CN108062075B - Equipment safety monitoring system and method - Google Patents
Equipment safety monitoring system and method Download PDFInfo
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- CN108062075B CN108062075B CN201610976941.8A CN201610976941A CN108062075B CN 108062075 B CN108062075 B CN 108062075B CN 201610976941 A CN201610976941 A CN 201610976941A CN 108062075 B CN108062075 B CN 108062075B
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- 238000000034 method Methods 0.000 title claims abstract description 121
- 238000012544 monitoring process Methods 0.000 title claims abstract description 50
- 230000008569 process Effects 0.000 claims abstract description 98
- 238000005070 sampling Methods 0.000 claims abstract description 91
- 230000002159 abnormal effect Effects 0.000 claims abstract description 58
- 230000006872 improvement Effects 0.000 claims abstract description 40
- 230000009471 action Effects 0.000 claims abstract description 24
- 230000008859 change Effects 0.000 claims abstract description 12
- 238000012423 maintenance Methods 0.000 claims description 7
- 230000000737 periodic effect Effects 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 abstract description 11
- 238000001514 detection method Methods 0.000 description 5
- 239000004065 semiconductor Substances 0.000 description 5
- 239000000463 material Substances 0.000 description 4
- 230000002411 adverse Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- 230000005856 abnormality Effects 0.000 description 2
- 238000005530 etching Methods 0.000 description 2
- 238000003754 machining Methods 0.000 description 2
- 239000002699 waste material Substances 0.000 description 2
- 230000002860 competitive effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 239000002002 slurry Substances 0.000 description 1
- 238000009966 trimming Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/4185—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by the network communication
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/31—From computer integrated manufacturing till monitoring
- G05B2219/31088—Network communication between supervisor and cell, machine group
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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- Engineering & Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The invention discloses an equipment safety monitoring system and recurrence. The equipment safety monitoring system provided by the invention comprises an equipment setting module, a monitoring module and a monitoring module, wherein the equipment setting module is used for monitoring abnormal actions of equipment; the equipment sampling module is used for simulating a reference process curve and a reference fitting degree value of equipment, the reference process curve is combined with a real-time process curve to obtain a real-time fitting degree value, and dynamic sampling operation is executed according to the reference fitting degree value, the real-time fitting degree value and the abnormal action; the process analysis module is used for analyzing the abnormal action of the equipment and providing an improvement action; and the equipment improvement module is used for maintaining the equipment according to the change of the dynamic sampling and the improvement action. Through the cooperation of the four parts, the information is fed back in real time, the hysteresis of finding problems of the equipment is avoided, and the production utilization rate of the equipment is improved.
Description
Technical Field
The invention relates to the technical field of semiconductors, in particular to a system and a method for monitoring equipment safety.
Background
The development of the current semiconductor manufacturing industry is more and more rapid, along with various process requirements of customers, the complexity and diversity of the manufacturing process are continuously improved, the competitive pressure among enterprises is more and more large, and high-quality and high-efficiency production is more and more emphasized by the semiconductor manufacturing industry according to the requirements of the customers. Under the condition of certain production cost and factory scale, the safety condition of the equipment can be better monitored and the utilization efficiency of the equipment can be improved by adopting a more reasonable and effective equipment process monitoring mode.
The existing monitoring mode of equipment in the semiconductor manufacturing industry is generally a method for sampling and testing the parameters of the equipment at regular intervals, and whether the parameters of the equipment deviate or not can be detected by the mode, so that the stability and the safety of the equipment are further reflected. However, this method has a certain hysteresis, and cannot respond to the safety of the equipment in real time, and if the equipment has a potential, a great loss is caused during the detection. And needs separate personnel to operate, thus causing waste in manpower and material resources.
Disclosure of Invention
The invention aims to provide a system and a method for monitoring equipment safety, which are used for monitoring equipment in real time and feeding back abnormal conditions in time.
In order to solve the above technical problem, the present invention provides an equipment safety monitoring system, including:
the equipment setting module is used for monitoring abnormal actions of the equipment;
the equipment sampling module is used for simulating a reference process curve and a reference fitting degree value of equipment, the reference process curve is combined with a real-time process curve to obtain a real-time fitting degree value, and dynamic sampling operation is executed according to the reference fitting degree value, the real-time fitting degree value and the abnormal action;
the process analysis module is used for analyzing the abnormal action of the equipment and providing an improvement action; and
and the equipment improvement module is used for maintaining the equipment according to the change of the dynamic sampling and the improvement action.
Optionally, for the equipment safety monitoring system, the equipment sampling module is connected to a database, the database stores a historical process recipe, and the equipment sampling module simulates a reference process curve and a reference fitting degree value of the equipment according to the historical process recipe.
Optionally, for the equipment safety monitoring system, the reference fitting degree value is 0.982-0.988.
Optionally, for the equipment safety monitoring system, the abnormal actions include equipment periodic maintenance, abnormal downtime, and unstable process improvement.
Optionally, for the equipment safety monitoring system, the dynamic sampling operation has a sampling rate, and if the real-time fitting degree value is smaller than the reference fitting degree value, the sampling rate is increased; and if the real-time fitting degree value is greater than or equal to the reference fitting degree value, keeping the sampling rate unchanged.
Optionally, for the equipment safety monitoring system, the reference sampling rate is 1/25.
Optionally, for the plant safety monitoring system, the increased sampling rate is increased to 3/25.
The invention also provides a device safety monitoring method, which comprises the following steps:
providing a product to be processed, and processing the product in equipment to obtain a real-time process curve;
an equipment sampling module simulates a reference process curve and a reference fitting degree value of equipment and obtains a real-time fitting degree value according to the real-time process curve and the reference process curve;
the equipment sampling module combines the real-time fitting degree value and the reference fitting degree value and abnormal actions monitored by an equipment setting module to execute dynamic sampling operation;
a process analysis module analyzes the abnormal action of the equipment and provides an improvement action; and
an equipment improvement module maintains the equipment according to the change of the dynamic sampling and the improvement action.
Optionally, for the equipment safety monitoring system, the equipment sampling module is connected to a database, the database stores a historical process recipe, and the equipment sampling module simulates a reference process curve and a reference fitting degree value of the equipment according to the historical process recipe.
Optionally, for the equipment safety monitoring system, the reference fitting degree value is 0.982-0.988.
Optionally, for the equipment safety monitoring system, the abnormal actions include equipment periodic maintenance, abnormal downtime, and unstable process improvement.
Optionally, for the equipment safety monitoring system, the dynamic sampling operation has a sampling rate, and if the real-time fitting degree value is smaller than the reference fitting degree value, the sampling rate is increased; and if the real-time fitting degree value is greater than or equal to the reference fitting degree value, keeping the sampling rate unchanged.
Optionally, for the equipment safety monitoring system, the reference sampling rate is 1/25.
Optionally, for the plant safety monitoring system, the increased sampling rate is increased to 3/25.
The equipment safety monitoring system and the method provided by the invention comprise an equipment sampling module, a real-time fitting degree value and a real-time fitting degree value, wherein the equipment sampling module is used for simulating a reference process curve and a reference fitting degree value of equipment; the equipment sampling module is used for executing dynamic sampling operation according to the abnormal action; the process analysis module is used for analyzing the abnormal action of the equipment and providing an improvement action; and the equipment improvement module is used for maintaining the equipment according to the change of the dynamic sampling and the improvement action. Through the cooperation of the four parts, the information is fed back in real time, so that the hysteresis of finding problems of the equipment is avoided, the manpower and material resources are saved while the safety of the equipment is monitored efficiently, and the production utilization rate of the equipment is improved.
Drawings
FIG. 1 is a schematic diagram of a safety monitoring system for equipment according to the present invention;
fig. 2 is a flow chart of the device safety monitoring method of the present invention.
Detailed Description
The equipment safety monitoring system and method of the present invention will now be described in more detail with reference to the schematic drawings, in which preferred embodiments of the invention are shown, it being understood that one skilled in the art may modify the invention herein described while still achieving the advantageous results of the invention. Accordingly, the following description should be construed as broadly as possible to those skilled in the art and not as limiting the invention.
The invention is described in more detail in the following paragraphs by way of example with reference to the accompanying drawings. Advantages and features of the present invention will become apparent from the following description and from the claims. It is to be noted that the drawings are in a very simplified form and are not to precise scale, which is merely for the purpose of facilitating and distinctly claiming the embodiments of the present invention.
The inventor finds that the equipment safety monitoring method commonly used in the semiconductor industry at present tests relevant parameters of equipment regularly according to a certain frequency in long-term production work, and the method has certain hysteresis and cannot react with the equipment in real time; and needs separate personnel to operate, thus causing waste in manpower and material resources.
Accordingly, the inventor proposes a device safety monitoring system, as shown in fig. 1, including:
the equipment setting module is used for monitoring abnormal actions of the equipment;
the equipment sampling module is used for simulating a reference process curve and a reference fitting degree value of equipment, the reference process curve is combined with a real-time process curve to obtain a real-time fitting degree value, and dynamic sampling operation is executed according to the reference fitting degree value, the real-time fitting degree value and the abnormal action;
the process analysis module is used for analyzing the abnormal action of the equipment and providing an improvement action; and
and the equipment improvement module is used for maintaining the equipment according to the change of the dynamic sampling and the improvement action.
Specifically, the equipment sampling module is connected with a database, a historical process recipe (process recipe) is stored in the database, and the equipment sampling module simulates a reference process curve and a reference fitting degree value of the equipment according to the historical process recipe. The process curves of the present invention are illustrated here: at least one factor can be found during a certain process, and the at least one factor can characterize the progress of the process, so that the variation curve of the at least one factor during the process can be obtained, namely the process curve. For example, for the etching process, the light intensity signal can be detected to obtain the variation curve of the light intensity in the etching process, and the variation curve is used as the process curve; for another example, during CMP, pH, slurry flow rate, etc. can be detected as a process curve. The reference process curve is then a process curve obtained from historical data, for example, by mathematical modeling. The goodness of fit (GOF) refers to the matching degree between the real-time process curve of the equipment during the machining process and the reference process curve, and for the sake of distinction, the GOF is called a real-time goodness of fit value, and a higher real-time goodness of fit value indicates a higher reliability of the real-time process. In order to judge the real-time process, a reference fitting degree value is set, and when the real-time fitting degree value is greater than or equal to the reference fitting degree value, the equipment is normal and the process is stable; when the real-time fit degree value is smaller than the reference fit degree value, the equipment is possibly abnormal, and the process is influenced.
In one embodiment of the invention, the reference fitting degree value is set to be 0.982-0.988.
Specifically, the abnormal actions include equipment maintenance (PM), abnormal downtime (down), process instability improvement (tubing), and the like, and the abnormal actions may affect the actions of the equipment, for example, may adversely affect the safety and stability of the equipment. Therefore, in the present invention, these abnormal actions are included in the observation range, and if the abnormal action occurs, the sampling rate of the dynamic sampling operation is changed. For example, the sampling rate has an initial value, such as 1/25 under normal conditions, i.e., one product per lot (typically 25 products per lot) is extracted, and if abnormal operation occurs, the initial value is increased, such as to 2/25-5/25. It is understood that the initial value of the sampling rate and the variation thereof are not limited to the scope of the present invention, and those skilled in the art can more effectively detect and prevent the product abnormality caused by the abnormal operation by only increasing the original sampling rate.
The process analysis module mainly analyzes the influence and principle of the abnormal action of the equipment on the process curve, provides subsequent improvement action on the basis of analysis, and arranges the subsequent improvement action to be used as a reference for analyzing the abnormal action of the equipment.
The equipment improvement module can feed back the dynamic sampling change and the improvement action to a technician in real time, for example, when the fitting degree value of an equipment process curve becomes larger and the sampling rate becomes larger, the related information can be fed back to the technician in real time, the technician improves according to the analysis provided by the process analysis module, and processes in time, for example, trimming and testing of related parts of the equipment are carried out, and (more) affected products are prevented from being generated.
Referring to fig. 2, a method for monitoring device safety by using the device safety monitoring system of the present invention is described, where the method specifically includes:
providing a product to be processed, and processing the product in equipment to obtain a real-time process curve;
an equipment sampling module simulates a reference process curve and a reference fitting degree value of equipment and obtains a real-time fitting degree value according to the real-time process curve and the reference process curve; specifically, the equipment sampling module is connected with a database, a historical process recipe (process recipe) is stored in the database, and the equipment sampling module simulates a reference process curve and a reference fitting degree value of the equipment according to the historical process recipe. This process may be accomplished by mathematical modeling, for example. The goodness of fit (GOF) refers to the matching degree between the real-time process curve of the equipment during the machining process and the reference process curve, and for the sake of distinction, the GOF is called a real-time goodness of fit value, and a higher real-time goodness of fit value indicates a higher reliability of the real-time process. In order to judge the real-time process, a reference fitting degree value is set, and when the real-time fitting degree value is greater than or equal to the reference fitting degree value, the equipment is normal and the process is stable; when the real-time fit degree value is smaller than the reference fit degree value, the equipment is possibly abnormal, and the process is influenced.
The equipment sampling module combines the real-time fitting degree value and the reference fitting degree value and abnormal actions monitored by an equipment setting module to execute dynamic sampling operation; specifically, the abnormal actions include equipment maintenance (PM), abnormal downtime (down), process instability improvement (tubing), and the like, and the abnormal actions may affect the actions of the equipment, for example, may adversely affect the safety and stability of the equipment. Therefore, in the present invention, these abnormal actions are included in the observation range, and if the abnormal action occurs, the sampling rate of the dynamic sampling operation is changed. For example, the sampling rate has an initial value, such as 1/25 under normal conditions, i.e., one product per lot (typically 25 products per lot) is extracted, and if abnormal operation occurs, the initial value is increased, such as to 2/25-5/25. It is understood that the initial value of the sampling rate and the variation thereof are not limited to the scope of the present invention, and those skilled in the art can more effectively detect and prevent the product abnormality caused by the abnormal operation by only increasing the original sampling rate. If the real-time fitting degree value is smaller than the reference fitting degree value, which indicates that equipment is possibly abnormal, the detection force needs to be increased for the product, and the sampling rate is made to be larger than the initial value; and if the real-time fitting degree value is greater than or equal to the reference fitting degree value, indicating that the equipment is still in a better reliability degree, and keeping the sampling rate unchanged. If the initial value is increased due to the abnormal action, after monitoring for a certain period (for example, 1 to 8 hours), if the real-time fitting degree value is still greater than or equal to the reference fitting degree value, the initial value can be recovered, that is, the abnormal action does not have adverse effect on the equipment.
When the initial value of the sampling rate is increased due to the abnormal action, a process analysis module analyzes the abnormal action of the equipment and provides an improvement action; and
an equipment improvement module maintains the equipment according to the change of the dynamic sampling and the improvement action.
For example, the reference goodness-of-fit value is 0.982-0.988, the real-time goodness-of-fit value is 0.98 and is less than the minimum value of the reference goodness-of-fit value, which indicates that the equipment may be abnormal, on one hand, if the initial value of the sampling rate is increased, for example, the initial value is 1/25, the initial value is increased to 2/25, if the initial value is less than 0.982, the sampling rate is further increased on the basis of increasing the initial value, for example, the sampling rate is increased to 3/25 on the basis of 2/25, and the process analysis module analyzes the influence and principle of the abnormal action on the process curve, provides subsequent improvement actions on the basis of analysis, and arranges the change of the sampling rate and the detection condition of sampling, and transmits the change of the sampling rate and the detection condition to the equipment improvement module, and technicians process the equipment improvement module in time, preventing the production of (more) affected products. On the other hand, if no abnormal action of the equipment is found, only the sampling rate needs to be increased on the basis of the initial value, and then the historical data and the sampling detection result of the process analysis module can be combined, so that the abnormal condition of the equipment can be analyzed, for example, whether a new problem occurs or not, or whether an old problem recurs or whether regular maintenance is needed, and the like, so that the abnormal condition can be solved as early as possible, and the loss of the product can be avoided.
In summary, the system and method for monitoring equipment safety provided by the present invention includes an equipment sampling module, configured to simulate a reference process curve and a reference goodness-of-fit value of equipment, where the reference process curve is combined with a real-time process curve to obtain a real-time goodness-of-fit value, and a dynamic sampling operation is performed according to the reference goodness-of-fit value and the real-time goodness-of-fit value; the equipment sampling module is used for executing dynamic sampling operation according to the abnormal action; the process analysis module is used for analyzing the abnormal action of the equipment and providing an improvement action; and the equipment improvement module is used for maintaining the equipment according to the change of the dynamic sampling and the improvement action. Through the cooperation of the four parts, the information is fed back in real time, so that the hysteresis of finding problems of the equipment is avoided, the manpower and material resources are saved while the safety of the equipment is monitored efficiently, and the production utilization rate of the equipment is improved.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (14)
1. An equipment safety monitoring system comprising:
the equipment setting module is used for monitoring abnormal actions of the equipment;
the equipment sampling module is used for simulating a reference process curve and a reference fitting degree value of equipment, the reference process curve is combined with a real-time process curve to obtain a real-time fitting degree value, and dynamic sampling operation is executed according to the reference fitting degree value, the real-time fitting degree value and the abnormal action;
the process analysis module is used for analyzing the abnormal action of the equipment and providing an improvement action; and
and the equipment improvement module is used for maintaining the equipment according to the change of the dynamic sampling and the improvement action.
2. The system of claim 1, wherein the tool sampling module is connected to a database, the database stores historical process recipes, and the tool sampling module simulates a baseline process curve and a reference goodness-of-fit value of the tool according to the historical process recipes.
3. The equipment safety monitoring system of claim 1, wherein the reference goodness-of-fit value is 0.982-0.988.
4. The equipment safety monitoring system of claim 1, wherein the abnormal actions include equipment scheduled maintenance, abnormal downtime, and process instability improvement.
5. The equipment safety monitoring system of claim 1, wherein the dynamic sampling operation has a sampling rate having an initial value.
6. The equipment safety monitoring system of claim 5, wherein the initial value of the sampling rate is 1/25.
7. An equipment safety monitoring method comprises the following steps:
providing a product to be processed, and processing the product in equipment to obtain a real-time process curve;
an equipment sampling module simulates a reference process curve and a reference fitting degree value of equipment and obtains a real-time fitting degree value according to the real-time process curve and the reference process curve;
the equipment sampling module combines the real-time fitting degree value and the reference fitting degree value and abnormal actions monitored by an equipment setting module to execute dynamic sampling operation;
a process analysis module analyzes the abnormal action of the equipment and provides an improvement action; and
an equipment improvement module maintains the equipment according to the change of the dynamic sampling and the improvement action.
8. The method of claim 7, wherein the tool sampling module is connected to a database, the database stores historical process recipes, and the tool sampling module simulates a baseline process curve and a reference goodness-of-fit value of the tool according to the historical process recipes.
9. The equipment safety monitoring method according to claim 7, wherein the reference fitness value is 0.982-0.988.
10. The equipment safety monitoring method according to claim 7, wherein the abnormal actions include equipment periodic maintenance, abnormal downtime, and improvement of process instability.
11. The device security monitoring method of claim 7, wherein the dynamic sampling operation has a sampling rate having an initial value, and wherein the initial value is increased if the device is malfunctioning.
12. The equipment safety monitoring method according to claim 11, wherein if the real-time fit degree value is smaller than the reference fit degree value, the sampling rate is made larger than an initial value; and if the real-time fitting degree value is greater than or equal to the reference fitting degree value, keeping the sampling rate unchanged.
13. The device security monitoring method of claim 12, wherein the initial value of the sampling rate is 1/25.
14. The equipment safety monitoring method according to claim 13, wherein the initial value of the sampling rate can be increased to 2/25-5/25.
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| CN201610976941.8A CN108062075B (en) | 2016-11-07 | 2016-11-07 | Equipment safety monitoring system and method |
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| CN201610976941.8A CN108062075B (en) | 2016-11-07 | 2016-11-07 | Equipment safety monitoring system and method |
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| CN108062075B true CN108062075B (en) | 2019-12-27 |
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| US7487064B2 (en) * | 2003-07-18 | 2009-02-03 | Chartered Semiconductor Manufacturing, Ltd. | Method for detecting and monitoring defects |
| CN102117731B (en) * | 2009-12-31 | 2013-01-02 | 中芯国际集成电路制造(上海)有限公司 | Method and device for monitoring measurement data in process production flow of semiconductor |
| EP2453395A1 (en) * | 2010-11-15 | 2012-05-16 | Deloitte Innovation B.V. | Method and system to analyze processes |
| CN102881619B (en) * | 2012-10-12 | 2015-01-07 | 上海华力微电子有限公司 | Yield monitoring system and monitoring method thereof |
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