System for a reel quality control and method of reel inspection

Abstract

The present disclosure relates to a system and method of inspection of reels comprising electronic components. A system for a reel quality control comprising at least one image capture module (1), at least one image analysis module (2), at least one verification module (3) and at least one server (6) wherein each of the at least one image capture module (1), the at least one image analysis module (2), the at least one verification module (3) and at least one server (6) are connected through a communication bus (5). A method of reel inspection performed on this system comprising steps of: a. capturing, by an image capture module (1), an image of at least one tape with at least on component (9); b. analyzing, by an image analysis module (2), the image; c. validating, by a validation module (3), a reel with the tape where a result of an analysis in step b. indicates that the tape is defective.

Description

[0001] TITLE

[0002] System for a reel quality control and method of reel inspection

[0003] TECHNICAL FIELD

[0004] The present disclosure relates to a system and method of inspection of reels comprising electronic components.

[0005] BACKGROUND OF THE DISCLOSURE

[0006] The automatic inspection machine should be including three operation process that is image capture handler, image analysis and image validation. The image capture handler is carried the unit under the camera to capture the image, image analysis is using the captured image to determine the unit is pass or fail and the optional process is image validation that is human justification the image analysis is correct or not.

[0007] In traditional method, the ratio of each process is 1 :1 , and the image capture handler normal with variation speed due to different pitch size of the carrier tape, if the system design with fix PC resource image analysis pool, it will cause unbalance loading for the image capture handling pool and image analysis pool.

[0008] Document KR101772673B1 discloses a multi-optic module vision inspection system, and more particularly, to a multi-optical module vision inspection system, which includes a dustproof device having an air cylinder structure for vibration reduction and a stage unit transfer module and a mechanical part for sample products having various shapes and sizes in the field of semiconductor materials and display materials In the inspection equipment, there is an effect of detecting surface defects (foreign objects, scratches, pattern errors, etc.) of the inspection target product by using optical illumination and vision inspection system and judging whether or not the product is defective, thereby reducing defective products in the production process.

[0009] Document KR101772673B1 discloses a machine-vision system for monitoring a quality metric for a product. The system includes a controller configured to receive a digital image from an image acquisition device. The controller is also configured to analyse the digital image using a first machine-vision algorithm to compute a measurement of the product. The system also includes a vision server connected to the controller, and configured to compute a quality metric and store the digital image and the measurement in a database storage. The system also includes a remote terminal connected to the vision server, and configured to display the digital image and the quality metric on the remote terminal.

[0010] Accordingly, it is a goal of the present disclosure to provide a new image inspection topology system that may be share the image analysis resource pool with different image capture handler, to obtain this inspection topology, it need to split those three process into three different module, to make the image capture handler resources pool, image analysis resource pool and image validation resource pool, it may separate to expand base on the install base of the machine, it may be fully utilize the each module resources base on the loading. The new system overcomes disadvantages of prior art solution, namely slow Inspection speed when high defect rate happens, single point of failure where one part of hardware fail, the entire system become inaccessible, lack of ability to fully utilize the machine where one process on hold will cause that the whole machine will be on hold, and lack of flexibility for the production ramp up where to upgrade there is a need to buy full set of machines, which cause the waste of machine resource.

[0011] SUMMARY OF THE DISCLOSURE

[0012] According to a first example of the disclosure, a system for a reel quality control is disclosed which comprising at least one image capture module, at least one image analysis module, at least one verification module and at least one server wherein each of the at least one image capture module, the at least one image analysis module, the at least one verification module and at least one server are connected through a communication bus.

[0013] Preferably each of the at least one image capture module, the at least one image analysis module, the at least one verification module are a separate device.

[0014] Preferably the system is configured such that at least two of the image capture modules are dedicated to analyze one production line.

[0015] According to a second example of a disclosure a method of reel inspection performed on a system is disclosed. The method comprising steps of a. capturing, by an image capture module, an image of at least one tape with at least on component; b. analyzing, by an image analysis module, the image; c. validating, by a validation module, a reel with the tape where a result of an analysis in step b. indicates that the tape is defective. Preferably each module receives information regarding a manufacturing machine ID, a Reel ID, a type of task or data being processed, and / or metadata.

[0016] Preferably the image is stored in the image capture module which captured the image.

[0017] Preferably the image is stored on the server.

[0018] Preferably the at least one image analysis module and / or the at least one verification module are sending a message to the server, wherein the message indicates the at least one image analysis module and / or the at least one verification module are capable to receive a next task.

[0019] Preferably at least one module type the image capture module, the image analysis module, and the verification module.

[0020] BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The disclosure will now be discussed with reference to the drawings, which show in:

[0022] Figure 1 a system known from the prior art,

[0023] Figure 2 an overview concept of a system according to the present disclosure,

[0024] Figure 3 an exemplary system according to the present disclosure,

[0025] Figure 4 a capture image of a tape from a reel,

[0026] Figures 5 and 6 an image analysis module workflow,

[0027] Figure 7 an image capture module workflow,

[0028] Figure 8 a validation module workflow.

[0029] DETAILED DESCRIPTION OF THE DISCLOSURE

[0030] For a proper understanding of the disclosure, in the detailed description below corresponding elements or parts of the disclosure will be denoted with identical reference numerals in the drawings.

[0031] A typical inspection machine or inspection module 4 comprises three modules, namely an image capture module 1 , an image analysis module 2, and a validation module 3 as it is shown in fig. 1. In such a machine a ratio between the image capture module 1 , the image analysis module 2, and the validation module 3 is always 1 :1 :1. Such solution is easy to implement since there is only a need to buy one machine, but in the case of uneven distribution of errors, reels to be checked etc. it is not possible to share capacity of each module between different machines so one machine may stay idle while other is working at the highest speed possible. It should also be noted that a malfunction of one module will cause that the whole production line will be stopped.

[0032] A present disclosure aims to overcome abovementioned disadvantages by splitting the inspection module 4 and thus an inspection process into three separate modules, namely the image capture module 1 , the image analysis module 2, and the validation module 3. A general concept is shown in Fig. 2 where each of the capture modules 1 is able to communicate with each of the image analysis module 2, and each of the image analysis module 2 is able to communicate with the validation module 3. There is no typical ratio between each module type. If needed this system is flexible to upgrade and expand. The risk of stopping the manufacturing process with a single failure is reduced, in some cases limited.

[0033] The system according to the present disclosure is characterized with following advantages:

[0034] • High availability: the image capture module 1 may distribute the workload and provide redundancy. If the image analysis module 2 fails, the others may continue to handle requests, ensuring high availability and minimizing downtime. This fault tolerance is particularly crucial for critical applications or services that require continuous operation.

[0035] • Scalability: distributed services architectures may easily scale by adding more modules as needed. As a workload increases, new modules may be added to handle an additional workload, ensuring efficient resource utilization and accommodating growing demands.

[0036] • Load balancing: with multiple modules, the workload may be balanced across the computer resources in the cluster. Load balancing algorithms may distribute incoming requests evenly, optimizing resource utilization and preventing any single module from becoming overwhelmed. This leads to improved performance and responsiveness.

[0037] • Performance improvement: by distributing the workload across multiple modules, the overall performance of the system may be enhanced. With more processing power, memory, and network bandwidth available, the system may handle a larger number of concurrent requests and provide faster response times. • Fault isolation: if the module in the system fails or experiences issues, the impact is limited to that module only. Other modules in the cluster may continue to function, ensuring fault isolation and minimizing the impact on the overall system. It should be noted that two of the image capture modules (1) are designated to capture images from a single production line so that, in the case of a failure of one of those image capture modules (1) the other one will still be able to capture images and the quality control will not stop.

[0038] Fig. 3 shows a schematic system according to the disclosure, wherein the track-in and track-out system is integrated into the system process flow. Track-In - all the process unit within the system start the task, it may request the central database with relevant information. This information includes the machine ID, Reel ID, the type of task or data being processed, and the metadata such as image are store in, for example, the image capture module 2 or the server 6.

[0039] The server 6 serves as a repository for tracking the status and availability of modules within the system. It maintains a record of which modules are currently engaged in processing tasks and which ones are available for new assignments.

[0040] T ask Assignment - the image analysis modules 2 and the validation modules 3 pick tasks on a basis of their own workload and query the server 6 and update a database in the server 6 (track-in).

[0041] Track-Out - once a process completes the task, it updates the database with the task status, results, and any relevant output data.

[0042] In the disclosed system there is a communication bus 5 to which the image capture modules 1 , the image analysis modules 2, the validation modules 3, and the server 6 are connected. It should be noted that the disclosure disclosed a plurality of modules and one server, however it should be noted that that any number of modules and servers 6, wherein there is at least one of the image capture module 1 , the image analysis module 2, and the validation module 3 will be sufficient to implement disclosed solution. It should also be noted that other topographies of the system may be implemented and the person skilled in the art will know how to connect each module and the server 6 into one working system.

[0043] In fig. 4 a typical view of a tape, which is wound on a reel, is shown. A carrier tape 7 comprises protrusions in which components 9 are placed and then a cover tape 8 seals the components 9 in place protecting them from falling of or being damaged. The image analysis module 2 analyses images obtained by the image capture module 2 and checks any relevant parameters, for example if the sealing 10 is made correctly, if index holes 11 have the right size, are in right place and are present, if leads 12 are present and have right dimensions, and finally components 9 are checked - and a product code 13 and outline 14 are verified. Additionally it is also checked if there is any foreign material which should not be there. It should be noted that those parameters are just an exemplary one and different components 9 may need different sets of parameters. The person skilled in the art will know which parameters are required for each type of electronic component. If any parameter fall outside the specified limits, the product is considered defective and must be rejected. The user is responsible for justifying and addressing the defect at the validation module 3 before allowing the product to be released.

[0044] Fig. 5 and 6 show a workflow of the image analysis module 2. The image analysis module 2 first checking own CPU / RAM resources to determine able to start the new analyser process. From the query of all the products waiting for analysis process from the server 6 one task is picked and track-in into the server 6, track-in process gets all the necessary information from the server 6 (such as reel-id, analyser parameter and an image storage location) and change the status as “Analysing”. Next the threading process for image analysis is created, and it go back resource checking process to check still have resource for the next analysis process. When the image analysis process is done, track-out is performed to the database and a status is changed to “Analyzer Completed”. Finally a result mapping from all the image inspection result is created.

[0045] Fig. 7 shows a workflow of the image analysis module 2. It starts when trackin is successful when all the necessary information are filled. The unique ID for the product information is Reel ID under the central database record. A track-ln process in the image analysis module 2 creates the record in the database and update this product status as “Capturing”. After this track-in process either one of the image analysis module 2 picks the task and update this product status. When the capture process is done the image analysis module 2 track-out the record into central database and update the status as “Capture Complete”.

[0046] Fig. 8 shows a workflow of the validation module 3. At first Input ID is obtained to get the status and result mapping from the database. Next the validation module 3 track-in to the database to change the status as “Verification Start”. User then finalize the defect type and update as the result and the validation module 3 track-out to the database change of the status to “Verification Completed”. At the end of the verification process an update of the result to the database is made. LIST OF REFERENCE NUMERALS USED

[0047] 1 image capture module

[0048] 2 image analysis module

[0049] 3 validation module

[0050] 4 inspection module

[0051] 5 communication bus

[0052] 6 server

[0053] 7 carrier tape

[0054] 8 cover tape

[0055] 9 component

[0056] 10 sealing

[0057] 11 index hole

[0058] 12 lead

[0059] 13 product code

[0060] 14 outline

Claims

CLAIMS1. A system for a reel quality control comprising at least one image capture module (1), at least one image analysis module (2), at least one verification module (3) and at least one server (6) wherein each of the at least one image capture module (1), the at least one image analysis module (2), the at least one verification module (3) and at least one server (6) are connected through a communication bus (5).

2. The system according to claim 1 , wherein each of the at least one image capture module (1), the at least one image analysis module (2), the at least one verification module (3) are a separate device.

3. The system according to claim 1 or 2, wherein the system is configured such that at least two of the image capture modules (1) are dedicated to analyse one production line.

4. A method of reel inspection performed on a system from anyone of claim 1- 3 comprising steps of: a) capturing, by an image capture module (1), an image of at least one tape with at least on component (9); b) analyzing, by an image analysis module (2), the image; c) validating, by a validation module (3), a reel with the tape where a result of an analysis in step b. indicates that the tape is defective.

5. The method according to claim 4, wherein each module (1, 2, 3) receives information regarding a manufacturing machine ID, a Reel ID, a type of task or data being processed, and / or metadata.

6. The method according to claim 4 or 5, wherein the image is stored in the image capture module (1) which captured the image.

7. The method according to claim 4 or 5, wherein the image is stored on the server (6).

8. The method according to anyone of claim 4-6, wherein the at least one image analysis module (2) and / or the at least one verification module (3) are sending a message to the server (6), wherein the message indicates the at least one image analysis module (2) and / or the at least one verification module (3) are capable to receive a next task.

9. The method according to anyone of claim 4-7, wherein at least one module type the image capture module (1), the image analysis module (2), and the verification module (3).

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