User Interface for Judgment Concerning Quality Classification of Displayed Arrays of Component Carriers

Abstract

A method of processing component carriers includes supplying a plurality of arrays, each comprising a plurality of component carriers, to a human operator for optical inspection, displaying a respective array on a display, and providing a user interface enabling the human operator to input a judgment concerning a quality classification of a displayed array without a mandatory manual handling of the array by the human operator.

Claims

1. A method of processing component carriers, comprising: supplying a plurality of arrays, each comprising a plurality of component carriers, to a human operator for optical inspection; displaying a respective array on a display; and providing a user interface enabling the human operator to input a judgment concerning a quality classification of a displayed array without a mandatory manual handling of the array by the human operator.

2. The method according to claim 1, further comprising: providing an option for the human operator for exceptionally manually handling the array on exceptional request.

3. The method according to claim 1, further comprising: making an automated proposal concerning the quality classification as a basis for the judgment.

4. The method according to claim 3, further comprising: displaying the automated proposal to the human operator, in particular offering the human operator to accept or to refuse the automated proposal.

5. The method according to claim 1, comprising at least one of the following features: wherein the method comprises carrying out the quality classification to classify a respective individual component carrier or an entire array as pass; wherein the method comprises carrying out the quality classification to classify a respective individual component carrier or an entire array as fail; wherein the method comprises carrying out the quality classification to classify a respective individual component carrier or an entire array as repairable or as to be repaired.

6. The method according to claim 1, further comprising: displaying an image of the array on the display, in particular a zoomed image of the array.

7. The method according to claim 6, further comprising: displaying on the display an image of the array in which at least one component carrier is marked as identified to be defective in a previous processing stage.

8. The method according to claim 7, further comprising: displaying on the display an image of the array in which at least one component carrier is marked as automatedly proposed to be defective in a present processing stage.

9. The method according to claim 8, further comprising: displaying on the display said image of the array in which at least one component carrier is marked as identified to be defective in the previous processing stage overlaid with said image of the array in which at least one component carrier is marked as automatedly proposed to be defective in the present processing stage.

10. The method according claim 1, wherein the optical inspection is carried out at a remote location, which differs from a processing location of the plurality of arrays, in particular from a location where the displayed array is repaired, if identified as defective and repairable.

11. The method according to claim 1, further comprising: displaying on the display at least one of the group consisting of an array identifier, defect codes, and a control field, in particular for controlling loading or unloading an array, for controlling exceptionally manually handling an array, and/or for controlling zooming an array.

12. The method according to claim 1, further comprising: carrying out the quality classification so as to indicate a type of defect among a number of predefined types of defect for at least one of the component carriers or for an entire array.

13. The method according to claim 1, further comprising: marking, in particular laser marking, a respective component carrier or an entire array based on the quality classification according to the judgment.

14. The method according to claim 1, comprising at least one of the following features: wherein the method comprises carrying out the optical inspection during back-end processing; wherein the method comprises carrying out the optical inspection by handling the arrays in a touchless way; wherein the method comprises carrying out the optical inspection in combination with a traceability system in which each array and/or each component carrier is provided with a readable code structure assigned to a related data set stored in a database for identifying each array and/or each component carrier by an assignment between a respective code structure and a respective data set; wherein the judgment is at least one of a human-based judgment and a machine-based judgment.

15. An apparatus for optical inspection of component carriers of arrays, comprising: a supply unit configured for supplying a plurality of arrays, each comprising a plurality of component carriers, to a human operator for optical inspection; a display configured for displaying a respective array to the human operator; and a user interface configured for enabling the human operator to input a judgment concerning a quality classification of a displayed array without a mandatory manual handling of the array by the human operator.

16. The apparatus according to claim 15, further comprising: a quality classification proposal unit configured for making a proposal concerning quality classification to be displayed to the human operator on the display as decision-making support for the judgment.

17. The apparatus according to claim 16, wherein the quality classification proposal unit is configured for making the proposal by applying artificial intelligence, wherein in particular the quality classification proposal unit applying artificial intelligence is configured for learning based on historical judgments, in particular under consideration of a comparison of historical apparatus-proposed judgments with historical judgments.

18. The apparatus according to claim 16, wherein the user interface is configured for enabling the human operator to selectively accept or overrule the proposal.

19. The apparatus according to claim 15, comprising at least one of the following features: wherein the display comprises an input device, in particular a touchscreen, for enabling the human operator to operate, in particular only, via the input device; an optical detection unit configured for detecting image data of a respective array to be optically inspected, wherein the image data is to be supplied to the display as a basis for displaying an image of the respective array; at least one processor configured to display a respective array on a display; and providing a user interface enabling the human operator to input a judgment concerning a quality classification of a displayed array without a mandatory manual handling of the array by the human operator.

20. A program element for processing component carriers, which program element, when being executed by one or a plurality of processors, is adapted to carry out or control a method comprising: supplying a plurality of arrays, each comprising a plurality of component carriers, to a human operator for optical inspection; displaying a respective array on a display; and providing a user interface enabling the human operator to input a judgment concerning a quality classification of a displayed array without a mandatory manual handling of the array by the human operator.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0058] FIG. 1 schematically illustrates an apparatus for optical inspection of component carriers of an array during processing component carriers according to an exemplary embodiment of the invention.

[0059] FIG. 2 illustrates a plan view of an apparatus for optical inspection of component carriers of an array during processing component carriers according to an exemplary embodiment of the invention.

[0060] FIG. 3 illustrates a display and a user interface of an apparatus for optical inspection of component carriers of an array during processing component carriers according to an exemplary embodiment of the invention.

[0061] FIG. 4 illustrates in detail a display and a user interface of an apparatus for optical inspection of component carriers of an array during processing component carriers according to another exemplary embodiment of the invention.

[0062] FIG. 5 illustrates a display and a user interface of an apparatus for optical inspection of component carriers of an array during processing component carriers according to still another exemplary embodiment of the invention.

[0063] FIG. 6 illustrates a flowchart of a method of processing component carriers according to an exemplary embodiment of the invention.

[0064] FIG. 7 illustrates a flowchart of a method of processing component carriers according to another exemplary embodiment of the invention.

DETAILED DESCRIPTION OF THE ILLUSTRATED EMBODIMENTS

[0065] The illustrations in the drawings are schematically presented. In different drawings, similar or identical elements are provided with the same reference signs.

[0066] Before referring to the drawings, exemplary embodiments will be described in further detail, some basic considerations will be summarized based on which exemplary embodiments of the invention have been developed.

[0067] According to an exemplary embodiment of the invention, a system and method are provided enabling an inspection of arrays comprising multiple component carriers or preforms thereof without a need that an operator manually handles the arrays. In contrast to this, a quality classification judgement is made by the human operator preferably only via a display and a user interface displaying the array and component carrier on the basis of which a decision has to be made. The human operator may then visually inspect the array displayed via the display and may operate the user interface for making a quality classification of the individual component carriers or preforms thereof, or of the array as a hole. While the machine may make a defect proposal, the final decision concerning quality classification may be up to the human operator. While there may be an option to exceptionally handle arrays on request of the human operator, the method and system may be carried out and operated without the mandatory need of a user touching and handling the arrays or component carriers. Consequently, the risk of damage (for instance scratching) of the preforms of the component carrier may be reduced. Furthermore, by involving artificial intelligence during the machine-based proposal concerning the presence or absence of defects of a respective component carrier, a more reliable quality classification can be carried out. Since the human operator may accept or reject said machine-based proposals, this information is meaningful learning material for an artificial intelligence system of the apparatus for making more and more meaningful proposals.

[0068] Thus, an exemplary embodiment of the invention provides a smart automated final inspection system. Application cases of manufacturing component carriers on panel level and separating the panel into arrays may involve a high number of component carriers per strip or array. Thus, the requirements for an at least semi-automated final inspection system may be increased. According to an exemplary embodiment of the invention, such a system may be fully automated with a loader/unloader system to prevent additional defects on the component carriers. Furthermore, such a system may also improve the human naked eye inspection capabilities by providing additional optical enhancements. At the same time, the final optical inspection may be equipped with a smart software-based system which may help a human operator to make a reliable and objective judgement of the quality of the component carriers, so that human errors may be reduced.

[0069] In particular advantageous may be the combination of such a semi-automatic final optical inspection with an electronic mapping or traceability system in which the various arrays displayed on a display of the system may be provided with a unique identifier, allowing to trace the arrays and individual component carriers along an entire manufacturing process.

[0070] It may be in particular advantageous to implement artificial intelligence in such a system to help a human operator in a final inspection process. Integrating such a concept in an electronic mapping or traceability system may allow full traceability in order to better monitor the entire manufacturing process. Advantageously, a touchless system may be provided improving back-end testing of component carriers yield significantly.

[0071] According to an exemplary embodiment, a smart automated final inspection system may be provided which increases reliability and efficiency by reducing human-based failure issues while simultaneously focusing on human capability of failure detection.

[0072] Conventionally, a fully manual handling and preparation in quality classification of component carriers on array level may cause certain defects such as scratching. Furthermore, a higher rate of human errors may occur due to a bigger number of component carriers per strip shaped array which may involve a higher risk of wrong judgment. Another conventional issue is the lack of a properly working electronic tracking system of tracing component carriers during manufacture. In conventional array inspection systems involving manual handling of arrays of component carriers by a human operator, errors may also occur as a result of a limited and discrete visual access to the component carriers or details thereof during inspection.

[0073] According to exemplary embodiment of the invention, an improved optical inspection of component carriers on array level may be provided in which at least part of the above-mentioned and/or other shortcomings may be overcome by rendering a manual inspection of the arrays optional rather than mandatory, i.e. by providing an inspection architecture which does not necessarily rely on a manual handling of the arrays by human operators. In one embodiment, exceptional manual handling of an array by human operators may be allowed only exceptionally on exceptional request. In another embodiment, manual handling of arrays by a human operator may be even entirely disabled.

[0074] In particular, an electronic mapping concept may be implemented which may be advantageously accompanied by an XML (Extensible Markup Language) file capability. Moreover, it may be possible to enhance reliability of human operator judgment abilities by combining them with a smart artificial intelligence (AI) function. Furthermore, a touchless array handling and testing architecture may be provided. Such an automated touchless handling may advantageously increase yield. Also, as a result of an enhanced judgement using artificial intelligence, yield and accuracy may be increased, and inspection time may be decreased. Moreover, full traceability may be supported through an electronic mapping functionality which may increase efficiency, and which may simplify and accelerate judgment. Furthermore, it may be possible to provide on demand quality reports, Exemplary embodiments may also contribute to the reduction or even minimization of human errors for arrays with a high number of component carriers per array, which will further increase yield and accuracy.

[0075] Exemplary embodiments of the invention may be applicable in particular for high density integration (HDI), modified semi-additive processing (mSAP) and integrated circuit (IC) based products, i.e. in particular for all manufacturing procedures implementing a final inspection stage. More specifically, exemplary embodiments may be advantageous for any kind of module products with small unit size and high number of units per strip or array. Exemplary embodiments of the invention may provide improvements concerning monitoring in a back-end production line and may also contribute to estimating trends of up-coming tasks. An advantageous aspect of exemplary embodiments is the implementation of the concept of electronic mapping in combination with an enhanced judgement function based on artificial intelligence (AI). In contrast to conventional approaches, exemplary embodiments may provide enhanced judgment abilities due to the implementation of AI. In particular, exemplary embodiments may decrease any potential process related defect and human misjudgment and may therefore increase overall yield during manufacture of component carriers.

[0076] FIG. 1 illustrates a block diagram of an apparatus 120 for optical inspection of component carriers 100 of an array 102 during processing component carriers 100 according to an exemplary embodiment of the invention.

[0077] Apparatus 120 serves for an optical inspection and a corresponding quality classification of component carriers 100 which still form integral part of an array 102 during processing the same in a manufacturing plant. The apparatus 120 comprises a supply unit 122 configured for supplying a plurality of arrays 102 received from a previous processing stage 130 to a schematically illustrated human operator 118 for optical inspection in a present processing stage 132. After said optical inspection, the arrays 102 may be forwarded to a subsequent processing stage 144 for further processing.

[0078] Furthermore, a display 104 is provided which is configured for displaying an image of a respective array 102, detected by optical detection unit 146, to the human operator 118. Additionally, apparatus 120 comprises a user interface 106 configured for enabling the human operator 118 to input a judgment concerning a quality classification of a displayed array 102 without the need to mandatorily manually handle and touch the array 102 by the human operator 118.

[0079] Moreover, apparatus 120 includes a quality classification proposal unit 124 configured for making an automated proposal concerning quality classification. Said proposal may be displayed to the human operator 118 on the display 104. Advantageously, the quality classification proposal unit 124 may be configured for making the proposal by applying artificial intelligence (AI). An artificial intelligence module of the quality classification proposal unit 124 may be configured for learning based on historical judgments, preferably under consideration of a comparison of historical apparatus-proposed judgments with historical judgments.

[0080] The user interface 106 may be configured for enabling the human operator 118 to selectively accept or overrule the machine-made proposal. Furthermore, the display 104 may comprise a touchscreen 114 for enabling the human operator 118 to operate fully via the touchscreen 114.

[0081] A processor 134 or control unit of the apparatus 120 may control overall operation of the apparatus 120 as a whole. The processor 134 may have access (in particular read and write access) to a database 140. In particular, such a processor 134 or control unit may be configured to carry out a method as described in the following.

[0082] In terms of said method of processing component carriers 100, the plurality of arrays 102, each comprising a plurality of component carriers 100, are supplied to a human operator 118 for optical inspection. The method may further comprise displaying a respective array 102 on display 104. Moreover, user interface 106 may enable the human operator 118 to input a judgment concerning a quality classification of a displayed array 102 without a mandatory manual handling of the array 102 by the human operator 118. Additionally, the method may comprise providing the option to human operator 118 for exceptionally manually handling the array 102 on exceptional request by the human operator 118. It may also be possible to make an automated proposal concerning the quality classification as decision-making support for simplifying a quality classification made by the human operator 118. Furthermore, the method comprises displaying the automated proposal concerning the quality classification to the human operator 118 on display 104. For instance) it may be possible in the context of the optical inspection to carry out the quality classification to classify a respective individual component carrier 100 or an entire array 102 as “pass”, “fail”, or “to be repaired”. It may also be possible to display, on display 104, a zoomed image of the array 102 to further assist the human operator 118 to assess the quality of an array 102 or an individual component carrier 100. Carrying out the quality classification may be accomplished by indicating a type of defect among a number of predefined types of defect, in particular when an array 102 or a component carrier 100 is classified as “fail” or “to be repaired”. The method may also comprise laser marking a respective component carrier 100 or an entire array 102 based on the quality classification, in particular in accordance with the classification as “fail”. The optical inspection may be carried out during back-end processing, i.e. on array level. During executing the method, it may be advantageously possible to carry out the optical inspection by handling the arrays 102 in a touchless way. Advantageously, the method may carry out the optical inspection in functional cooperation with a traceability system in which each array 102 and/or each component carrier 100 is provided with a readable code structure 136 (such as a QR code) assigned to a related data set 138 stored in database 140. Reading out a code structure 136 and querying database 140 for finding a best match with one of the data sets 138 may allow identifying each array 102 and/or each component carrier 100 via the assignment between a respective code structure 136 and a respective data set 138.

[0083] According to the apparatus 120 shown in FIG. 1, arrays 102 comprising a plurality of still integrally connected preforms of component carriers 100 may be supplied by supply unit 122 from previous processing stage 130 to present processing stage 132. As shown in the schematic illustration of the array 102 in FIG. 1, each component carrier 100 or preform thereof and/or each array 102 (not shown) may be provided with a respective code structure 136 such as a QR code (or any other machine-identifiable code structure, for instance visually, haptically, thermally and/or electrically identifiable). Each code structure 136 is assigned to a corresponding data set 138 in database 140 which can be accessed by control unit or processor 134, as well as of certain entities of previous processing stage 130, present processing stage 132 and subsequent processing stage 144. The code structures 136 have been formed on and/or attached to a respective pre-form of a component carrier 100 or to the entire array 102 during the manufacturing process. For instance, a respective code structure 136 may be a unique QR code formed by patterning a corresponding copper layer laminated to a layer stack forming the respective component carrier 100. By detecting a respective code structure 136, for instance by optical detection unit 146, may allow determining information about a respective preform of a component carrier 100 by accessing in database 140 an assigned data set 138, being assigned to an individual code structure 136. Thus, the illustrated system of quality classification of preforms of component carriers 100 may be integrated in a traceability system. The optical detection unit 146 may comprise a camera capturing an image of the array 102 and processing a corresponding image. This processing may be carried out on the basis of, on the one hand, identifying the array 102 or an individual preform of a component carrier 100 by correlation of respective code structure 136 and a respective data set 138 in the database 140. Furthermore, it is also possible that the image of the array 102 captured by the optical detection unit 146 may be processed so as to display it on display 104, as described below in further detail. A corresponding processing of image data detected by optical detection unit 146 may also be made as a basis for a proposal concerning a quality classification of a respective array 102 or preform of a component carrier 100 by quality classification proposal unit 124, as described below as well.

[0084] During operation of the apparatus 120, a respective array 102 is supplied by supply unit 122 automatically from previous processing stage 130 to present processing stage 132. An image of the array 102 is captured by optical detection unit 146. This image is used for identifying the panel 102 or the individual preforms of component carriers 100 based on detecting the respective code structure 136 and assigning it to a respective data set 138 in database 140. Furthermore, the image of the array 102 may be supplied to the quality classification proposal unit 124 as a basis for making a proposal concerning quality classification of the array 102 or its component carriers 100. Quality classification proposal unit 124 may carry out automatic image recognition to determine various features of the array 102. Furthermore, the quality classification proposal unit 124 may use artificial intelligence for making the quality decision. For instance, the quality proposal made by quality classification proposal unit 124 may be that a specific component carrier 100 is classified as “pass”, “fail” or “repair”. Passing means that the respective component carrier 100 is accepted as meeting a specification. Failing means that a respective component carrier 100 may be considered to fail meeting a specification. Repair means that it is possible to repair the respective component carrier 100, presently not meeting the specification, to meet the specification after repair.

[0085] The image of the array 102 together with its identification data derived from a corresponding data set 138 is then displayed on display 104, for instance a liquid crystal display (LCD) with touchscreen functionality. The captured image of the array 102 together with identifier information of the described system may be displayed on display 104, for instance in a way as shown in FIG. 3 to FIG. 5. The human operator 118 may inspect the array 102 on the display 104 and may confirm or reject the corresponding quality proposal made by quality classification proposal unit 124. In order to improve the (for instance neural network based) artificial intelligence system of the quality classification proposal unit 124, a data exchange between the quality classification proposal unit 124 and the user interface 106 may be advantageous, see feedback loop 148. For instance, it can be meaningful for learning of the self-adaptive neural network system of the quality classification proposal unit 124 in which cases a human operator 118 has accepted and in which cases the human operator 118 has refused the quality classification proposal.

[0086] As indicated by a communication line 150, the human operator 118 may exceptionally instruct the supply unit 122 to physically supply the array 102 for manual handling and touching by the human operator 118. For instance, the human operator 118 may make such an exceptional request for dedicated quality analysis of critical arrays 102 or component carriers 100. However, apart from such highly exceptional cases, the apparatus 120 works in a touchless way without manual handling of the arrays 102 by the human operator 118. Thereby, the risk of scratches or the like on the array 102 may be reduced. After the quality classification, the array 102 may proceed to the next or subsequent processing stage 144.

[0087] FIG. 2 illustrates a plan view of an apparatus 120 for optical inspection of component carriers 100 of an array 102 during processing component carriers 100 according to an exemplary embodiment of the invention.

[0088] As shown in FIG. 2, the arrays 102 can be supplied to the apparatus 120 automatically by supply unit 122, i.e. a loader. The arrays 102 are then transported fully automatic to a first main table 160 and, after flipping (see reference sign 163) the arrays 102 by a flipper 162, to a second main table 164. When on the first main table 160, a human operator 118 can visually inspect an image of the array 102 via display 104 and may carry out a human based quality classification via user interface 106. A second operator 118 can do the same task when the array 102 lies on the second main table 164 and is displayed from a back side, on a further display 104. Via a further user interface 106, the second operator 118 may make a quality classification of the array 102 by backside inspection. Thereafter, the array 102 may be transported away from the apparatus 120 by an unloader 166. In an exceptional case, when the respective human operator 118, 118 needs to inspect the array 102 directly, the respective human operator 118, 118 may request the automatic handling system to put the array 102 physically on a respective working table 168, 170 for exceptional detailed inspection by the respective human operator 118, 118. However, in the majority of cases, the respective human operator 118, 118 carries out the quality classification without manually handling and touching the respective array 102. FIG. 2 furthermore shows, with reference numeral 172, a hook up and utilities of the apparatus 120.

[0089] As an alternative to the architecture shown in FIG. 2, the process can also be carried out by a single human operator 118 rather than by two cooperating human operators 118, 118. Thus, the described method can be carried out with one or two operators 118.

[0090] Flipper 162 can turn over an array 102 from one main table 160 to the other main table 162 or on the same table (for instance in a one-operator mode). In particular, a fully automated and touchless loader/unloader system may be provided. Such a system may be fully integrated in an electronic mapping system allowing for a tracing of each individual array 102 or component carrier 100 during manufacture. The illustrated apparatus 120 may have the ability to transfer an array 102 to the working tables 168, 170 for repair and/or for manual inspection. The illustrated apparatus 120 may ensure a shorter cycle time as compared to conventional approaches. Such an apparatus 120 may also be capable of preventing or at least suppressing human errors in a final inspection station for data input.

[0091] FIG. 3 illustrates a display 104 and a user interface 106 of an apparatus 120 for optical inspection of component carriers 100 of an array 102 during processing component carriers 100 according to an exemplary embodiment of the invention.

[0092] As illustrated in FIG. 3, it may be possible to display on the display 104 an array identifier 108, error codes 110, and one or more control fields 112, for instance for loading or unloading an array 102, for exceptionally manually handling an array 102, or for zooming an array 102.

[0093] More specifically, FIG. 3 shows a touchscreen interface for a human operator 118. On the left-hand side of the display 104, an array display area 174 is shown on which an image of an array 102 which is presently optically inspected may be displayed. Error codes 110 may be displayed as well, for instance as scarp code patterns. The array identifier 108 may show production data concerning the array 102 derived from the assigned code structure 136 in combination with the database 140, more specifically an assigned data set 138 thereof. Various control and operation buttons as well as loader and unloader controlling buttons may be displayed as control fields 112.

[0094] FIG. 4 illustrates details of a display 104 and a user interface 106 of an apparatus 120 for optical inspection of component carriers 100 of an array 102 during processing component carriers 100 according to an exemplary embodiment of the invention,

[0095] FIG. 4 shows that it may be possible to display on array display area 174 of the display 104 an image 102′ of the array 102 in which at least one component carrier 100 is marked with corresponding crosses as “identified to be defective” in previous processing stage 130 (see reference signs 175). In other words, image 102′ reflects the fact that certain component carriers (see reference numeral 175) have already been identified as defective in previous processing stage 130. An image of a respective component carrier 100 which is not defective is denoted in FIG. 4 with reference sign 100′. In other words, an image of a respective defective component carrier 100 is denoted in FIG. 4 with reference sign 175, whereas an image of a non-defective, i.e. defect-free, component carrier 100 is denoted in FIG. 4 with reference sign 100′.

[0096] In addition, it may be possible to display on the display 104 a further image 102″ of the same array 102 in which at least one component carrier 100 is marked with corresponding crosses as “automatedly proposed to be defective” in present processing stage 132 (see reference signs 177). Component carriers 100 marked in accordance with reference sign 177 of further image 102″ are thus proposed by quality classification proposal unit 124 as potentially defective in present processing stage 132. A human operator 118 however still has the option to overrule this proposal.

[0097] It may also be advantageously possible to display on the display 104 said image 102′ of the array 102 in which at least one component carrier 100 is marked as identified to be defective in the previous processing stage 130 overlaid or superposed with said further image 102″ of the array 102 in which at least one component carrier 100 is marked as automatedly proposed to be defective in the present processing stage 132. The result of such an overlay or superposition of images 102′, 102″ is displayed as an additional image 102′″. In additional image 102′″, all component carriers 100 considered defective in previous processing stage 130 (see reference sign 175) and all component carriers 100 considered defective in present processing stage 132 (see reference sign 177) are shown together in a very intuitive way in one common image 102′″. Images 100′ of said component carriers 100 corresponding to reference signs 175 and corresponding to reference signs 177 may however still be visually distinguished in common image 102′″.

[0098] Descriptively speaking, FIG. 4 shows the display 104 in more detail. In particular referring again to array display area 174, the described three images 102′, 102″, 102′″ of the array 102 and of the component carriers 100 (images shown as component carrier images 100′) are illustrated here. In the upper portion of array display area 174, the image 102′ of the array 102 is shown corresponding to a defect classification in previous processing stage 130. In previous processing stage 130, some of the electronic components 100 have already been classified as defective, as indicated by crosses 175. In a central portion of the array display area 174, image 102″ of the array 102 is shown which corresponds to a defect proposal in the present processing stage 132. As shown by crosses 177, specific ones of the component carriers 100 have been proposed to be defective by the quality classification proposal unit 124. In the lowermost portion of the array display area 174, both the defective component carriers 100 as identified in the previous processing stage 130 (see crosses 175) as well as the component carriers 100 which are proposed to be classified as defective in the present processing stage 132 (see crosses 177) are overlaid in common image 102′″. Thus, the human operator 118 may focus, in his assessment of the quality classification on the component carriers 100 according to crosses 177. Since they have already been finally classified as defective, the human operator 118 may disregard for the quality assessment the component carriers 100 corresponding to crosses 175. The other component carriers 100, which are neither marked with a cross 175 nor with a cross 177 have been accepted by the apparatus 120 as pass, and this decision may be reviewed by the human operator only if desired or required in view of specific circumstances. Thus, in particular the image 102′″ of the lower portion of array display area 174 is highly intuitive for a human operator 118 and significantly simplifies the human-based quality classification, which can thereby also be rendered more accurate. Thus, an improved yield and a reduced number of false quality classifications may be achieved.

[0099] As can be taken from FIG. 4, an array defect history may be taken into account, for instance by making use of electronic mapping data of previous inspection stations. An actual image from an array 102 showing potential new defects may be determined and displayed. Advantageously, there may be the option to zoom in each unit or component carrier 100 of an array 102. It may be possible to prevent showing previously scrapped units again which may result in a shorter cycle time and the prevention of double scrap issues. In a first section, a human operator 118 can zoom in on each machine suggested defect to see it better and then decide if it is a real defect to not. After defect confirmation by the human operator 118, the software-based system may ask the human operator 118 to assign a scarp code to this defect, for instance by making a selection from provided scrap codes buttons (see reference signs 110 in FIG. 3 and FIG. 4).

[0100] The two overlaid images 102′ and 102″ shown as further image 102′″ in FIG. 4 show a combination of already confirmed failed units and potentially new failed units or component carriers 100. In the overlaid section corresponding to further image 102′″, the system may show an overall defect mapping of the component carriers 100 of an array 102 and may ask the human operator 118 to confirm (or reject). The system may then automatically save this information, for instance in an XML file of a file server which may be used in a later process for laser marking of defective units or component carriers 100.

[0101] FIG. 5 illustrates a display 104 and a touchscreen-based user interface 106 of an apparatus 120 for optical inspection of component carriers 100 of an array 102 during processing component carriers 100 according to still another exemplary embodiment of the invention.

[0102] In the alternative display content shown in FIG. 5, the array display area 174 only shows the overlaid result from the previous processing stage 130 and the present processing stage 132, i.e. only shows image 102′″.

[0103] FIG. 6 illustrates a flowchart 200 of a method of processing component carriers 100 according to an exemplary embodiment of the invention.

[0104] FIG. 6 in particular shows a logical position of the apparatus 120 according to an exemplary embodiment of the invention in the entire process flow during processing the component carriers 100. An automatic visual inspection is carried out in a block 202 by a machine, i.e. in a fully automated way. This may be followed by a manual verification process, see block 204. After that, the apparatus 120 and the method, as described above, may be implemented and carried out. Thereafter, see block 206, defective component carriers 100 of an array 102 may be provided with a corresponding physical mark, for instance by laser marking. This may take place based on the finalized decision or consolidated data set on faulty component carriers that may be obtained in the process according to reference numeral 204. Thereafter, a cleaning procedure may be carried out in a block 208, for instance for removing burr. This may be followed by a baking procedure carried out in block 210. Such a baking procedure may be done for dewarping, deoxidizing and further cleaning the component carriers 100. Subsequently, see block 212, a vacuum packing procedure may be carried out.

[0105] FIG. 7 illustrates a flowchart 250 of a method of processing component carriers 100 according to another exemplary embodiment of the invention.

[0106] Now referring to FIG. 7, an overview over a smart automated final inspection system according to an exemplary embodiment of the invention will be given. A progress of a process flow can be taken from reference numeral 252. Descriptively speaking, advantageous aspects of said automated final inspection system is an automated touchless handling 254, an enhanced judgement inspection 256 as well as the utilization of an electronic mapping or traceability system 258. Operation of apparatus 120 and method according to an exemplary embodiment of the invention may involve a fully automated loading on a main table and a flipping to the second side, as indicated by reference numeral 260. Furthermore, it is advantageous to carry out a touchless inspection of both array sides with different magnifications, if desired. For instance, the magnifications may be in a range from 1 to 100. This is indicated schematically by a block 262. Furthermore, it is possible to overlay electronic mapping data with final inspection generated images and skip previous defective units, see block 264. As indicated by block 266, suggestions to a human operator may be based on artificial intelligence for obtaining an enhanced judgement function. Furthermore, there is a possibility for repairing, cleaning and carrying out a naked eye check, see block 268. As indicated by a block 270, it may become simplified to define scrapped component carriers or arrays, preferably using predefined defect codes. An output may update a corresponding electronic mapping file, see data sets 138 in database 140.

[0107] It should be noted that the term “comprising” does not exclude other elements or steps and the article “a” or “an” does not exclude a plurality. Also, elements described in association with different embodiments may be combined.

[0108] Implementation of the invention is not limited to the preferred embodiments shown in the figures and described above. Instead, a multiplicity of variants is possible which variants use the solutions shown and the principle according to the invention even in the case of fundamentally different embodiments.