A method and device for detecting and processing delivery exceptions

Abstract

The application discloses a kind of detection, processing method and device of dispatch exception, to realize the real-time automatic detection of dispatch exception of semiconductor production equipment, so as to improve the work efficiency of dispatch exception detection, satisfy operation demand.A kind of detection method of dispatch exception provided by the application comprises: determining that the detected object is in idle state, and cannot dispatch;Wherein, the detected object is the minimum capacity unit of the delivery of semiconductor production equipment;Determine the detection result by detecting one or a combination of the following contents: whether the detected object is prohibited to work;Whether there is a work-in-process in waiting state;Whether loading port is in full-automatic state;The state of wafer group.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of semiconductor, in particular to a method and device for detecting and processing delivery exception. BACKGROUND

[0002] In the prior art, if there is a delivery exception, the production operation personnel need to find the problem passively. The problem can be found only when there is an abnormal alarm on the machine, abnormal information on the automatic system, or when the output is less than the expected output. If no one finds the problem, the system will not actively notify the problem. However, as the production capacity increases, the number of machines increases, and the abnormal processing process cannot meet the needs of efficient operation.

[0003] In summary, the current delivery exception detection results in low work efficiency and cannot meet the operation needs. SUMMARY

[0004] Embodiments of the present application provide a method and device for detecting and processing delivery exception, to realize real-time automatic detection of delivery exception of semiconductor production equipment, thereby improving the work efficiency of delivery exception detection and processing, and meeting the operation needs.

[0005] The method for detecting delivery exception provided by the embodiments of the present application comprises the following steps.

[0006] It is determined that the detected object is in an idle state and cannot deliver goods. The detected object is a minimum capacity unit of the semiconductor production equipment.

[0007] The detection result is determined by detecting one or a combination of the following contents.

[0008] Whether the detected object is prohibited from working;

[0009] Whether there is a work-in-process in a waiting state;

[0010] Whether the loading port is in a full-automatic state;

[0011] The state of the wafer group.

[0012] When it is determined that the detected object is in an idle state and cannot deliver goods, the detection result is determined by detecting one or a combination of the following contents: whether the detected object is prohibited from working; whether there is a work-in-process in a waiting state; whether the loading port is in a full-automatic state; and the state of the wafer group. Thus, real-time automatic detection of delivery exception of semiconductor production equipment is realized, thereby improving the work efficiency of delivery exception detection and meeting the operation needs.

[0013] Optionally, the determination of the detection result comprises the following steps.

[0014] If the detected object is detected to be prohibited from working, the detection result is determined to be that the detected object is prohibited from working; if the detected object is detected not to be prohibited from working, whether there is a work-in-process in a waiting state is further detected;

[0015] If there is a work-in-process in a waiting state, whether the loading port is in a full-automatic state is further detected; if the loading port is not in the full-automatic state, the detection result is determined to be that the loading port is in a non-full-automatic state; if the loading port is in the full-automatic state, the state of the wafer group is further detected, and the detection result is determined according to the state of the wafer group.

[0016] Optionally, according to the state of the wafer group, the detection result is determined to be one of the following:

[0017] The automated dispatching platform has no reservation;

[0018] The automated dispatching platform fails to reserve;

[0019] There is no reason for no dispatching.

[0020] Optionally, the method further includes:

[0021] The detection result is stored in a detection result database of the automated dispatching platform.

[0022] The embodiment of the application provides a processing method for dispatching exception, which includes:

[0023] Obtaining a detection result obtained by using the method for detecting dispatching exception, and classifying problems causing the dispatching exception based on the detection result to generate a classification result;

[0024] Debugging processing is performed on the classification result, and feedback information and / or exception information required to be sent to a user are generated according to a processing result;

[0025] The feedback information is sent to at least one client, and / or an analysis report is generated by using the exception information, and the analysis report is sent to at least one client.

[0026] Optionally, the method further includes:

[0027] Data is obtained from a production capacity system database, and / or a real-time dispatching system database, and / or a production parameter system database, and is stored into a preset production material database; and the detection result obtained from the detection result database is stored into the production material database; the classification result is generated based on data read from the production material database.

[0028] The embodiment of the application provides a device for detecting dispatching exception, which includes:

[0029] a first unit configured to determine that the detected object is in an idle state and unable to dispatch goods; wherein the detected object is a minimum capacity unit of a semiconductor production device;

[0030] a second unit configured to determine a detection result by detecting one or a combination of the following:

[0031] whether the detected object is prohibited from working;

[0032] whether there is a work-in-process in a waiting state;

[0033] whether the loading port is in a full-automatic state;

[0034] a state of a wafer group.

[0035] Optionally, the second unit is configured to:

[0036] if it is detected that the detected object is prohibited from working, determine that the detection result is that the detected object is prohibited from working; and if it is detected that the detected object is not prohibited from working, further detect whether there is a work-in-process in a waiting state;

[0037] if there is a work-in-process in a waiting state, further detect whether the loading port is in a full-automatic state; if the loading port is not in a full-automatic state, determine that the detection result is that the loading port is in a non-full-automatic state; if the loading port is in a full-automatic state, further detect a state of a wafer group, and determine the detection result according to the state of the wafer group.

[0038] Optionally, the second unit determines the detection result to be one of the following according to the state of the wafer group:

[0039] the automated dispatching platform has no reservation;

[0040] the automated dispatching platform fails to reserve;

[0041] a reason for no dispatching of goods.

[0042] Optionally, the apparatus further comprises:

[0043] a third unit configured to store the detection result in a detection result database of the automated dispatching platform.

[0044] Another processing apparatus for dispatching exceptions provided by an embodiment of the present application comprises:

[0045] a classification unit configured to obtain a detection result obtained by the apparatus for detecting dispatching exceptions, and classify problems causing the dispatching exception based on the detection result to generate a classification result;

[0046] a debugging unit configured to perform debugging on the classification result, and generate feedback information and / or exception information to be sent to a user according to a processing result;

[0047] a sending unit configured to send the feedback information to at least one client, and / or generate an analysis report by using the exception information, and send the analysis report to at least one client.

[0048] Optionally, the classification unit is further configured to:

[0049] acquire data from a capacity system database, and / or a real-time delivery system database, and / or a production parameter system database, and store the data into a preset production material database; and store the detection result acquired from the detection result database into the production material database; the classification result is generated based on data read from the production material database.

[0050] Another embodiment of the present application provides a computing device, comprising a memory and a processor, wherein the memory is configured to store program instructions, and the processor is configured to invoke the program instructions stored in the memory to execute any of the above methods.

[0051] In addition, according to an embodiment, for example, a computer program product for a computer is provided, which comprises software code portions for performing the steps of the above-defined method when the product is run on the computer. The computer program product can comprise a computer-readable medium on which the software code portions are stored. In addition, the computer program product can be directly loadable into the internal memory of the computer and / or transmittable via a network by means of at least one of a upload process, a download process and a push process.

[0052] Another embodiment of the present application provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are used to make the computer execute any of the above methods. BRIEF DESCRIPTION OF DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0054] Figure 1 The report schematic diagram provided by the embodiments of the present application;

[0055] Figure 2aThe analysis report provided by the embodiment of the present application is intended to be presented from the perspective of wafer lot;

[0056] Figure 2b The analysis report provided by the embodiment of the present application is intended to be presented from the perspective of machine (Tool);

[0057] Figure 2c The manufacturing department (MFG Dept) diagram provided by the embodiment of the present application is intended to be presented from the perspective of machine (Tool);

[0058] Figure 2d The manufacturing department (MFG Dept) diagram provided by the embodiment of the present application is intended to be presented from the perspective of machine (Tool);

[0059] Figure 2e The manufacturing department (MFG Dept) diagram provided by the embodiment of the present application is intended to be presented from the perspective of machine (Tool);

[0060] Figure 2f The manufacturing department (MFG Dept) diagram provided by the embodiment of the present application is intended to be presented from the perspective of machine (Tool);

[0061] Figure 2g The manufacturing department (MFG Dept) diagram provided by the embodiment of the present application is intended to be presented from the perspective of machine (Tool);

[0062] Figure 2h The manufacturing department (MFG Dept) diagram provided by the embodiment of the present application is intended to be presented from the perspective of machine (Tool);

[0063] Figure 3 The manufacturing department (MFG Dept) diagram provided by the embodiment of the present application is intended to be presented from the perspective of machine (Tool);

[0064] Figure 4 The manufacturing department (MFG Dept) diagram provided by the embodiment of the present application is intended to be presented from the perspective of machine (Tool);

[0065] Figure 5 The manufacturing department (MFG Dept) diagram provided by the embodiment of the present application is intended to be presented from the perspective of machine (Tool);

[0066] Figure 6 The manufacturing department (MFG Dept) diagram provided by the embodiment of the present application is intended to be presented from the perspective of machine (Tool);

[0067] Figure 7 The manufacturing department (MFG Dept) diagram provided by the embodiment of the present application is intended to be presented from the perspective of machine (Tool);

[0068] Figure 8 The manufacturing department (MFG Dept) diagram provided by the embodiment of the present application is intended to be presented from the perspective of machine (Tool);

[0069] Figure 9 FIG. 1 is a structural schematic diagram of a device for detecting delivery abnormality according to an embodiment of the present application;

[0070] Figure 10 FIG. 2 is a structural schematic diagram of a device for processing delivery abnormality according to an embodiment of the present application;

[0071] Figure 11 FIG. 3 is a structural schematic diagram of a computing device according to an embodiment of the present application. DETAILED DESCRIPTION

[0072] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, and not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of the present application.

[0073] The embodiments of the present application provide a method and device for detecting and processing delivery abnormality, which can realize real-time automatic detection of delivery abnormality of semiconductor production equipment, meet the functional requirements of product delivery abnormality information collection, timely and active feedback of abnormality, intelligent exclusion of abnormality and analysis of abnormal problems, thereby improving the work efficiency of delivery abnormality detection and processing, and meeting the operation requirements.

[0074] Among them, the method and the device are based on the same application concept. Since the principles of the method and the device for solving problems are similar, the implementation of the device and the method can be mutually referred to, and the repeated parts will not be described again.

[0075] The terms "first", "second", and the like (if any) in the specification and claims of the embodiments of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device including a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to the process, method, product, or device.

[0076] The following examples and embodiments will be understood only as illustrative examples. Although the present description can refer to "a", "an" or "some" example or embodiment at several places, this does not mean that each such reference is made to the same example or embodiment, also that this feature only applies to a single example or embodiment. Individual features of different embodiments can also be combined to provide other embodiments. Furthermore, terms such as "comprising" and "including" are to be understood as not limiting the described embodiments to only those features that have been mentioned in the respective sentence; such examples and embodiments can also contain features, structures, units, modules etc. that have not been specifically mentioned.

[0077] The various embodiments of the present application will be described in detail below with reference to the accompanying drawings. It should be noted that the order of the display of the embodiments of the present application only represents the order of the embodiments, and does not represent the advantages and disadvantages of the technical solutions provided by the embodiments.

[0078] On a semiconductor production line, a manufacturing execution system (MES) and a real-time dispatch system (RTD) can execute manufacturing and manage product dispatch order cards to control dispatch. However, when system or some restrictive problems occur, product dispatch abnormalities may occur, and if production operation personnel do not discover the abnormalities in time or at all, machine utilization rate and output may be reduced. Therefore, it is particularly important to detect whether the dispatch of the smallest production unit of a semiconductor production device such as a machine is normal in real time, give corresponding prompt information, and intelligently exclude abnormalities based on the detection results, so as to correct errors in time, greatly improve production efficiency, and meet the operation needs of mass production.

[0079] The embodiments of the present application establish a dispatch abnormality detection scheme to timely detect abnormal dispatch events, centrally integrate, classify, actively feedback, automatically correct abnormalities, provide a report analysis, and thus improve problem processing efficiency and abnormality improvement.

[0080] In the embodiments of the present application, a machine is taken as an example of the smallest production unit of a semiconductor production device, but is not limited to a machine, and may be, for example, a chamber.

[0081] The technical solutions provided by the embodiments of the present application include the following four parts:

[0082] I. Detect and integrate WIP (Work In Process, in-process product, specifically the number of chips) information that cannot be normally dispatched when a machine is idle, and generate a report (Loss detection report) using the information.

[0083] The report, for example Figure 1 The department shown refers to the semiconductor production department, abbreviated as department, Figure 1 X and XX in the above are only schematic or exemplary, and are different depending on the content of the report.

[0084] Second, the causes are classified according to the departments of the products in their process stations, and analysis reports are generated, which explain the causes of the abnormalities and the ways to handle the abnormalities (the specific words can be in English or Chinese), so that the operators can quickly master the problems and respond in a timely manner.

[0085] The analysis report can specifically include the following contents, for example:

[0086] The chart presented from the perspective of Lot, for example Figure 2a The chart presented from the perspective of Tool, for example Figure 2b The occurrence rate of the machine idle and waiting for wafers, i.e. the occurrence number / WIP amount; the simple average of the occurrence times of the machine idle and waiting for wafers in the query interval, such as 1 day, i.e. the occurrence times / 24 in 24 hours; the occurrence rate of the machine idle and waiting for wafers, i.e. the occurrence machine number / machine amount. Specifically, for example:

[0087] The columnar diagram in the analysis report corresponds to the left side of the occurrence number of the machine idle and waiting for WIP (IWP Count);

[0088] The curve diagram in the analysis report corresponds to the right side of the occurrence rate (LD Ratio). The occurrence rate is the occurrence number / WIP amount;

[0089] The analysis report can select and view the specific content according to the time condition interval, for example, if the user selects a single day, the analysis report content of the 24-hour interval of that day will be displayed; if the user selects a week, the analysis report content of the 7 days of that week will be displayed; if the user selects a month, the analysis report content of each day of that month will be displayed.

[0090] The user can see the WIP and the amount of products with abnormalities at that time point, as well as the occurrence rate, by moving the mouse focus close to Figure 2a Or Figure 2b Any column in

[0091] The user can see the historical raw data of that time point by clicking on any ratio point.

[0092] The user can see the historical raw data of that time point by clicking on any ratio point.Figure 2b The column shown in the middle is automatically connected to the manufacturing department MFG Dept (PS1~PS5 & other departments), as shown in Figure 2c Clicking the manufacturing department MFG Dept is automatically connected to the Module, as shown in Figure 2d Clicking the Module is automatically connected to the CapaGroup, as shown in Figure 2e The horizontal coordinates A, B, C, etc. represent different capacity machine groups, which are only for illustration and are not specifically listed; clicking the CapaGroup is automatically connected to the Workstation, as shown in Figure 2f F1, F2, F3 represent different workstation sites, which are only for illustration and are not specifically listed; clicking the Workstation is automatically connected to the EQP (+unit), as shown in Figure 2g F1a-F1e represent each different device (+chamber), which is only for illustration and is not specifically listed; clicking the EQP (+unit) is automatically connected to the Reason, as shown in Figure 2h F1a-1 to F1a-12 represent each different reason, which is only for illustration and is not specifically listed, such as a certain machine being inhibited, a certain loading port not being fully automatic, an automated dispatching platform not being reserved, an automated dispatching platform reservation failure, and various detailed reasons for not dispatching goods, etc. Different reasons can be represented by different codes, of course, different codes corresponding to different reasons are pre-set. And these quantities are sorted from more to less.

[0093] It should be noted that Figures 2a-2h It can be understood as a presentation form of the report, and all numerical points or marker symbols in it are only for illustration or example and are different for different reports.

[0094] The product in its process station department, such as the photolithography department (PH), photolithography measurement (PH_MET), etching (EH), diffusion / furnace tube (DF), thin film (TF), chemical mechanical grinding (CMP), etc. The responsible department for producing each corresponding area is PS1~PS5.

[0095] In the embodiments of the present application, the analysis report can be intelligently sorted according to the user's selection, the Lot or the machine (Tool) angle, and the specific content is presented, classified, and analyzed layer by layer, the problem is quickly processed for different nodes, the abnormality rate is reduced, and the machine efficiency is improved.

[0096] III. Through the abnormality detection server, the abnormality is detected in real time, and when the abnormality occurs, the warning information is actively sent to the terminal to notify the production operation responsible person.

[0097] When the machine state is available and in the idle (IDLE) state, but there is no product to be sent to the machine, it is an exception. There are many categories of abnormal reasons, and the most common one is that when the goods cannot be sent, the MES system will give the corresponding code and English description of the code. For example, today the machine is in the IDLE state, and a batch of goods should be sent to this machine. As a result, the system detects that it cannot send goods because the FOUP of this lot is always in transmission, so it can issue an abnormal alarm information that the machine cannot work now. The FOUP is a front-end open silicon wafer carrier box (Front-Opening Unified Pod).

[0098] For example, the warning information is issued through a pop-up window, such as Figure 3 As shown, which includes one or a combination of the following information:

[0099] Wafer batch number (Lot ID);

[0100] Machine number (Tool ID);

[0101] Reason (Reason);

[0102] Whether in the Qtime loop site (Qtime loop, same as Qtime flag, that is, whether the lot is in the Qtime loop or whether the lot has a mark in the Qtime loop); wherein the Q-time is the silicon waiting time limit, which refers to the limit time of the product from one site to the next site;

[0103] How to do.

[0104] The window can also be set by the user to remind again after a few minutes.

[0105] Four, generate an analysis report, which can be intelligently sorted, clearly classified, and analyzed layer by layer from the perspective of Lot or machine (Tool), quickly handle problems at different nodes, reduce the occurrence of exceptions, and improve machine efficiency.

[0106] In the embodiments of the present application, real-time detection of exceptions is performed, and the detected exception information is completely retained in the database. Finally, an analysis report can be provided for analysis.

[0107] Regarding the node, it refers to the process of product output responsible for the smooth production of products on the machine process, and it is concerned about its yield and capacity. The capacity is controlled according to the same process machine group -> the same machine type machine group -> the same process site to control the yield and capacity. The report can view the area, same process machine group, same machine type machine group…from the perspective of machine or product to see which link has the most abnormality, so as to do real-time corresponding processing. For example, from the report, it can be seen that the number or proportion of this transfer abnormality in a certain machine group at a certain time node is very high, so it can quickly check whether the transfer system or the machine end is the problem.

[0108] Referring to Figure 4 In the embodiments of the present application, the machine is detected in real time by the monitor, and the main detection items include, for example: the state of the machine, whether the machine is limited, whether there are waiting products, the loading port of the machine, the state of the goods, etc.

[0109] The monitor saves the detection results of these items to the database, and then loads them to the application end of the server through the data extraction, transformation and loading program (ETL). The application end first classifies the problems, then identifies the categories, and performs debugging processing on the problems that can be automatically updated. The problems that cannot be successfully updated will enter a small cycle of debugging, and the problems that cannot be updated can send alarm information to the user of the terminal. All abnormal information will be saved to the report for subsequent analysis.

[0110] In summary, referring to Figure 4 The overall process provided by the embodiments of the present application is as follows:

[0111] 1. Detecting the delivery abnormality problem by the detector;

[0112] Among them, the delivery abnormality problem, for example, when the machine is available and idle, but there are waiting goods, which is an abnormal problem.

[0113] 2. After obtaining the raw data of the detection results from the database where the detection results are saved through ETL (data extraction / transposition / loading program process), classify the data.

[0114] 3. Automatically determine the abnormality category and automatically debug to generate a report;

[0115] The content of the report, for example, the specific part of the detection abnormality is which part of the production process, and then an instruction is sent to update, such as a system transfer problem, which triggers an instruction to update the transfer state, thereby realizing automatic debugging.

[0116] 4. Active bounce alert information notification;

[0117] 5. A debug small cycle is provided, and no debug is reclassified.

[0118] The debug small cycle is executed again for the first time when the update is not completed.

[0119] For example, when the Lot cannot be shipped due to continuous transmission, the system detects that the classification is first, the category is a transmission problem, and then determines which transmission problem is, and then performs an update process (i.e. an automatic debug process) for the transmission problem. If the update is not successful, it will enter the debug small cycle, i.e. execute the classification judgment and update process again, if the reason is the same as the last time, it will directly enter the next step, i.e. the alarm information triggers the user to confirm.

[0120] The detector described in the embodiments of the application can be called CDP-Watch dog, wherein CDP is a dispatching platform for reservation, shipment and other FAB production behaviors automation, and Watch dog is the name of a timing monitoring small program.

[0121] Then, the specific detection process of the detector is as shown in the following figure: Figure 5

[0122] S701, whether the shipment minimum capacity unit is idle is detected, if yes, step S702 is executed, otherwise, the process is ended.

[0123] The shipment minimum capacity unit is, for example, a machine, a chamber, etc.

[0124] The idle state is defined as SBY (standby time), IDLE (idle) and SESN (warm-up) in the MES system. That is, for example, whether the state of the shipment minimum capacity unit is SBY can be read, if yes, it is considered to be idle, otherwise, it is not in the idle state.

[0125] S702, whether the shipment minimum capacity unit is restricted is detected, i.e. whether the shipment minimum capacity unit is prohibited, locked or stopped, etc., if yes, step S706 is executed, otherwise, step S703 is executed.

[0126] When step S706 is executed, the detection result e is generated, i.e. the result that the shipment minimum capacity unit is prohibited to work is obtained.

[0127] S703, whether there is a work-in-process (Wip) is detected, if yes, step S704 is executed, otherwise, the process is ended.

[0128] ​As for the in-process work-in-process, such as the lot in waiting, it can be a lot without dispatching instruction (no control job lot) and a lot without being put on hold (no on hold).

[0129] S704, detecting whether the load port is in full-automatic mode, if yes, executing step S705, otherwise, executing step S706.

[0130] When executing step S706, the detection result a is generated, that is, the result that the load port state is not full-automatic is obtained.

[0131] The load port is the loading port, that is, the dispatching place of the machine.

[0132] The full-automatic mode is, for example, the auto3 state of the loading port.

[0133] If the loading port is in the auto2 state, it means that it is in the semi-automatic state.

[0134] S705, detecting the lot state.

[0135] The lot state can indicate that the automated dispatching platform has no reservation (no reserve), the automated dispatching platform reservation fails, and there is no batch ID reason.

[0136] S706, generating a detection result.

[0137] According to the lot state, the corresponding detection result is generated, for example, one of the following detection results:

[0138] b, the automated dispatching platform has no reservation;

[0139] c, the automated dispatching platform reservation fails;

[0140] d, no batch ID reason.

[0141] The automated dispatching platform is a collaborative automated dispatching platform (CDP, Cohesion Dispatch Platform), which is an automated platform for reservation, dispatching and other FAB production behaviors, and will execute reservation under normal system conditions.

[0142] The No batch ID reason is an abnormal reason (with code number + reason) given by the RTD when the goods cannot be dispatched to the machine, so the application embodiment gives the Chinese translation and the information on how to handle the problem, so that when reporting the abnormal report, there are Chinese and how to handle the content, which can be referred to by the user.

[0143] S707. Store the test results in the database.

[0144] Based on the above test results, further problem-solving procedures can be implemented.

[0145] See Figure 6 In this embodiment of the application, the data sources for handling abnormal problems can be four databases: the database of detection results of the automated dispatching platform (i.e., the database mentioned in step S707 above), the database of the production capacity system, the database of the real-time dispatching system, and the database of the production parameter system.

[0146] The detection results are stored in the database of detection results of the automated dispatching platform.

[0147] The server can read data from one or more of the above databases and classify the problems, for example, such as Figure 6 As shown, the problems are divided into the following ten categories:

[0148] 1. Limitations;

[0149] 2. Issues with automated work dispatching platforms;

[0150] 3. Loading port issue;

[0151] 4. Transmission issues;

[0152] 5. Special rule issues;

[0153] 6. Special marking issues;

[0154] 7. Q-time control issues;

[0155] 8. Experiment with the Lot problem;

[0156] 9. Issues related to the control plate;

[0157] 10. Problems caused by multiple shipments being placed in the same FOUP.

[0158] Optionally, the server stores the above classification results in a production materials database;

[0159] The server idle machine detection system determines whether the automatic update can be performed to solve the above problems. The automatic update is a way to solve the problem, such as updating the machine system or updating the machine state, so as to determine whether the corresponding problem can be solved by the automatic update, that is, the debugging process is performed. Some problems can be solved by automatic update, and some problems may not be solved by automatic update. Then, for the problems that cannot be solved, the server idle machine detection system can output alarm information to the user through the client, such as mobile phone, computer and the like. The alarm information, such as Figure 3 The server idle machine detection system can also generate a report using the abnormal information and store it to the report system (which can be another server to implement), and then generate a cause analysis report through the report system and provide it to the user.

[0160] Among them, the data sources in the report generation or classification rule are divided into CDP detection data and CDP benchmark reference data, and the detection data problems include machine and other hardware error, program parameter error, human-induced cause error, etc.

[0161] In summary, Figure 6 The server working content includes:

[0162] According to the CDP detection data and the CDP benchmark reference data, the CDP detection result data is classified;

[0163] Make a debugging judgment;

[0164] Generate a report.

[0165] The report will extract the required data from the above four data sources, and do the copying / data extraction, transposition and loading processes in the application server, and finally summarize, collect all the abnormalities to the report, which can be analyzed; The application program on the mobile phone and the computer can also send warning information to the user to warn the user how to deal with the abnormality. The application server will classify, store the classification results in the production data database, and then make category judgment and automatic update, and finally upload the processing results to the report (which can be another server or terminal), and the terminal such as mobile phone and computer.

[0166] In summary, referring to Figure 7 At the detector end, the method for detecting delivery exception provided by the embodiment of the application comprises:

[0167] S101, determining that the detected object is in an idle state and cannot be delivered; wherein the detected object is a minimum capacity unit of a semiconductor production device;

[0168] S102, determining the detection result by detecting one or a combination of the following contents:

[0169] whether the detected object is prohibited from working;

[0170] whether there is a work-in-process in a waiting state;

[0171] whether the loading port is in a full-automatic state;

[0172] a state of a wafer group.

[0173] Optionally, the determining the detection result comprises:

[0174] if it is detected that the detected object is prohibited from working, determining the detection result as that the detected object is prohibited from working; and if it is detected that the detected object is not prohibited from working, further detecting whether there is a work-in-process in a waiting state;

[0175] if there is a work-in-process in a waiting state, further detecting whether the loading port is in a full-automatic state; if the loading port is not in the full-automatic state, determining the detection result as that the loading port is in a non-full-automatic state; if the loading port is in the full-automatic state, further detecting a state of a wafer group, and determining the detection result according to the state of the wafer group.

[0176] Optionally, according to the state of the wafer group, the detection result is determined as one of the following:

[0177] the automation dispatching platform has no reservation;

[0178] the automation dispatching platform fails to reserve;

[0179] no cause of dispatching failure.

[0180] Optionally, the method further comprises:

[0181] storing the detection result in a detection result database of the automation dispatching platform.

[0182] Referring to Figure 8 , on the server side shown in Figure 6 , the embodiment of the present application provides a processing method for dispatching exception, comprising:

[0183] S201, acquiring the detection result from a database, and classifying problems causing dispatching exception based on the detection result, to generate a classification result;

[0184] S202, performing debugging processing for the classification result, and generating feedback information and / or exception information to be sent to a user according to a processing result;

[0185] S203, send the feedback information to at least one client, and / or generate an analysis report using the abnormal information, and send the analysis report to at least one client.

[0186] Optionally, the method further comprises:

[0187] acquiring data from a capacity system database, and / or a real-time dispatch system database, and / or a production parameter system database, and storing the data into a preset production material database; and storing the detection result acquired from the detection result database into the production material database; the classification result is generated based on data read from the production material database.

[0188] The following describes the device or apparatus provided by the embodiments of the present application, and the same or corresponding technical features described in the above method are not repeated.

[0189] Referring to Figure 9 At the detector end, the device for detecting dispatching abnormality provided by the embodiments of the present application comprises:

[0190] The first unit 11 is configured to determine that the detected object is in an idle state and cannot be dispatched; wherein the detected object is a minimum capacity unit of a semiconductor production device;

[0191] The second unit 12 is configured to determine the detection result by detecting one or a combination of the following contents:

[0192] Whether the detected object is prohibited from working;

[0193] Whether there is a work-in-process in a waiting state;

[0194] Whether the loading port is in a full-automatic state;

[0195] The state of the wafer group.

[0196] Optionally, the second unit 12 is configured to:

[0197] If it is detected that the detected object is prohibited from working, it is determined that the detection result is that the detected object is prohibited from working; if it is detected that the detected object is not prohibited from working, it is further detected whether there is a work-in-process in a waiting state;

[0198] If there is a work-in-process in a waiting state, it is further detected whether the loading port is in a full-automatic state; if the loading port is not in a full-automatic state, it is determined that the detection result is that the loading port is in a non-full-automatic state; if the loading port is in a full-automatic state, it is further detected the state of the wafer group, and the detection result is determined according to the state of the wafer group.

[0199] Optionally, the second unit 12 determines the detection result to be one of the following according to the state of the wafer group:

[0200] The automated dispatch platform has no appointment;

[0201] The automated dispatch platform fails to make an appointment;

[0202] No reason for no dispatch.

[0203] Optionally, the apparatus further comprises:

[0204] A third unit 13 is configured to store the detection result in a detection result database of the automated dispatch platform.

[0205] Referring to Figure 10 , in Figure 6 the server end, the processing apparatus for dispatching exceptions provided by the embodiments of the present application comprises:

[0206] A classification unit 21 is configured to obtain a detection result obtained by the apparatus for detecting dispatching exceptions, and classify problems causing the dispatching exception based on the detection result, and generate a classification result;

[0207] A debugging unit 22 is configured to perform debugging processing on the classification result, and generate feedback information and / or exception information to be sent to a user according to the processing result;

[0208] A sending unit 23 is configured to send the feedback information to at least one client, and / or generate an analysis report using the exception information, and send the analysis report to at least one client.

[0209] Optionally, the classification unit 21 is further configured to:

[0210] obtain data from a production capacity system database, and / or a real-time dispatch system database, and / or a production parameter system database, and store the data in a preset production material database; and store the detection result obtained from the detection result database in the production material database; the classification result is generated based on data read from the production material database.

[0211] It should be noted that the division of units in the embodiments of the present application is illustrative, and is only a logical function division. In actual implementation, another division mode can be used. In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present alone, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0212] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or say the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform all or part of the steps of the methods described in various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0213] Referring to Figure 11 The computing device provided in the embodiments of the present application can be specifically a server, a desktop computer, a portable computer, a smart phone, a tablet computer, a personal digital assistant (PDA), etc. The computing device can include a central processing unit (CPU) 500, a memory 520, a transceiver 510, and an input / output device, etc. The input device can include a keyboard, a mouse, a touch screen, etc. The output device can include a display device, such as a liquid crystal display (LCD), a cathode ray tube (CRT), etc.

[0214] The memory 520 can include a read-only memory (ROM) and a random access memory (RAM), and provide the processor with program instructions and data stored in the memory. In the embodiments of the present application, the memory can be used to store the programs of any of the methods provided in the embodiments of the present application.

[0215] The central processing unit 500 processes the program instructions stored in the memory, and the processor is used to execute any of the methods provided in the embodiments of the present application according to the obtained program instructions.

[0216] The embodiments of the present application further provide a computer program product or computer program, which comprises computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to enable the computer device to perform any of the methods described in the above embodiments. The program product can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium may, for example, be but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination of the above. More specific examples (non-exhaustive list) of the readable storage medium include an electrical connection having one or more wires, a portable disc, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0217] The embodiments of the present application provide a computer readable storage medium for storing computer program instructions for the apparatus provided in the above embodiments of the present application, which contains programs for executing any of the methods provided in the above embodiments of the present application. The computer readable storage medium can be a non-transitory computer readable medium.

[0218] The computer readable storage medium can be any available medium or data storage device that can be accessed by a computer, including but not limited to a magnetic storage (such as a floppy disk, a hard disk, a magnetic tape, a magneto-optical disk (MO), etc.), an optical storage (such as a CD, a DVD, a BD, a HVD, etc.), and a semiconductor storage (such as a ROM, an EPROM, an EEPROM, a non-volatile memory (NAND FLASH), a solid state disk (SSD)), etc.

[0219] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt a computer program product implemented on one or more computer readable storage media containing computer usable program code (including but not limited to magnetic disk storage and optical storage, etc.).

[0220] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure One One or more processes and / or boxes Figure One A device that provides the functions specified in one or more boxes.

[0221] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure One One or more processes and / or boxes Figure One The function specified in one or more boxes.

[0222] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure One One or more processes and / or boxes Figure One The steps of the function specified in one or more boxes.

[0223] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method of detecting a shipment anomaly, characterized by, The method comprises: determining that the detected object is in an idle state and unable to dispatch goods; wherein the detected object is a minimum capacity unit of a semiconductor production device; determining a detection result by detecting one or a combination of the following: whether the detected object is prohibited from working; whether there is a work-in-process in a waiting state; whether the loading port is in a fully automatic state; a state of a wafer group; the determining of the detection result comprises: if it is detected that the detected object is prohibited from working, determining that the detection result is that the detected object is prohibited from working; if it is detected that the detected object is not prohibited from working, further detecting whether there is a work-in-process in a waiting state; if there is a work-in-process in a waiting state, further detecting whether the loading port is in a fully automatic state; if the loading port is not in a fully automatic state, determining that the detection result is that the loading port is in a non-full automatic state; if the loading port is in a full automatic state, further detecting a state of a wafer group, and determining the detection result according to the state of the wafer group.

2. The method of claim 1, wherein, According to the state of the wafer group, the detection result is one of: the automated dispatching platform has no reservation; the automated dispatching platform reservation fails; there is no reason for dispatching goods.

3. The method of claim 1, wherein, The method further comprises: storing the detection result in a detection result database of the automated dispatching platform.

4. A method of handling a shipment exception, the method comprising: receiving a shipment exception; and providing a notification of the shipment exception to a user. The method comprises: obtaining a detection result obtained by the method of claim 3, and classifying problems causing dispatching exceptions based on the detection result to generate a classification result; performing debugging processing on the classification result, and generating feedback information and / or exception information to be sent to a user according to a processing result; sending the feedback information to at least one client, and / or generating an analysis report using the exception information and sending the analysis report to at least one client.

5. The method of claim 4, wherein, The method further comprises: obtaining data from a capacity system database, and / or a real-time dispatching system database, and / or a production parameter system database and storing the data into a preset production data database; and storing the detection result obtained from the detection result database into the production data database; the classification result is generated based on data read from the production data database.

6. A delivery abnormality detecting device characterized by comprising: comprises: a first unit configured to determine that a detected object is in an idle state and unable to dispatch goods; wherein the detected object is a minimum capacity unit of a semiconductor production device; a second unit configured to determine a detection result by detecting one or a combination of the following: whether the detected object is prohibited from working; whether there is a work-in-process in a waiting state; whether the loading port is in a fully automatic state; a state of a wafer group; the determining of the detection result comprises: if it is detected that the detected object is prohibited from working, determining that the detection result is that the detected object is prohibited from working; if it is detected that the detected object is not prohibited from working, further detecting whether there is a work-in-process in a waiting state; If there is a work-in-process in the waiting state, further detecting whether the loading port is in the full-automatic state; if the loading port is not in the full-automatic state, determining that the detection result is that the loading port is in the non-full-automatic state; if the loading port is in the full-automatic state, further detecting the state of the wafer group, and determining the detection result according to the state of the wafer group.

7. The apparatus of claim 6, wherein, The second unit is configured to: If it is detected that the detected object is prohibited from working, determining that the detection result is that the detected object is prohibited from working; if it is detected that the detected object is not prohibited from working, further detecting whether there is a work-in-process in the waiting state; If there is a work-in-process in the waiting state, further detecting whether the loading port is in the full-automatic state; if the loading port is not in the full-automatic state, determining that the detection result is that the loading port is in the non-full-automatic state; if the loading port is in the full-automatic state, further detecting the state of the wafer group, and determining the detection result according to the state of the wafer group.

8. The apparatus of claim 6 or 7, wherein, The second unit determines the detection result to be one of the following according to the state of the wafer group: The automation dispatching platform has no reservation; The automation dispatching platform fails to reserve; There is no reason for dispatching.

9. The apparatus of claim 6 or 7, wherein, The apparatus further includes: A third unit configured to store the detection result in a detection result database of the automation dispatching platform.

10. A delivery exception processing apparatus characterized by comprising: The apparatus further includes: A classification unit configured to obtain the detection result obtained by the apparatus of claim 9, and classify problems causing dispatching exceptions based on the detection result to generate a classification result; A debugging unit configured to perform debugging processing on the classification result, and generate feedback information and / or exception information to be sent to a user according to a processing result; A sending unit configured to send the feedback information to at least one client, and / or generate an analysis report using the exception information, and send the analysis report to at least one client.

11. The apparatus of claim 10, wherein, The classification unit is further configured to: Obtain data from a production capacity system database, and / or a real-time dispatching system database, and / or a production parameter system database, and store the data into a preset production material database; and store the detection result obtained from the detection result database into the production material database; The classification result is generated based on data read from the production material database.

12. A computing device, comprising: The apparatus further includes: A memory configured to store program instructions; A processor configured to invoke the program instructions stored in the memory, and perform the method of any one of claims 1 to 5 according to the obtained program execution right.

13. A computer program product for a computer, characterized in that The software code portion is configured to execute the method of any one of claims 1 to 5 when the product is running on the computer.

14. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer executable instructions, and the computer executable instructions are configured to cause the computer to perform the method of any one of claims 1 to 5. The computer readable storage medium stores computer executable instructions, and the computer executable instructions are configured to cause the computer to perform the method of any one of claims 1 to 5.

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