TWI363963B - Automated abnormal machine tracking and notifying system and method - Google Patents

Description

363963. IX. Description of the Invention: [Technical Field] The present invention relates to a system and method for abnormal automatic tracking and notification of a machine, in particular, an automatic tracking that can integrate different abnormal information and instantly reflect possible abnormal machines. And notification systems and methods. [Prior Art] _ Today's manufacturing industry, especially semiconductor fabs or LCD panel manufacturers, involves very complex and numerous manufacturing process steps. A product must be manufactured through different manufacturing machines, transfer handlers, storage machines, and after dozens or even hundreds of processes. Each process must undergo repeated tests and fine-tuning of parameters to achieve specific production requirements, while ensuring and controlling the various processes and products produced before mass production of real products or trial production of different technologies or products. quality. ® generally works in the quality control department of the production line, testing specific products produced by a specific process, and is engineered to out of control (OOC lot) or hold lot. Statistical process control report (statistical process contro SPC chart) or product wafer acceptance test (wafer acceptance test (WAT) data, etc., to find out the relationship between abnormal products and abnormal machines, to identify and diagnose possible Abnormal machine. However, this analysis method that targets products or processes often ignores the variation of some abnormal machines before they cause significant impact. Therefore, to 6 1363963, the abnormal state of the machine can not be found in time before the next lot enters the possible abnormal machine, resulting in loss of product yield and production cost. In addition, due to the large number of production and inspection tools used on the production line, different operators are usually only responsible for part of the production and testing tools, and most of the operators are performing quality control work in shifts. Although the manufacturing companies do not pass through a document management or electronic handover system, due to the different judgments on the results of human analysis, or the occurrence of missing handovers, etc., the single event or minor event that is misjudged is often triggered. Or expand into subsequent major anomalies, resulting in loss of product yield and production costs. It can be seen that how to automatically track and integrate different abnormal information of each process machine across each shift, and then automatically track and report the abnormal machine to improve the stability of the production process, it is worth studying. The issue. SUMMARY OF THE INVENTION Accordingly, it is an object of the present invention to provide a system and method for automatically tracking and reporting anomaly information that automatically integrates various process machines across shifts and that summarizes possible abnormalities. The patent application scope provided in accordance with the present invention provides an automated tracking and notification system for machine anomalies. The system comprises: a data acquisition and analysis subsystem for extracting a plurality of test results from 1363963 and integrating into a plurality of abnormal information; a machine state database for storing the abnormal information; An abnormality information computing device for respectively calculating an abnormality score of an individual possible abnormal machine according to the abnormal information and at least one related abnormal machine; and determining whether the sum of the abnormal scores of one of the individual abnormal machines is greater than The η value judging means, and when the sum of the abnormality scores is greater than the η value, it is judged that at least one user is to be notified. The system further includes an automatic notification subsystem for communicating the possible abnormal machine and associated abnormal information to the user. According to the patent application scope of the present invention, a method for automatically tracking and notifying the abnormality of the machine is provided. The method includes the following steps: First, a data acquisition and analysis subsystem automatically extracts a plurality of detection results and integrates and analyzes the plurality of abnormalities into a plurality of abnormal information, and the abnormal information is stored in a machine state database. Next, an abnormality information computing device is used to calculate the abnormality scores of the individual abnormal machines according to the abnormal information and the at least one related abnormal machine, and use a determining device to determine the sum of the abnormal scores of one of the individual abnormal machines. Whether it is greater than an η value. When the sum is greater than the value of η, an automatic notification subsystem is used to notify the at least one user of the possible abnormal machine and related abnormal information. The system and method for automatic tracking and notification of machine abnormalities according to the present invention, the abnormal information is obtained by the data extraction and analysis subsystem from 8 1363963

• Uncovering the results of the various stages of the online or offline, or using the input data 'and analyzing and integrating the test results and input data by the analysis and judgment device' and storing the abnormal information in the state of the machine In the database. When the sum of the scores calculated by the abnormal information is greater than the value of η, the possible abnormal machine and the related abnormal information are automatically notified to the user. Therefore, it can be seen that the method for automatic tracking and notification of the abnormality of the machine provided by the present invention can automatically track, statistically analyze and analyze the relationship between the abnormal information and the related machine, and summarize the machine that diagnoses the abnormal machine or the abnormal machine. And notify the user immediately. Moreover, since each step in the above method is completed by using the automatic tracking and notification system of the abnormal machine provided by the present invention, the influence of the manual operation and the deficiency of the user experience can be saved, so the present invention is more System and method for providing complete abnormal information and abnormal machine correlation across different shifts, different processes, and different machines. [Embodiment] Please refer to Figure 1, Figure 1 is provided for the present invention. A schematic diagram of one preferred embodiment of an automated tracking and notification system for machine anomalies. As shown in the figure i, the automatic tracking and notification system 100 for the machine abnormality provided by the present invention comprises a data acquisition and analysis subsystem 102, a loading device 104, and a machine state-before the library 1 〇 6 An abnormality information computing device 1 〇8, a determining device 110, and an automatic notification subsystem 112. The data acquisition and analysis subsystem 102 is configured to automatically retrieve a plurality of detection results, such as on-line process data, offline (0ff_〗 〖) process data, machine monitoring 1363963 (machine monitor) data, product defects (product defect) data, or input data of the user, such as displaying maintenance time points, replacing parts, commenting on the review results, etc., and integrating the test results or input data analysis into a plurality of abnormal information, and The ingress device 104 automatically loads the exception information into the stored machine state database 106. The abnormal information stored in the machine state database 106 includes at least the date, the product batch, the defect type, the defect degree, the related abnormal machine, and the abnormality score of the possible abnormal machine. In addition, the data capture and analysis subsystem 102 can also be used to analyze and diagnose at least one possible abnormal machine based on the abnormal information, and automatically load the abnormal information of the machine into the machine state database 106. The loading device 104 can be used to manually load the exception information or manually load any new anomaly information that is not from the data acquisition and analysis subsystem 102. The abnormality information computing device 108 is configured to separately calculate an abnormality score of the individual possible abnormal machine according to the abnormal information associated with the abnormal information, and the determining device 110 is configured to determine the individual abnormal machine. Whether the sum of the abnormal scores is greater than an η value. When the sum of the abnormal scores is greater than the value of η, for example, when the value of η is greater than or equal to (g) 2, the determining means 110 determines that the abnormal machine and the associated abnormal information are to be notified to at least one user. It is to be noted that the judging device 11 is configured to determine the sum of the abnormal scores in a predetermined period. When the sum of the abnormalities and the scores in the predetermined period is greater than the η value, it is determined that the abnormal machine must be The abnormal information related to the phase 1363963 is notified to the user. The n value can be defined or adjusted by the user according to the industry category, process complexity, machine type, machine output, machine downtime, or machine preventive maintenance (ΡΜ cycle). Finally, the automatic notification subsystem 112 is used to enable the possibility by means of an electronic mail, a computer integrated manufacturing (CIM) system warning device, a mobile phone newsletter, a machine operation interface warning signal, or a terminal user computer screen. The abnormal φ machine and the related abnormal information are notified to the user. Please refer to Fig. 1 and Fig. 2 at the same time. Fig. 2 is a first flow diagram showing one of the methods for automatic tracking and notification of machine abnormalities provided by the present invention. In general, users such as online process engineers or quality control engineers will test different products for different processes, such as process qualification related tests, product qualification related tests, and process evaluations (pr〇cess). Evaiuati〇n) related test, process monitor, routine product monitor, in_Hne process evaluation and monitoring, etc., to obtain online process data, offline process data, machine k measurement data, or product defect data. This large amount of test and monitoring result data is the so-called original data, and the online process engineer or quality control engineer will judge whether a batch of products is abnormal based on the above-mentioned original data. As shown in Figure 2, the statistical process control report (spc 1363963 • 曰rt) or product crystal determined to be scrapped (scrapl〇〇, controlled abnormal batch (OOC lot) or suspended batch (h〇ld 1〇t) The round acceptance test (wat) data, etc., is then obtained through the analysis of the work - to find out the abnormal product and the heterosexuality' to identify and diagnose at least one possible abnormal machine, and the engineering = this abnormality Information or directly enter the test results - annotation (Caf / in. Next, as shown in Figure 2, the method for automated tracking and notification of the machine provided by the present invention comprises the following steps:

Step 200: The automatic tracking and notification system 100 for the abnormality of the machine provided by the present invention utilizes the data acquisition and analysis subsystem 1 to automatically input the input data of the engineer, for example, the abnormal information in the annotation; The extraction and analysis subsystem can also directly extract the above detection results and integrate the analysis to obtain a plurality of abnormal information. Step 210: Continue with step 200. The loading device 104 is then used to automatically load and store the exceptions δίΐ in the machine state database. It is worth noting that the abnormal information can also be loaded and stored in the machine status database 1〇6 by manually loading the shock 104. In addition, when the new machine enters the process, the new machine's related difference > βίΐ can also be manually loaded into the machine status database 1〇6 through the loading device 1〇4. The abnormal information stored in the machine status database 106 includes at least the date, the product batch, the defect type, the defect degree, the related abnormal machine, and the abnormality score of the possible abnormal machine. Step 220: Continue with step 210. The abnormality information calculating means 1 8 calculates the abnormal payout amount of the individual month b different crane stations based on the abnormality information and the at least one related abnormal machine. Since the throughput 12 exposure 63963 is different from the machine idle time and the preventive maintenance (PM cycle), the abnormality information computing device 108 calculates the abnormal scores. The abnormal score within a predetermined period is calculated; and the abnormal score outside the period is negligible or not included in the calculation, but can still be stored in the machine state database 106 as an auxiliary diagnostic reference material for the subsequent abnormal machine. Step · Step 230: Continue with step 2 plus. The judging means 110 is used to judge whether the sum of the abnormal scores of one of the individual possible abnormal machines is greater than an η value. Dream 240: Continue with step 230. When the sum of the abnormal scores is greater than the value of η in the predetermined period, the judging means 11 judges that the abnormal abnormality machine and the associated abnormality information are notified to the at least one user by the automatic notification subsystem 112. And when the sum of the abnormal scores is less than the value of η; even if it is less than the value of η after exceeding the predetermined period, the abnormal score calculation is not included in the next predetermined period, but is still stored in the machine state database 106 as the latter Assist the diagnostic reference of the abnormal machine until the user thinks that the abnormal information and abnormal score can be zeroed or deleted. The following is a first preferred embodiment of the invention provided in accordance with the first flow steps described above. When the first batch of products produced by the first machine completed polycrystalline germanium lithography (p〇ly i ph〇t〇) was found to have a controlled abnormality (ooc), it was identified as a suspension and suspended. (4) Deficiencies such as defocus and dropped particles occur in the first batch of products through the Weicheng. If the defect is serious and it is scrapped 栌 13 1363963 The first batch is considered as a scrapped batch, and the first machine must be calibrated immediately. If the scrapping standard has not been reached and the engineer determines that the process can be continued, a note will be entered at the same time as the first batch is released. For example, the first batch of products has a grain out of focus and 50% of the particles fall. defect. The automatic tracking and notification system 100 for machine abnormalities provided by the present invention is as described in step 200. After the different processes are completed, the data acquisition and analysis subsystem 102 automatically captures and analyzes the engineer's annotations. The abnormal information is obtained, so the first batch of products receives the abnormal information as shown in Table 1: Table 1 The range of occurrence of the batch defect type in the flood season (%) Fatal defect / Non-fatal defect Machine machine abnormal score discovery level Level score No. 1 N/a Fatal 1 Poly 1 photo 1 First particle drop N/a 50 Fatal first 1 Poly 1 photo 1 It is worth noting that the data acquisition and analysis subsystem 102 is not for engineers The part of the annotation can be temporarily represented by n/a, and the machine that the batch has just experienced will be automatically retrieved, and the first machine 14 1363963 will be displayed in the abnormal information of Table 1. In addition, the user may pre-set the types of defects that may occur in different processes and different machines as killer defects or non-killer defects, while the data acquisition and analysis subsystem 102 is in accordance with the user's The predetermined rules automatically classify defects within the annotation and record them as fatal or non-fatal defects. Next, as described in step 210, the automatic tracking and notification system 100 for the machine abnormality provided by the present invention uses the loading device 104 to store the abnormal information contained in the table 1 in the machine state database 106. . And, as described in step 220, the abnormality information computing device 108 respectively gives the abnormal information an abnormality score, and an abnormality score is given to the abnormality score of the machine indicated in Table 1; the abnormal information computing device 1〇8 starts. These abnormal scores are calculated separately. Next, the determining means 110 determines whether the sum of the abnormal scores of the first machine is greater than a value of η within a predetermined period, for example, within two days, as determined by step 220 and step 230, and decides whether to notify the user. As described above, this η value can be adjusted as required, and in the first embodiment, the η value is equal to 2. In addition, the predetermined period in the present invention can be adjusted according to the requirements of the process and the type of the machine, the output of the machine, the downtime of the machine, or the preventive maintenance cycle of the machine. In the first preferred embodiment, the first machine has two types of defects, and the sum of the abnormal scores is greater than two, so the automatic tracking and notification system 100 of the machine abnormality is as described in step 240, 15 1363963 The first machine and related abnormal information are communicated to the user by the automatic notification subsystem 112, such as an online process engineer or a quality control engineer. When the sum of the abnormal scores is less than 2, even if it is less than 2 for more than 2 days, it is judged as a single event, and is not included in the abnormal score calculation in the next predetermined period. However, this abnormal information is still stored in the machine status database 106 as an auxiliary diagnostic reference material for the abnormal machine, until the user thinks that the abnormal information and its abnormality score can be deleted. In addition, after a predetermined period of time, the abnormal scores may also be zeroed according to the user's regulations to avoid affecting the subsequent abnormal score calculation; of course, the abnormal information is still stored in the machine state database 106 as a future Assisted diagnostic reference materials for abnormal machines. Since the automatic tracking and notification system 100 and the method for the abnormality of the machine provided by the present invention automatically extract test results or annotations of different products, different processes, different machines, and perform analysis and calculation, even if the above defects occur in Different shifts, or marked by different engineers, can still automatically track and analyze the abnormal information of the abnormal machine through the system, and automatically report it to the user. Therefore, it is possible to avoid the omission or error that may be caused by manual handover, which can also compensate for the problems that may be caused by neglecting minor anomalies. The following is a second preferred embodiment of the present invention provided in accordance with the above first flow steps. When the second 16 1363963 batch product of the polycrystalline germanium lithography was completed by the first machine, the condition of the controlled abnormality (ooc) was detected, and was paused and suspended. Then, the engineer confirmed that the second offset was defocus and other defects, but the defects of the second batch of products have not reached the scrapping standard, so the engineer judged that the process could be continued and released the second batch of products. At the same time, a first annotation is input, for example, a second batch of products has a grain defocusing. The second batch of products is followed by a subsequent process. For example, the metal 1 photo is produced through the first machine. After the test, it is found that a controlled abnormality occurs and is suspended. Then, through different or the same engineer, the defects of the second batch of products, such as defocus and metal particles, were confirmed, but the scrapping standards were not met. Therefore, the engineer determined that the process could be continued and released the second batch of products. A second annotation is entered, for example, a second batch of products has a grain that is out of focus and has defects in the metal particles. The automatic tracking and notification system 100 for the machine abnormality provided by the present invention, as described in step 200, immediately uses the data acquisition and analysis subsystem 102 to automatically capture and analyze the first annotation and the first, respectively, after different processes. The abnormal information in the two annotations, for example, using an automatic judgment string engine for the special character string in the annotation in the annotation, and analyzing and arranging into the abnormal information as shown in Table 2. Table 2 17 1363963 The number of occurrences of batch defect types is %% Fatal defect/non-fatal defect Machine 异常 Machine abnormal score Find hierarchical level score Defocus 1 N/a Fatal - 1 Poly 1 photo 1 Metal particle N/a N/ a Non-fatal first* 1 Metal 1 photo 1 Defocus 1 N/a Fatal - 1 Metal 1 photo 1 Next, as described in step 210, the automated tracking and notification of machine anomalies provided by the present invention The system 100 loads and stores the abnormal data in the machine state database 106 using the loading device 104. And, as described in step 220, the abnormality information computing device 108 respectively gives the abnormality information an abnormality score, for example, an abnormality score is given in the field of the abnormality score of the machine as indicated in Table 2; and the abnormality information computing device 108 is used according to the abnormality information The abnormality information and the related abnormal machine are respectively calculated for the abnormality scores of the individual possible abnormal machines. Next, the determining device 110 determines, according to step 220 and step 230, that the abnormal score of one of the first machines is total within a predetermined period, for example, two days.

1B 1363963 and whether it is greater than a value of η, and decide whether to notify the user. As previously mentioned, this η value can be adjusted as required, while in the second embodiment, the η value is equal to two. In the second preferred embodiment, the first machine has two types of defects in 2 days, and the sum of the abnormal scores is equal to 3, so the automatic tracking and notification system 100 of the machine abnormality is as shown in step 240. As described, the first machine and related abnormal information are immediately notified to the user through the automatic notification subsystem 112, such as an online process engineer or a quality control engineer. As mentioned above, when the sum of the abnormal scores is less than 2, or is still less than 2 in more than 2 days, it is judged as a single event, and is not included in the abnormal score calculation in the next predetermined period, but is still stored in The machine status database 106 serves as an auxiliary diagnostic reference material for the subsequent abnormal machine until the user thinks that the abnormal information and the abnormality score can be deleted. In the second preferred embodiment, the non-fatal defect is also included in the calculation of the abnormal score. However, the user can define the non-fatal defect as not included in the abnormal score calculation according to the tolerance requirements of different processes and different products. Or after weighting, the abnormal score calculation is included to avoid excessively amplifying the impact of non-fatal defects on the machine, resulting in unnecessary cost, and avoiding excessive neglect of the effects of non-fatal defects. Other defects are caused in the subsequent major anomalies, resulting in loss of product yield and production costs. It is worth noting that since the automatic 19 1363963 tracking and notification system 100 and the method provided by the present invention automatically capture test results or annotations of different processes, and perform analysis and calculation, even if the defect occurs in Different processes, different layers, or different times, and marked by different engineers, the system can automatically track the abnormal information of the same abnormal machine and notify it to the user. Please refer to Fig. 1 and Fig. 3 at the same time. Figure 3 is a second flow diagram of the method for automatic tracking and notification of the abnormal machine provided by the present invention. As mentioned above, when a user, such as an online process engineer or a quality control engineer, tests different products of different processes and obtains the original data as described above, the online process engineer or quality control engineer analyzes the original data. Obtain a test result and determine whether a batch of products can be released. Next, as shown in FIG. 3, the method for automatically tracking and reporting the abnormality of the machine provided by the present invention comprises the following steps: Step 300: automatically inputting the input of the engineer by using the data acquisition and analysis subsystem 1〇2 Data, such as such anomalous information in the annotation; the data acquisition and analysis subsystem can also directly retrieve the above detection results or online process data, offline process data, machine monitoring data, or product defect data, and integrate analysis Obtaining a plurality of abnormal information, and diagnosing at least one possible abnormal machine according to the abnormal information. Step 310: Continue step 300. The load device 104 is then used to automatically load and store the exception information in the machine status database 106. As described above, the abnormal information can also be loaded and stored in the machine state database through the loading device 104 20 by hand. In addition, when the new machine is used in winter, it can also be manually used by the manned device 1Q4. The new machine mouth station ^"Bai Xun in the machine state f library 1 〇 6 heart error in the machine state, please Kuga The information includes at least the date, product batch, defect type, lack of _ degree, possible abnormal machine, abnormal score of the possible abnormal machine. Step 320: Continue with step 310. The abnormality information computing device is used to calculate the abnormal scores of the individual abnormal machines in a predetermined period according to the abnormal information and the related abnormal machine. It is worth noting that since the output of each machine is different from the downtime and the preventive maintenance cycle, the abnormal information computing device (10) calculates the abnormal score in the predetermined time when calculating the abnormal score; and the predetermined period The abnormality score outside can be ignored or stored in the machine status database (10) as a diagnostic reference for assisting the abnormal machine. Step 330: Continue step, step 320. Use the judgment f ιι〇 to determine whether the sum of the abnormal scores of one of the possible abnormal machines is greater than an n value. Step 340 ·· Follow-up steps. When the sum of the abnormal scores is greater than the η value within the predetermined period, the automatic notification subsystem 112 is used to notify the at least one user of the possible abnormal machine and the associated abnormal information. When the sum of the abnormal scores is still less than the threshold after exceeding the predetermined period, the abnormal score calculation in the next predetermined period is not included, but is still stored in the machine state database 106 as the assistance of the abnormal machine afterwards. Diagnosis 21

lDOJyOJ lDOJyOJ The exception information and the exception score are cut off until the user thinks it can be deleted. The present invention is based on the preferred embodiment of the invention. When the first (four) first-flowing step is provided for the third generation, the second batch of I machine is completed, and the third layer of the lithography is determined to be the second/then. A condition of a controlled abnormality (ooc) occurs, and the A-port chrome tau ratio is suspended. Then the engineer confirmed the third batch (4) and the defects such as falling particles, but it has not yet reached the end of life: η 4 division judged that the process can be continued, and the third batch of the second batch of the first comment is released, for example: the third batch The secondary product has - the grain is out of focus. The automatic tracking and notification system 100 for the abnormality of the machine provided by Maoyue is as described in step 300. Immediately after the different processes, the 1M2 of the metering and analysis subsystem is automatically recorded and automatically recorded in the following: Such abnormal information 'or straight (4) take the third batch of product-related line magic data, offline process data, machine monitoring data, etc., or product lack of display" according to the analysis of the abnormal information as shown in Table 3, And identify the possible abnormal machine to /. For example, in the third preferred embodiment, the user does not have a defect in the third batch of the transfer to which the machine is from the machine. However, since the machine state database 1〇6 system can provide a huge abnormality. The dad diagnoses the reference information, so the data_and the analysis subsystem can be _ user input, or can be automatically analyzed according to the other test results described above. 22 1363963 diagnoses the defects of the third batch of products Because of the first machine, and automatically recorded in the machine block in Table 3 as the first machine. Table 3 Range of occurrences of defective batch defects in the flood season % fatal defect / non-fatal defect machine machine abnormality score found level of hierarchy score defocus 1 N / a fatal - one 氺 1 Poly 1 photo 1 first particle N / a 50 Fatal - 氺 1 Poly 1 photo 1 Next, the abnormal data is loaded and stored in the machine state database 106 by the loading device 104 as described in step 310. And as described in step 320, the abnormality information computing device 108 respectively gives the abnormal information an abnormality score, for example, an abnormality score is given in the field of the abnormality score of the machine as indicated in Table 3. The abnormality information computing device 108 then calculates the abnormality scores of the individual possible abnormal machines based on the abnormality information and the associated possible abnormal machine. Next, the determining device 110 is as described in step 320 and step 330, 23 1363963

In the predetermined week _, for example, two days, it is judged whether or not the total score of the first machine is equal to or greater than n, and whether or not the user is notified. As described above, the value of ^ can be adjusted according to requirements. In the third preferred embodiment, the value of n is specific to h. In addition, the third (four) implementation of the financial definition is defined as a two-day predetermined period, which can be based on the process and the machine. Type, machine output, machine downtime, and adjustment of the preventive maintenance cycle adjustment of the machine. In the third preferred embodiment, the first machine has two types of defects within two days, and the sum of the abnormal scores is greater than two, so the automatic tracking and notification system of the machine abnormality is as follows: It is said that the first machine and related abnormal information are notified to the user by the automatic notification subsystem H2, such as an online process engineer or a quality control engineer. As mentioned above, when the sum of the scores of the abnormal scores is less than 2, or is still less than 2 for more than 2 days, it is determined as a single event, and is not included in the abnormal score calculation in the next predetermined period, but is still stored in The machine status database 1〇6 is used as a reference for assisting diagnosis of the abnormal machine afterwards, until the user thinks that the abnormal information and the abnormal score can be deleted. In a third preferred embodiment, the automated tracking and notification system 100 and method for machine anomaly provided by the present invention are automatically analyzed by a large number of abnormal machine diagnostic reference data stored in the machine state database 106. Identify at least one possible abnormal machine. The following is a preferred embodiment of the fourth aspect of the present invention provided by the second flow step of the present invention. When a fourth batch of products that have been completed by the first machine to complete the polysilicon layer lithography has been found to have a controlled abnormality, and the engineer confirms that the fourth batch of products has an exposure defocus defect, but has not yet reached the scrapping standard, If the engineer determines that the process can be continued, a first note will be entered at the same time as the fourth batch of product is released. For example, a grain of the fourth batch has a defocus. The next fifth batch of products is also finished with the metal layer lithography through the first machine. After the test, it was found that a condition of controlled abnormality occurred and was suspended. Then, through different or the same engineer, the fifth batch of products was confirmed to have defects such as exposure defocus and metal particles, but the scrapping standard has not yet been reached. Therefore, the engineer judges that the process can be continued, and will input one at the same time as the fifth batch of products is released. Second note, for example, the fifth batch of products has a grain defocusing and defects in metal particles. Next, a sixth batch of goods was produced through a second machine to complete the production of polycrystalline germanium lithography. However, after the test, it was found that a condition of controlled abnormality occurred and was suspended. Then, through the different or the same engineer, the sixth batch of products was diagnosed as having an exposure defocus defect 'but the scrapping standard was not met'. Therefore, the engineer determined that the process could be continued, and the third batch of products was released while entering a third. Note: For example, the sixth batch product has a grain defocusing 0 25 1363963 The automatic tracking and notification system 100 for the machine abnormality provided by the present invention is as described in step 300, and the data is used immediately after different processes. The acquisition and analysis subsystem 102 automatically captures and analyzes the abnormal information in the first, second, and third annotations, or directly captures the online process data, offline process data, and machine related to the three batches of products. Monitoring data, etc., and analyzing and arranging the abnormal information as shown in Table 4: Table 4 The number of occurrences of batch defects in the flood season is %. The fatal defect/non-fatal defect machine machine abnormal score is found to be the fourth level of the hierarchical level score. Coke 1 N/a Fatal - 1 Poly 1 photo 1 Fifth Defocus 1 N/a Fatal _ — 1 Metal 1 photo 1 Hardware Particle N/a N/a Non-fatal 1st Metal 1 photo 1 6th out of focus 1 N/a Deadly -_ 1 Poly 1 photo 1 26 1363963 Next, as described in step 310, using the loading device 104 The exception data is loaded and stored in the machine status database 106. And as described in step 320, the abnormality information computing device 108 is used to give and calculate an abnormality score of one of the abnormal information, for example, an abnormality score is respectively given in the field of the abnormality score of the machine as indicated in Table 4. Next, the judging device 110 determines whether the sum of the abnormality scores of one of the first machines is greater than or equal to 2 within a predetermined period of I, for example, as described in step 320 and step 330, and determines whether to notify the user. As mentioned earlier, this predetermined period can be adjusted according to the requirements of the process and machine type, machine output, machine downtime, or machine preventive maintenance cycle adjustment. In the fourth preferred embodiment, the first machine has two types of defects in two days, and the sum of the abnormal scores is greater than 2'. The automatic tracking and notification system 100 of the machine abnormality is as described in step 340. The first machine and related abnormal information are notified to the user by the automatic notification subsystem 112, such as an online process engineer or a quality control engineer. As mentioned above, when the sum of the abnormal scores is less than 2, or is still less than 2 in more than 2 days, it is judged as a single event, and is not included in the abnormal score calculation in the next predetermined period, but is still stored in the machine. The status database 106 serves as an auxiliary diagnostic reference for the subsequent abnormal machine until the user believes that the abnormal information and the abnormal score can be deleted. In the fourth preferred embodiment, the sum of the abnormality scores of the 27th-machines experienced by the fourth batch and the fifth batch is greater than 2, so the abnormal machine and the associated abnormality 2 are notified by the automatic notification subsystem 112. To at least one user. Guang, is the automatic tracking and notification system provided by the invention. It is just tracking the abnormality of the abnormal machine. Therefore, even if the abnormal one is in different processes, no layer or even different batches. And marked by the engineer of Z, can still be notified to the user through the tracking of the system. ^ Bu is worth noting, in the difficult implementation of wealth, the fourth batch of two /, batch-human defect system for the user diagnosed as the first machine and the second often Beixun and through the data acquisition and analysis subsystem 102 shows dichrome 4". However, since the two batches of goods are in the same state as the first layer of polycrystalline germanium layer, the auto-tracking and overnight, first 100 series available data couching and analysis are provided. The subsystem automatically analyzes the abnormality information and the manufacturing process of the two batches of goods. If the calendar-the second machine is found, the data acquisition and analysis subsystem can additionally identify the third related abnormal machine. And inform the user: the additional 5 tolerate the information of the third related machine. If the abnormality score of the second related machine is additionally indicated according to the different (four) news, the user must notify the user immediately. And the user is notified by the automatic notification subsystem n2. In the fourth embodiment, the machine provided by the present invention is abnormal from 28 1363963. The dynamic tracking and notification system 100 and the method system span different batches and different processes. Different shift engineers The tracking and tracking of the abnormal information is automatically tracked. More importantly, the same defect type that can be generated for different machines can be automatically analyzed by a large number of abnormal machine diagnostic reference data stored in the machine state database 106. Inferring and additionally recognizing at least one possible related abnormal machine, providing a user reference. The following is a fifth preferred embodiment of the present invention according to the second flow step described above. When the polysilicon layer lithography is completed The seventh batch of products is found to have a controlled abnormal condition, such as an occurrence of exposure defocusing defects, etc., and the automatic tracking and notification system for the abnormality of the machine provided by the present invention is completed as described in step 300, and the polycrystalline silicon is completed. After the layer lithography is produced, the data acquisition and analysis subsystem 102 is automatically used to automatically extract and analyze the engineer's annotations or retrieve the relevant original data, and analyze and organize the abnormal information as shown in Table 5, and identify the abnormal information. Related to the abnormal machine. For example, in the fifth preferred embodiment, the defect of the exposure defocus corresponds to the first machine of the station. For example, an exposure abnormality of a lithography machine; or due to a particle abnormality of the second machine 'such as a polysilicon layer deposition machine. Therefore, the data acquisition and analysis subsystem 102 can be input according to the user, or can be based on The other test results are automatically analyzed and the defects diagnosed in the seventh batch of products are related to the first machine and the second machine, and are automatically recorded in the machine field in Table 5 as the first The second machine. 29 1363963, another eighth batch, the ninth batch, the tenth batch and the eleventh batch of products were respectively produced in different lithography machines after the completion of polycrystalline germanium lithography. Exposure defocusing defect. The exposure defocusing defect is related to different station lithography machines, such as a third machine, a fourth machine, a fifth machine, and a sixth machine. However, the present invention provides The automatic tracking and notification system of the machine abnormality 100 automatically compares the production processes of the previous batches of products, and analyzes that the batch products pass through the second machine, so the data acquisition and sub-measurement subsystem 102 series automatically in the machine in Table 5 Field, respectively, and other records of the machine:

Table 5 Number of occurrences of batch defects on the surface of the flood season % fatal defect / non-fatal defect machine machine abnormal score found level of hierarchy score missing 1 N / a fatal 1 Poly 1 1 7 jog - photo 1st loss N / a Fatal 1st Poly 1 1 Seven Jiao 2 photo Lost 1 N/a Deadly 1 Poly 1 1 Eight-focus II Photo Lost 1 N/a Deadly 1 Poly 1 1 Eight-focus three photo Lost 1 N/a Deadly - 1st Poly 1 1 photo 30 1363963 九焦^·— S----- _ 1 lost 1 N/a fatal 1 ' P〇ly 1 1 9 焦四Photo Lost 1 N/a Fatal -- -- 1 十焦二Photo Lost 1 N/a Fatal f〇bnr~ — 1 Ten Jiao Five Photo Brother Lost 1 N/a Fatal 1 ' Poly 1 1 Ten Jiao'—' Photo Lost 1 N/a Fatal 1st ------- 1 10 - Jiaoliu Photo ~~~~--.

The abnormal data is loaded and stored in the machine status database by the loading device ι〇4 as described in step 31〇. And, as described in detail, the abnormality information computing device 108 calculates and calculates an abnormality score of the individual abnormal machine according to the abnormal information and the related abnormal machine, for example, the abnormality score of the machine indicated in Table 5. The distribution is determined by the abnormality score 0 and the step 330, and the sum of the abnormal scores is determined by the judging device 110 in the predetermined period of step 320, for example, within 2 days, each machine is determined to be: > at the position 3. No greater than or equal to one The value of n, and decide whether to notify the use of I. As mentioned earlier, the it匕 predetermined cycle can be adjusted according to the process and machine type, machine output, machine time, or machine preventive maintenance cycle adjustment requirements. The value of the value is that, in the fifth preferred embodiment, the abnormal information of the machine is identified by the system, and is unnecessary to avoid excessive amplification of the abnormal information of the machine tracked by the system. Cost of expenditure 'In the fifth preferred embodiment, the value of n is set equal to four. It can be seen from Table 5 that: • The sum of the abnormal scores of the second machine is equal to 4, so the automatic tracking and notification system 100 of the machine abnormality is as described in step 340, 'This second machine and related abnormal information The automatic notification subsystem 112 is used to notify the user, such as an online process engineer or a quality control engineer. The sum of the abnormal scores of other machines is equal to 1, so it can be judged as a single event. Since each defect may be caused by an abnormality of different types of machines, that is, each defect corresponds to a plurality of machines, and the defects corresponding to various machine abnormalities can be specified and built in the machine state database. +. When a defect occurs, not only when the station is identifiable, but also the associated abnormal machine can be identified by the automatic tracking and notification system 100 of the machine abnormality provided by the present invention. And as described in the fifth preferred embodiment, even if different batches of products completed by different similar types of wheat machines can be compared with the flow through the automatic tracking and notification method of the machine abnormality provided by the present invention. Automatically track out the abnormal information of the same possible abnormal machine. Therefore, even if such abnormal information occurs on a non-station machine or a different batch, and is marked by a different 32 engineer, it is reported to the user. Still can be found by the system

station. In addition, when the same type of defect is different in the system and method provided according to the present invention, the difference between the batch and the different machine occurs, the automatic tracking and notification system and method for the machine abnormality provided by the present invention is more By analyzing the production processes experienced by different batches, we can further identify at least the opposite stage. That is to say, the method provided by the invention can automatically count and analyze the correlation between the abnormal product and the abnormal machine, and summarize the abnormal information and the machine that may be abnormal, and immediately report the user. Since the above steps are all completed by the automatic tracking and notification system provided by the present invention, the influence of the manual operation and the deficiencies of the user experience can be saved, and the training effect of the new personnel can also be used. Therefore, the present invention is a system and method for providing complete anomaly information correlation across different shifts and different machines. The above are only the preferred embodiments of the present invention, and the equivalent variations and modifications made by the scope of the present invention are to be included in the scope of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS Fig. 1 is a schematic view showing a preferred embodiment of an automatic tracking and notification system for machine abnormalities provided by the present invention. Figure 2 is a first flow diagram showing one of the methods for automatic tracking and notification of machine abnormalities provided by the present invention. Figure 3 is a second flow diagram of one of the methods for automatic tracking and notification of machine abnormalities provided by the present invention. [Main component symbol description] 100 machine automatic tracking and notification system 102 data acquisition and analysis subsystem 104 loading device 106 machine state database 108 abnormal information computing device 110 determining device 112 automatic notification subsystem 200 utilizing The data capture and analysis subsystem automatically retrieves the abnormal information in the annotation 210. The abnormal information is automatically loaded into a machine state database 34 by a loading device. 963 22〇 230 240

300 3l〇

320 330 The use-abnormal information computing device separately calculates, according to the abnormal information and at least one related abnormal machine, the abnormality of the individual abnormal machine in the predetermined period, and the determining device determines one of the individual abnormal machines. Whether the sum of the abnormal scores is greater than an η value, when the sum of the abnormal scores is greater than the η value, that is, the automatic notification subsystem notifies the abnormal machine and the related information to at least one user using a data capture And the analysis subsystem automatically takes the annotation or related online process data, offline process data, machine monitoring data and integrates into a plurality of abnormal information, and diagnoses at least one related abnormal machine using a loading device The exception information is automatically loaded into a machine status database. An abnormality information computing device is used to calculate an abnormality score of a possible abnormal machine in a predetermined period based on the abnormal information and the at least one related abnormal machine. The judging means judges whether the sum of the abnormal scores of one of the individual abnormal machines is greater than a value of η. When the sum of the abnormal scores is greater than the value of η, an automatic notification subsystem is used to notify the at least one user of the abnormal machine and the associated one. 35 340

Claims (1)

1363963 -----^ Patent application scope: ι· - Anomaly automatic tracking and notification system for seed machines, including - Data lion and analysis sub-line for automatic fruit analysis and integrated analysis into multiple abnormal information; a detection node, a machine state database for storing the abnormal information. - An abnormal information calculation device for calculating the individual machine-days according to the information of the abnormal information that is related to the reading - Frequently scored; the different judgment device 'is used to determine whether the sum of the individual abnormal machine △ is greater than an n value, and when the abnormal score is different from the bm knife', when the sum is greater than the 11 value, Judging that at least one user must be notified, the η ^ and τ η values can be adjusted according to the type of broadcast station, the machine output, the machine downtime, or the preventive maintenance cycle (PM cycie). And an automatic notification subsystem for notifying the potential abnormal machine and the abnormal information to the user. 2. The system of claim 1, wherein the test results are from on-line process data, off-line process data, machine monitor data, product defects ( Product defect) Data, or input from the user. 3. The system of claim 1, wherein the data acquisition and analysis subsystem is configured to analyze and diagnose the abnormal machine according to the abnormal information. Revised replacement page on February 13, 2010. 4♦ The system described in claim i, in addition to the loading device, is used to automatically load the abnormal information into the machine status database. Such as Shen. The system of claim 4, wherein the loading device is to manually load the abnormal information, or manually load any non-from the According to the system of the state of the machine, the system described in claim 2, wherein the abnormal information stored in the machine-like 11 library includes at least a sundial, a product batch, and a missing type. The degree of defect, the relevant abnormal machine 'and the abnormality of the possible abnormal machine. The system described in Item 1 of the second and second patents, wherein the value system is greater than 8 fields, such as the system described in claim 1 of the patent application, wherein the judging device is used for the simple-predetermined week (4), and the individual may be different. The abnormality score of the machine (4) 7 when the sum of the abnormal scores in the predetermined period is greater than the value of n, that is, the 4J is required to notify the user. 9. The system of claim 8, wherein the predetermined period is 37 1363963 _:_ February 13th, 13th, the revised replacement page can be adjusted according to the type of machine, the output of the machine, the downtime of the machine, or the preventive maintenance cycle of the machine. 10. If the patent application scope is the first item The system, wherein the automatic notification subsystem comprises an electronic mail, a computer integrated manufacturing (CIM) system warning device, a mobile phone newsletter, a machine operation--interface warning signal, or a terminal user computer screen Etc.. 11. A method for automated tracking and notification of machine anomalies, including: Using a data acquisition and analysis subsystem to automatically capture multiple test results and integrate them into multiple exceptions Information; using a machine state database to store the abnormal information; using an abnormal information computing device to calculate anomaly scores of individual possible abnormal machines according to the abnormal information and at least one related abnormal machine; The judging device judges whether the sum of the abnormal scores of one of the possibly abnormal machines is greater than an η value, wherein the η value can be adjusted according to the type of the machine, the output of the machine, the downtime of the machine, or the preventive maintenance cycle of the machine; And when the sum of the abnormal scores of the abnormal machine is greater than .n, it is judged that the automatic abnormality subsystem is used to notify the at least one user of the abnormal abnormality with the automatic notification subsystem. For example, the scope of the patent application is derived from the fact that the test results from the online clothing domain data, the offline process machine product defect data, or the user's wheeled data. The method described, wherein the data is taken from the machine; and the system analyzes and judges the possibility according to the abnormal information. The method further includes a step of automatically loading the abnormal information into the machine state database by using a device, such as the method described in claim 14 of the patent scope, and further including using the The manual loading of such anomalous information 'or any - not from the bedding material acquisition and analysis subsystem, the new state information library. 16 · As stated in the May patent scope The method of storing the abnormal information stored in the state database includes at least a date, a product batch-person, a defect type, a defect degree, the related abnormal machine platform, and the abnormality of the monthly machine 17. The method of claim 11, etc. 17. The method of claim 11, wherein the η value is large '39 1363963 is equal to (g) 2 February 13, 101 revised replacement page 18. If the patent application scope is u The party judging device analyzes and judges a pre-replacement & 1 using the sum of the abnormal scores, and when the predetermined period = the value of the individual possible abnormal machine, it is judged that the user is notified. The sum of the abnormal scores is greater than the 19. The scope of the patent application can be adjusted according to the type of the machine, the machine A, and the method 'the predetermined period of the preventive maintenance cycle. ^ 1, the machine downtime, or the machine muscle as described in the patent scope of the method described in item u, wherein the second system = period e-mail, computer integrated manufacturing system (C Μ) two: machine, machine The operation interface warning signal is notified to the user. Electricity ten pattern: