag it to a predetermined position. At this time, the determination reference adjustment section 336 can update the reference value to a value corresponding to the predetermined position to which the reference value is dragged in response to this graphical input. According to another embodiment, the determination reference adjustment section 336 can receive a graphical input from the user that specifies a predetermined position on the inspection result chart. For example, as the user input section 322, the user can use a mouse to click on a predetermined position on the inspection result chart. At this time, the determination reference adjustment section 336 can update the reference value to a value corresponding to the clicked predetermined position in response to this graphical input. The updated reference value can be stored in the reference value DB 348 by the determination reference adjustment section 336.

[0096] The pass / fail determination section 332 can determine again whether the inspection object 22 of the inspection body 20 is good or bad based on the reference value updated by the determination reference adjustment section 336. According to one embodiment, the pass / fail determination section 332 can determine again that the inspection body 20 is good when the error value of the inspection object 22 of the inspection body 20 is below the updated reference value, and determine that the inspection body 20 is bad when the corresponding error value exceeds the updated reference value.

[0097] In addition, the pass / fail determination section 332 can identify the inspection body 20 in which an error occurs in the re-determination. According to one embodiment, the pass / fail determination section 332 can identify the inspection body 20 in which an error occurs in the re-determination based on the re-determination result of the inspection body 20 and the determination review result stored in the determination review result DB 352. For example, the pass / fail determination section 332 can determine that the inspection body 20 that is actually bad but is determined to be good again is an error of a first type (Escape), and determine that the inspection body 20 that is actually good but is determined to be bad again is an error of a second type (False call).

[0098] The determination result generation section 334 can display the reference value updated by the determination reference adjustment section 336, the pass / fail re-determination result using the updated reference value, and the determination review result of the pass / fail re-determination result on the inspection result chart. The user can confirm the inspection result chart output through the output section 324, and thus can confirm that the error occurring in the pass / fail re-determination using the updated reference value is reduced compared to the error occurring in the pass / fail determination using the reference value before the update.

[0099] As described above, the good-bad determination device 300 of the embodiments of the present disclosure displays the good-bad determination result of the inspection object and the reference value in a graphical manner, and the reference value can be adjusted according to the graphical input of the user. In addition, the good-bad determination device 300 can perform the good-bad determination of the inspection object again on the basis of the re-set reference value, check whether the good-bad determination again has an error, and display the good-bad determination result again and the determination check result thereof in a graphical manner. As a result, the user can more efficiently and simply adjust the reference value used in the good-bad determination of the inspection object.

[0100] Figure 4 is a diagram showing an inspection result list 400 of one embodiment of the present disclosure. According to the plurality of embodiments, Figure 4 The inspection result list 400 can be generated by the determination result generation section 334 of the good-bad determination device 300 and output through the output section 324. Figure 3

[0101] As shown in Figure 4 , the inspection result list 400 includes the inspection result data 410, 420, 430, 440, 450, 460 of each of the plurality of inspection objects. Each of the inspection result data 410, 420, 430, 440, 450, 460 includes the inspection object ID, the inspection object, the measurement object, the measurement value, the error value, the good-bad determination result, and the determination check result with respect to the corresponding inspection object.

[0102] In the inspection result data 410, 430, 450, the measurement value of the lateral length of the "solder pad 1" formed on the inspection object and the error value calculated from the difference between the measurement value and the design value 10.0 mm are included. The reference value used in the good-bad determination of the lateral length of the "solder pad 1" is assumed to be set to 0.5 mm. If the inspection result data 410 is referred to, the inspection object with the inspection object ID "1" is determined to be good because the error value is 0.5 mm or less. On the contrary, if the inspection result data 430, 450 is referred to, the inspection objects with the inspection object IDs "2", "459" are determined to be bad because the error value exceeds 0.5 mm. Among them, the inspection object with the inspection object ID "459" is determined to have a second type (False call) error in the good-bad determination check result. For example, in the inspection object with the inspection object ID "459", the lateral length of the "solder pad 1" is determined to be bad according to the pre-set determination reference, but actually has a good characteristic.

[0103] ​Inspection result data 420, 440, and 460 include the measured value of the longitudinal length of "pad 1" formed on the inspected body and the error value calculated from the difference between the measured value and the design value of 10.0 mm. The benchmark value used in determining whether the longitudinal length of "pad 1" is good is assumed to be 0.5 mm. Referring to inspection result data 410, inspected bodies with inspection body IDs "1", "2", and "459" are judged as good because the error value is below 0.5 mm. However, the inspection body with inspection body ID "459" is judged to have a Type 1 (Escape) error. For example, in the inspection body with inspection body ID "459", the longitudinal length of "pad 1" is good according to the pre-set judgment benchmark, but it actually has a defective characteristic.

[0104] Figure 5 This is a diagram illustrating an inspection result chart 500 showing the results of the good / bad assessment and the review results, according to one embodiment of this disclosure. According to various embodiments, Figure 5 The inspection results chart 500 can be used with the help of Figure 3 The determination result is generated by the generation unit 334 and output by the output unit 324. According to one embodiment, Figure 5 The inspection result chart 500 can be a response received by the user input section 322. Figure 4 It is generated by selecting any one of the inspection result data (e.g., inspection result data 450) from the inspection result list 400.

[0105] like Figure 5 As shown, the horizontal axis of the inspection result chart 500 represents the error value, and the vertical axis represents the number of inspected items. The inspection result chart 500 includes a curve 510 representing the number of inspected items with corresponding error values. Additionally, the inspection result chart 500 may include a first reference value GUI520 representing a first reference value used in determining whether an inspected item is good, and a second reference value GUI530 representing a second reference value used in determining inspected items that are deemed good and corresponding to warnings. For example, the second reference value may be set to 90% of the first reference value.

[0106] Additionally, the inspection result chart 500 may include a sample error value indicator 540 that displays the error value p of any specific inspected item, such as an inspected item of particular interest to the user. As an example, the sample error value indicator 540 may be... Figure 4 The inspection results list 400 displays the error values ​​of the selected inspection body. As another example, the sample error value indicator 540 can display the error values ​​of the most recently inspected inspection body.

[0107] The inspection result chart 500 can display the "good" or "not good" judgment result and the audit result. The chart can also identify areas corresponding to "good," "warning," and "error" (judgment results) and areas corresponding to "poor" (audit results). Furthermore, the chart can also display the number of inspection items corresponding to "good," "warning," "error," and "poor" respectively. Figure 5 As shown, 352 inspected items with an error value below the first reference value b are judged as good, while 107 inspected items with an error value exceeding the first reference value b are temporarily judged as defective. Specifically, among the 352 good inspected items, 57 inspected items with an error value between the second reference value a and the first reference value b, although judged as good, are close to the first reference value and are therefore classified as warnings. On the other hand, 60 inspected items with an error value between d and e exceed the natural error distribution pattern of the given process and can therefore be judged as defective due to a problem not belonging to the given process. However, the error distribution of the 47 inspected items with an error value between the first reference value b and c is consistent with the natural error distribution of the 352 good inspected items; therefore, the 47 inspected items between b and c judged as defective are actually good as a normal result of the given process. Therefore, the 47 inspected items between the first reference value b and c can be judged as a type II error (false call). In practice, to verify whether this judgment is a type II error, the user can select a specific inspected item with an error value p between the first reference value b and c for investigation.

[0108] If the first reference value is maintained at b, even if abnormal problems in the process that induce abnormal error values ​​between d and e are eliminated, the error value will naturally be distributed between 0 and c as a normal process. Therefore, if production continues according to this process, a considerable amount of the subsequently produced products will continuously have an error value between the first reference value b and c and will be judged as defective. That is, in Figure 5 In the example, if there are no errors in the product manufacturing process itself, the first benchmark used to determine good and bad may not reflect the natural error distribution characteristics of the product manufacturing process and may be set too strictly.

[0109] The inspection result chart 500 may include a candidate benchmark indicator 550 displaying a candidate benchmark value that minimizes the number of inspected items judged incorrectly. The candidate benchmark value, as a benchmark value candidate that minimizes the number of inspected items judged incorrectly (e.g., 0), can be selected within a range of error values ​​between c and d. Figure 5 In the text, the candidate reference value indicator 550 is marked with dots, but it is not limited to this; it can also be marked with various shapes such as arrows, lines, and quadrilaterals. Additionally, in... Figure 5In the example, the candidate reference value indicator 550 identifies a single value, but is not limited thereto and can identify multiple values or a range.

[0110] Figure 6 is a diagram of a check result chart 600 that displays a reference value update according to one embodiment of the present disclosure. According to one embodiment, Figure 6 The check result chart 600 can be updated from the check result chart 500 of Figure 5 that has a reference value update.

[0111] According to one embodiment, a user can update the reference value on the check result chart 600 by using the user input 322. As one example, as the user input 322, the user can use a mouse to drag the first reference value GUI 520 to the position of the candidate reference value indicator 550 on the check result chart 600. As another example, the user can use a touchpad to touch the position of the candidate reference value indicator 550 on the check result chart 600. As described above, by means of the graphical form input through the user input 322, the position of the first reference value GUI 520 moves on the check result chart 600. In addition, as the position of the first reference value GUI 520 moves, the first reference value can also be updated. For example, as shown in Figure 6 , the first reference value is updated from b to b'.

[0112] According to one embodiment, as the position of the first reference value GUI 520 moves, the position of the second reference value GUI 530 can also move without additional user input. For example, when the ratio of the second reference value with respect to the first reference value is set to 90%, the second reference value GUI 530 can move to the right side so that the second reference value reaches 90% of the updated first reference value. As shown in Figure 6 , by means of the movement of the first reference value GUI 520, the second reference value GUI 530 can move so that the second reference value is updated from a to a', which is 90% of b'. According to another embodiment, the second reference value 530 can move the position of the second reference value GUI 530 on the check result chart 600 by means of the graphical form input through the user input 322.

[0113] According to one embodiment, in response to the movement of the first and second reference value GUIs 520, 530, the pass / fail determination section 332 can perform a re-determination of the pass / fail of each test object on the basis of the updated first and second reference values. The pass / fail determination section 332 can determine that each test object is good when the error value of each test object is equal to or less than the first reference value b', and determine that each test object is bad when the error value of each test object exceeds b'. In addition, the pass / fail determination section 332 can determine that each test object is a warning when the error value of each test object is equal to or less than the second reference value, i.e., exceeds a' and is equal to or less than b'. In addition, the pass / fail determination section 332 can identify a test object in which a re-determination error has occurred among the test objects.

[0114] The pass / fail re-determination result and the re-determination review result can be displayed in the test result chart 600. As shown in Figure 6 , 399 test objects whose error values are equal to or less than b' are determined to be "good", 12 test objects whose error values exceed a' and are equal to or less than b' are determined to be "warning", and 60 test objects whose error values are equal to or less than e are determined to be "bad". If compared with the test result chart 500 of Figure 5 , the number of test objects in which a pass / fail determination error has occurred changes from 47 in Figure 5 to 0 in Figure 6 . In other words, by updating the first reference value used as a reference for the pass / fail determination of the test objects, the error of the pass / fail determination is minimized.

[0115] As described above, by means of the graphical input by the user, the first reference value GUI 520 is moved, so that the pass / fail determination device 300 can re-determine the pass / fail of the test objects on the basis of the updated reference values. That is, unlike the conventional procedure in which the user visually confirms the measurement values one by one and decides the new reference values as numerical values, according to the present disclosure, the user can decide the new reference values while looking at the test result chart, and can update the reference values by means of the graphical input. As a result, in a state in which the determination error is visually displayed, the first reference value GUI 520 is moved, so that the first reference value can be changed, and thus the determination error can be quickly and easily corrected. In addition, the pass / fail of the test objects can be re-determined on the basis of the updated reference values, and thus user convenience can be sought.

[0116] Figure 7 is a chart in which a part of the test result chart is enlarged according to one embodiment of the present disclosure. Figure 7 The test result chart 700 can be the same as the test result chart 500 of Figure 5 as a chart in which the pass / fail determination result and the determination review result of the test objects are displayed.

[0117] According to one embodiment, a user can use the user input unit 322 to enlarge at least a portion of the inspection result chart 700 output by the output unit 324. As an example, as the user input unit 322, the user can use a mouse to select a predetermined area 710 on the inspection result chart 700. In response to the selection of the predetermined area 710, the determination result generation unit 334 can generate an enlarged chart 720 of the enlarged predetermined area 710. The generated enlarged chart 720 can be output through the output unit 324. The enlarged chart 720 can be output independently of the inspection result chart 700, or output to cover the inspection result chart 700.

[0118] Figure 8 This is a diagram showing an inspection result chart 800 displaying the results of the good / bad assessment and the review results, according to one embodiment of this disclosure. According to various embodiments, Figure 8 The inspection results chart 800 can be used with the help of Figure 3 The determination result is generated by the generation unit 334 and output by the output unit 324. According to one embodiment, Figure 8 The inspection result chart 800 can be a response received by the user input section 322. Figure 4 It is generated by selecting any one of the inspection result data (e.g., inspection result data 460) from the inspection result list 400.

[0119] The inspection result chart 800 includes a curve 810 showing the number of inspected items with corresponding error values ​​and a reference value GUI 820 showing the reference values ​​used to determine whether the inspected items are good or bad. Figure 8 As shown, 330 inspected items with an error value below the first reference value d are judged as "good," while 129 inspected items with an error value between e and f, which is greater than the first reference value d, are judged as "bad." In this case, even among the 330 good inspected items, the 25 inspected items with error values ​​between b and c, although judged as good, exceed the natural error distribution pattern (0 to a) in the given process, and therefore would actually be considered "bad" due to a problem not belonging to the given process. Therefore, the 25 inspected items between b and c can be judged as type one errors (Escape).

[0120] If the first reference value d is maintained, then even if the abnormal problems in the process that induce abnormal error values ​​between e and f are eliminated, as a normal process, the error value will only naturally be distributed between 0 and a. Therefore, if production continues according to this process, a considerable amount of the products produced later will actually be defective and will continuously show error values ​​lower than the first reference value d, and will be judged as good. That is, in Figure 8In the example of FIG. 8, if the product manufacturing process itself is not in error, it can be that the first reference value used to determine good and bad cannot reflect the natural error distribution characteristics of the product manufacturing process, and is set too loosely.

[0121] In the inspection result chart 800, a candidate reference value indicator 830 that displays a candidate reference value that minimizes the number of inspection bodies for which a determination error occurs can be included. The candidate reference value can be selected within a range between a and b in which the number of inspection bodies determined to be in error is minimized (e.g., 0). In Figure 8 , the candidate reference value indicator 830 is identified with a dot, but is not limited thereto, and can be identified with various shapes such as an arrow, a line, a quadrangle, etc. In addition, in Figure 8 , the candidate reference value indicator 830 is identified singularly, but is not limited thereto, and can be identified in plural or as a range. In addition, although not illustrated in Figure 8 , the inspection result chart 800 of one embodiment can include a GUI that displays a reference value used to determine inspection bodies corresponding to warnings among inspection bodies determined to be good, and an indicator that displays an error value of any one of a plurality of inspection bodies.

[0122] Figure 9 FIG. 9 is a diagram illustrating an inspection result chart 900 in which a reference value is updated according to one embodiment of the present disclosure. According to one embodiment, Figure 9 , the inspection result chart 900 can be updated from the inspection result chart 800 of Figure 8 .

[0123] According to one embodiment, a user can update a reference value on the inspection result chart 900 by using the user input unit 322. As one example, as the user input unit 322, the user can use a mouse to drag the reference value GUI 820 to the position of the candidate reference value indicator 830 on the inspection result chart 900. As another example, the user can use a touchpad to touch the position of the candidate reference value indicator 830 on the inspection result chart 900. As described above, by means of the graphical form input through the user input unit 322, the position of the reference value GUI 820 is moved in the inspection result chart 900. In addition, as the position of the reference value GUI 820 is moved, the reference value can also be updated. For example, as illustrated in Figure 9 , the reference value is updated from d to d'.

[0124] According to one embodiment, in response to the movement of the reference value GUI 820, the good-bad determination unit 332 can perform good-bad re-determination of each inspection object on the basis of the updated reference value. The good-bad determination unit 332 can determine that each inspection object is good when the error value of each inspection object is equal to or less than the reference value d', and can determine that each inspection object is bad when the error value of each inspection object exceeds d'. In addition, the good-bad determination unit 332 can identify an inspection object in which a re-determination error occurs among the inspection objects.

[0125] In the inspection result chart 900, the good-bad re-determination result and the re-determination review result can be displayed. As shown in Figure 9 , 305 inspection objects whose error values are equal to or less than d' are determined to be "good", and 154 inspection objects whose error values exceed d' are determined to be "bad". If compared with the inspection result chart 800 of Figure 8 , the number of inspection objects in which a good-bad determination error occurs changes from 25 of Figure 8 to 0 of Figure 9 . In other words, by updating the reference value used as a reference for good-bad determination of the inspection objects, the good-bad determination error is minimized.

[0126] Figure 10 is a sequence diagram showing a method of adjusting a good-bad determination condition for an inspection object according to an embodiment of the present disclosure. Figure 10 At least a part of the steps illustrated in Figures 1 to 3 can be performed by means of the configuration shown in

[0127] First, in step S1000, the good-bad determination device 300 obtains measurement values of structures of a plurality of inspection objects. For example, the measurement device 100 irradiates light to an inspection object, receives light reflected from the inspection object, and can generate image data of the inspection object on the basis of the received light. In addition, the measurement device 100 can generate measurement values that measure the structure of the inspection object on the basis of the image data. The good-bad determination device 300 can obtain the measurement values generated by means of the measurement device 100 through the communication unit 310.

[0128] Then, in step S1010, the good-bad determination unit 332 performs good-bad determination of a plurality of inspection objects. For example, the good-bad determination unit 332 determines whether the measurement values obtained in step S1000 are within a predetermined range, and thus can determine the good or bad of the inspection object. The good-bad determination unit 332 calculates error values of the measurement values of the structure of the inspection object with respect to design values, and compares the calculated error values with a predetermined reference value. The good-bad determination unit 332 can determine that an inspection object whose error value is equal to or less than a predetermined reference value is good (Good), and determine that an inspection object whose error value exceeds the predetermined reference value is bad (NG).

[0129] Then, in step S1020, the determination result generating section 334 identifies the inspection body in which a determination error has occurred among the plurality of inspection bodies. For example, the determination result generating section 334 identifies the inspection body in which a determination error has occurred among the plurality of inspection bodies on the basis of the pass / fail determination result of the inspection body obtained in step S1010 and the determination review result by means of the determination review device 140. Here, the determination error includes a first error in which the inspection body determined to be good is identified as actually bad, and a second error in which the inspection body determined to be bad is identified as actually good.

[0130] According to one embodiment, the determination review device 140 can decide the good error value distribution and the bad error value distribution (if any) on the basis of the error value distribution of the inspection body 20 measured by means of the measuring device 100, and estimate the good error value range and the bad error value range (if any) from the good error value distribution and the bad error value distribution (if any), respectively. In addition, the determination review device 140 can discriminate the inspection body 20 in which a determination error has occurred among the inspection bodies 20 on the basis of the good error value range and the bad error value range (if any). In addition, the determination result generating section 334 can receive such determination review result from the determination review device 140 and identify the inspection body 20 in which a determination error has occurred.

[0131] Then, in step S1030, the determination result generating section 334 outputs the inspection result chart. For example, the determination result generating section 334 generates the inspection result chart that displays the number of inspection bodies on the basis of the error value. The inspection result chart is displayed as a two-dimensional chart in which the horizontal axis represents the error value and the vertical axis represents the number of inspection bodies having the corresponding error value among the plurality of inspection bodies. The determination result generating section 334 can display a GUI object in the shape of a bar that can be moved by means of the user's operation as the reference value on the inspection result chart. In addition, the determination result generating section 334 can display good, warning, and bad as the pass / fail determination result on the inspection result chart. In addition, the determination result generating section 334 can display the review result of the pass / fail determination result on the inspection result chart. In addition, the determination result generating section 334 can decide at least one candidate reference value that makes the number of one or more inspection bodies in which a determination error has occurred minimum and display it on the inspection result chart.

[0132] According to one embodiment, the candidate reference value can be decided on the basis of the good error value range and the bad error value range (if any) estimated in step S1020. When there is the bad error value range, the candidate reference value can be selected from among certain values that are greater than or equal to the maximum value of the good error value range and less than or equal to the minimum value of the bad error value range. When there is no bad error value range, the candidate reference value can be selected from among certain values that are greater than or equal to the maximum value of the good error value range.

[0133] Then, in step S1040, the judgment benchmark adjustment unit 336 updates the benchmark value according to the graphical input on the inspection result chart. The user can provide graphical input on the inspection result chart to reduce the number of inspection items with more than one judgment error. For example, as the user input unit 322, the user can use a mouse to drag the GUI representing the benchmark value to a predetermined position on the inspection result chart 600. The judgment benchmark adjustment unit 336 updates the benchmark value to the predetermined value in response to the user's graphical input (i.e., the movement of the GUI representing the benchmark value).

[0134] Then, in step S1050, the goodness / badness determination unit 332 performs a re-determination of the goodness / badness of multiple inspection items based on the updated reference value. For example, the goodness / badness determination unit 332 compares the updated reference value in step S1040 with the error value, and re-determines whether each of the multiple inspection items is good or bad. In addition, the goodness / badness determination unit 332 identifies the inspection items among the multiple inspection items that have been re-determined incorrectly. Furthermore, the determination result generation unit 336 displays the updated reference value and the number of inspection items that have been re-determined incorrectly on the inspection result chart.

[0135] exist Figure 10 In the steps shown, some steps may be omitted, or two or more steps may be performed simultaneously, and the order of implementation between steps may be changed. Furthermore, the method for adjusting the criteria for determining whether an inspected object is good has been described through specific embodiments, but the method can also be embodied in computer-readable code on a computer-readable recording medium. A computer-readable recording medium includes all types of recording devices that store data readable by a computer system. Computer-readable recording media may include ROM (Read-Only Memory), RAM (Random Access Memory), CD-ROM (Read-Only Optical Disc Drive), magnetic tape, floppy disk, optical data storage devices, etc. Additionally, the computer-readable recording medium is distributed across a network-connected computer system, storing and running computer-readable code in a distributed manner. Moreover, the functional programs, code, and code snippets required to embody the described embodiments can be readily derived by a programmer skilled in the art to which this disclosure pertains.

[0136] This disclosure has been described and illustrated through preferred embodiments, but those skilled in the art will understand that various modifications and alterations can be made without departing from the scope and subject matter of the appended claims.

Claims

1. A method for adjusting a pass / fail judgment condition of an inspection object in a pass / fail judgment device, characterized by, comprising: a step of obtaining a measurement value of a structure of each of a plurality of inspection bodies; a step of comparing the measurement value of the structure of each of the plurality of inspection bodies with a design value of the structure of each of the plurality of inspection bodies, and calculating an error value of each of the plurality of inspection bodies; a step of respectively determining each of the plurality of inspection bodies as good or bad based on a reference value set for determining whether the plurality of inspection bodies are good or not and the error value of each of the plurality of inspection bodies; a step of identifying one or more inspection bodies in which a determination error occurs among the plurality of inspection bodies; a step of generating and displaying a first GUI object representing the reference value, a number of one or more inspection bodies in which the determination error occurs, and a graph representing a result of respectively determining each of the plurality of inspection bodies as good or bad; a step of determining at least one candidate reference value that reduces the number of one or more inspection bodies in which the determination error occurs; a step of displaying at least one second GUI object representing the at least one candidate reference value on the graph; a step of receiving a user input for selecting one of the at least one second GUI object; and a step of updating the reference value with a value corresponding to a position of a third GUI object selected from the at least one second GUI object according to the user input.

2. The method according to claim 1, wherein the user input includes: at least one of a graphical input for moving a position of the first GUI object in the graph and an input for specifying a position to which the first GUI object is to be moved in the graph. comprising:

3. A method of performing a good-or-not decision on an inspection object in a good-or-not decision device, characterized by, a step of obtaining a measurement value of a structure of each of a plurality of inspection bodies; a step of comparing the measurement value of the structure of each of the plurality of inspection bodies with a design value of the structure of each of the plurality of inspection bodies, and calculating an error value of each of the plurality of inspection bodies; a step of respectively determining each of the plurality of inspection bodies as good or bad based on a reference value set for determining whether the plurality of inspection bodies are good or not and the error value of each of the plurality of inspection bodies; a step of identifying one or more inspection bodies in which a determination error occurs among the plurality of inspection bodies; a step of determining at least one candidate reference value that reduces the number of one or more inspection bodies in which the determination error occurs based on a measurement value of at least one inspection body determined as good and a measurement value of at least one inspection body determined as bad among the plurality of inspection bodies; and a step of displaying a result graph including the reference value and the at least one candidate reference value, and representing a result of respectively determining each of the plurality of inspection bodies as good or bad. further comprising:

4. The method of claim 3, wherein, a step of displaying a GUI object representing the reference value on the result graph; a step of receiving a user input for moving a position of the GUI object; a step of updating the reference value with a value corresponding to the position of the GUI object moved according to the user input; a step of respectively determining each of the plurality of inspection bodies as good or bad again based on the updated reference value. ​ 5. The method according to claim 4, wherein the step of rejudging includes: a step of identifying a number of the inspection bodies in which a rejudging error occurs; and a step of displaying the updated reference value and the number of the inspection bodies in which the rejudging error occurs on the result chart.

6. A method of performing a good-or-not decision on an inspection object in a good-or-not decision device, characterized by, includes: a step of obtaining a measured value of a structure of each of a plurality of inspection bodies; a step of comparing the measured value of the structure of each of the plurality of inspection bodies with a designed value of the structure of each of the plurality of inspection bodies, and calculating an error value of each of the plurality of inspection bodies; a step of individually judging each of the plurality of inspection bodies as good or bad based on a reference value set for judging whether the plurality of inspection bodies are good or not and the error value of each of the plurality of inspection bodies; a step of identifying one or more of the plurality of inspection bodies in which a judging error occurs, the judging error including a first error in which an inspection body judged as good is identified as bad and a second error in which an inspection body judged as bad is identified as good; a step of deciding at least one candidate reference value that minimizes the number of the one or more of the plurality of inspection bodies in which the judging error occurs, based on a measured value of at least one of the plurality of inspection bodies judged as good and a measured value of at least one of the plurality of inspection bodies judged as bad; and a step of displaying a result chart including the reference value and the at least one candidate reference value, and representing a result of individually judging each of the plurality of inspection bodies as good or bad.

7. The method according to claim 6, wherein the step of deciding the at least one candidate reference value includes: a step of deciding the at least one candidate reference value that minimizes the number of the one or more of the plurality of inspection bodies in which the judging error occurs, based on a distribution of the calculated error value of each of the plurality of inspection bodies.

Images