CN104932428A - Method and device for detecting early failure of hardware - Google Patents
Method and device for detecting early failure of hardware Download PDFInfo
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- CN104932428A CN104932428A CN201410101114.5A CN201410101114A CN104932428A CN 104932428 A CN104932428 A CN 104932428A CN 201410101114 A CN201410101114 A CN 201410101114A CN 104932428 A CN104932428 A CN 104932428A
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- hardware
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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
- G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
- G05B19/406—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
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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
- G05B2219/34—Director, elements to supervisory
- G05B2219/34294—Diagnostic, locate failures
Abstract
The invention discloses a method and a device for detecting an early failure of a hardware, wherein the method comprises the steps of acquiring original data in processing a wafer by a wafer processing machine tool; performing statistics on predetermined event information of the wafer processing machine tool according to the original data, wherein the predetermined event information comprises the type of the predetermined event and occurrence frequency of the predetermined event; and according to the predetermined event information, determining the early fault condition, which corresponds with the type, of the hardware in the wafer processing machine tool. Through the method and the device of the invention, a problem of large-amount wafer discarding caused by incapability of detecting the early failure of hardware in related technology is settled. The invention provides the method for detecting the early failure of the hardware and reduces rejection rate of the wafer.
Description
Technical field
The present invention relates to the communications field, in particular to a kind of hardware Early Failure Detection method and apparatus.
Background technology
Current, scrapping of wafer mainly comes from the aging of hardware component, and such as, 3046 wafers that certain factory in 2012 scraps because of hardware component account for 63% of scrapping wafers sum then.
The main cause that hardware component is aging is initial failure problem, the inferior quality of such as parts, in the damage arrived before life span or aging etc.In the related, after large stroke causes wafer scrap, corresponding module is triggered to take measures to change parts.Adopt in this way by the time of at substantial, generally need weekly the time of more than ten hours, carry out a large amount of raw data of statistical quality system, take corresponding measure with monitor for faults rate hardware and prompting staff.
Visible, current people just change hardware when hardware arrives life span or produces a large amount of scrapping wafers; Manually added up the mode of the information of scrapping in existing quality engineering by a large amount of leading time, hardware initial failure problem cannot be detected.
For cannot detect in correlation technique hardware initial failure problem cause the problem of a large amount of wafer scrap, at present effective solution is not yet proposed.
Summary of the invention
The invention provides a kind of hardware Early Failure Detection method and apparatus, at least to solve the problem.
According to an aspect of the present invention, provide a kind of hardware Early Failure Detection method, comprising: the raw data obtaining wafer process lathe processed wafer; According to described raw data, add up the predetermined event information of described wafer process lathe, wherein, described predetermined event information comprises: the type of scheduled event and the frequency of occurrences of described scheduled event; According to described predetermined event information, determine the initial failure situation with the hardware corresponding to described type in described wafer process lathe.
Preferably, described scheduled event comprises: by the abnormality alarming event of described machining tool alarm module statistics, and/or, by the wafer scrap event of scrapping wafers integrated data status system statistics.
Preferably, according to described predetermined event information, determine to comprise with the initial failure situation of the hardware corresponding to described type in described wafer process lathe: judge whether the described frequency of occurrences exceeds predetermined threshold; When judged result is for exceeding predetermined threshold, determine that the hardware corresponding to described type is in initial failure state.
Preferably, according to described predetermined event information, determine to comprise with the initial failure situation of the hardware corresponding to described type in described wafer process lathe: described predetermined event information is sent to failure mode and effect analysis (FMEA) system; By described failure mode and effect analysis (FMEA) system, determine the initial failure situation with the hardware corresponding to described type in described wafer process lathe.
Preferably, by described failure mode and effect analysis (FMEA) system, determine to comprise with the initial failure situation of the hardware corresponding to described type in described wafer process lathe: described failure mode and effect analysis (FMEA) system judges whether the described frequency of occurrences exceeds the predetermined threshold arranged in described failure mode and effect analysis (FMEA) system; When judged result is for exceeding predetermined threshold, described failure mode and effect analysis (FMEA) system determines according to described type the hardware being in initial failure state.
Preferably, described method also comprises: change the hardware being in initial failure state.
According to another aspect of the present invention, additionally provide a kind of hardware Early Failure Detection device, comprising: acquisition module, for obtaining the raw data of wafer process lathe processed wafer; Statistical module, for according to described raw data, add up the predetermined event information of described wafer process lathe, wherein, described predetermined event information comprises: the type of scheduled event and the frequency of occurrences of described scheduled event; Determination module, for according to described predetermined event information, determines the initial failure situation with the hardware corresponding to described type in described wafer process lathe.
Preferably, described determination module comprises: judging unit, for judging whether the described frequency of occurrences exceeds predetermined threshold; Determining unit, for when judged result is for exceeding predetermined threshold, determines that the hardware corresponding to described type is in initial failure state.
Preferably, described determination module comprises: transmitting element, for described predetermined event information is sent to failure mode and effect analysis (FMEA) system; Second determining unit, for by described failure mode and effect analysis (FMEA) system, determines the initial failure situation with the hardware corresponding to described type in described wafer process lathe.
Preferably, described device also comprises: change module, for changing the hardware being in initial failure state.
By the present invention, adopt the raw data obtaining wafer process lathe processed wafer; According to raw data, the predetermined event information of statistics wafer process lathe, wherein, predetermined event information comprises: the type of scheduled event and the frequency of occurrences of scheduled event; According to predetermined event information, determine the mode with the initial failure situation of the hardware corresponding to type in wafer process lathe, solve in correlation technique cannot detect hardware initial failure problem cause the problem of a large amount of wafer scrap, provide a kind of method of detection hardware initial failure problem, reduce wafer scrap rate.
Accompanying drawing explanation
Accompanying drawing described herein is used to provide a further understanding of the present invention, and form a application's part, schematic description and description of the present invention, for explaining the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings:
Fig. 1 is the schematic flow sheet of the hardware Early Failure Detection method according to the embodiment of the present invention;
Fig. 2 is the structural representation of the hardware Early Failure Detection device according to the embodiment of the present invention;
Fig. 3 is the preferred structure schematic diagram one of the hardware Early Failure Detection device according to the embodiment of the present invention;
Fig. 4 is the preferred structure schematic diagram two of the hardware Early Failure Detection device according to the embodiment of the present invention;
Fig. 5 is the preferred structure schematic diagram three of the hardware Early Failure Detection device according to the embodiment of the present invention;
Fig. 6 is the schematic flow sheet detecting early stage hardware aging method according to the preferred embodiment of the invention;
Fig. 7 is the schematic diagram of initial failure deterministic process according to the preferred embodiment of the invention.
Embodiment
It should be noted that, when not conflicting, the embodiment in the application and the feature in embodiment can combine mutually.Below with reference to the accompanying drawings and describe the present invention in detail in conjunction with the embodiments.
Can perform in the computer system of such as one group of computer executable instructions in the step shown in the process flow diagram of accompanying drawing, and, although show logical order in flow charts, in some cases, can be different from the step shown or described by order execution herein.
Present embodiments provide a kind of hardware Early Failure Detection method, Fig. 1 is the schematic flow sheet of the hardware Early Failure Detection method according to the embodiment of the present invention, and as shown in Figure 1, this flow process comprises the steps:
Step S102, obtains the raw data of wafer process lathe processed wafer;
Step S104, according to raw data, the predetermined event information of statistics wafer process lathe, wherein, predetermined event information comprises: the type of scheduled event and the frequency of occurrences of scheduled event;
Step S106, according to predetermined event information, determines the initial failure situation with the hardware corresponding to type in wafer process lathe.
Pass through above-mentioned steps, by type and the frequency of occurrences of the scheduled event in statistics raw data, thus the initial failure situation of hardware corresponding with the type in wafer process lathe can be determined, solve in correlation technique cannot detect hardware initial failure problem cause the problem of a large amount of wafer scrap, provide a kind of method of detection hardware initial failure problem, reduce wafer scrap rate.
Preferably, above-mentioned scheduled event includes but not limited to: the abnormality alarming event of being added up by machining tool alarm module, and/or, by the wafer scrap event of scrapping wafers integrated data status system statistics.
Preferably, in step s 106, in order to determine initial failure situation, first can judge whether the frequency of occurrences exceeds predetermined threshold; When judged result is for exceeding predetermined threshold, determine that the hardware corresponding to corresponding type is in initial failure state.Wherein, predetermined threshold can be by early stage system operating experience statistics obtain and arrange.
Preferably, in step s 106, in order to determine initial failure situation, first predetermined event information can also be sent to failure mode and effect analysis (FMEA) system; By failure mode and effect analysis (FMEA) system, determine the initial failure situation with the hardware corresponding to type in wafer process lathe.Preferably, in failure mode and effect analysis (FMEA) system, be provided with the corresponding predetermined threshold of the operating experience statistics of system in early stage.
Preferably, failure mode and effect analysis (FMEA) system determination initial failure situation is adopted to adopt following manner: failure mode and effect analysis (FMEA) system judges whether the frequency of occurrences exceeds the predetermined threshold arranged in failure mode and effect analysis (FMEA) system; When judged result is for exceeding predetermined threshold, failure mode and effect analysis (FMEA) system determines according to corresponding type the hardware being in initial failure state.
Preferably, when defining hardware and being in initial failure state, the method also comprises: change the hardware being in initial failure state.
The present embodiment additionally provides a kind of hardware Early Failure Detection device, and this device is used for realizing above-mentioned hardware Early Failure Detection method, and the functional realiey of this device is illustrated in said method embodiment, does not repeat them here.
Fig. 2 is the structural representation of the hardware Early Failure Detection device according to the embodiment of the present invention, as shown in Figure 2, this device comprises: acquisition module 22, statistical module 24 and determination module 26, wherein, acquisition module 22, for obtaining the raw data of wafer process lathe processed wafer; Statistical module 24 is coupled to acquisition module 22, for according to raw data, and the predetermined event information of statistics wafer process lathe, wherein, predetermined event information comprises: the type of scheduled event and the frequency of occurrences of scheduled event; Determination module 26 is coupled to statistical module 24, for according to predetermined event information, determines the initial failure situation with the hardware corresponding to type in wafer process lathe.
Module involved in embodiments of the invention, unit can be realized by the mode of software, also can be realized by the mode of hardware.Described module in the present embodiment, unit also can be arranged within a processor, such as, can be described as: a kind of processor comprises acquisition module 22, statistical module 24 and determination module 26.Wherein, the title of these modules does not form the restriction to this module itself under certain conditions, and such as, acquisition module 22 can also be described to " for obtaining the module of the raw data of wafer process lathe processed wafer ".
Preferably, above-mentioned scheduled event includes but not limited to: the abnormality alarming event of being added up by machining tool alarm module, and/or, by the wafer scrap event of scrapping wafers integrated data status system statistics.
Fig. 3 is the preferred structure schematic diagram one of the hardware Early Failure Detection device according to the embodiment of the present invention, and as shown in Figure 3, preferably, determination module 26 comprises: judging unit 262, for judging whether the frequency of occurrences exceeds predetermined threshold; Determining unit 264 is coupled to judging unit 262, for when judged result is for exceeding predetermined threshold, determines that the hardware corresponding to type is in initial failure state.
Fig. 4 is the preferred structure schematic diagram two of the hardware Early Failure Detection device according to the embodiment of the present invention, and as shown in Figure 4, preferably, determination module 26 comprises: transmitting element 266, for predetermined event information is sent to failure mode and effect analysis (FMEA) system; Second determining unit 268 is coupled to transmitting element 266, for by failure mode and effect analysis (FMEA) system, determines the initial failure situation with the hardware corresponding to type in wafer process lathe.
Fig. 5 is the preferred structure schematic diagram three of the hardware Early Failure Detection device according to the embodiment of the present invention, and as shown in Figure 5, preferably, this device also comprises: change module 28 and be coupled to determination module 26, for changing the hardware being in initial failure state.
Be described below in conjunction with preferred embodiment and illustrate.
This preferred embodiment provides a kind of scheme detecting early stage hardware aging, to solve the just problem that causes of replacing hardware when hardware arrives life span or produce the wafer scrapped in a large number adopted in correlation technique.
Be different from hardware life span control program, Fig. 6 is the schematic flow sheet detecting early stage hardware aging method according to the preferred embodiment of the invention, as shown in Figure 6, in the preferred embodiment, preferably have employed following step:
Step 1, concentrates quality information relevant for all hardware in a database;
Step 2, database is by lathe/level/cause value (being equivalent to the type of event) programming count and the level (being equivalent to the frequency of occurrences) analyzing the appearance of lathe anomalous event;
Step 3, by results link to failure mode and effect analysis (FMEA) (Failure Mode and Effect Analysis, referred to as FMEA) system, to judge whether the level that anomalous event occurs is in normal level;
Step 4, if the level that anomalous event occurs is higher than FEMA definition value, then determines that hardware is that initial failure also can take corresponding measure to carry out the replacing of hardware.
Such as, Fig. 7 is the schematic diagram of initial failure deterministic process according to the preferred embodiment of the invention, as shown in Figure 7, the level that the event of etching region board 04 in Table 1 occurs reaches 1,000,000/19.44(and 19.44ppm), higher than the 10ppm set in FMEA system, according to the definition (table 2) of FMEA system, can determine it is radio frequency (Radio Frequency, referred to as RF) generator fault.
In figure 6, warning system (Alarm System) is for collecting warning information; Rejection system (Scrap System) is for collecting scrapping wafers information; IEMS system is used for collection system parameter; Database (Database, referred to as DB) carries out automatic analysis and statistics according to lathe/level/cause value; The level that event occurs can be determined by alarm rate, scrappage or other ratios.
In sum, by this preferred embodiment, propose a new design to detect hardware initial failure problem and to reduce wafer scrap.By the machine tooling alarm of this preferred embodiment, the automatic control of scrapping integrated data status system and the alarm of analysis hardware component, scrap information, and be linked to FMEA, the level occurred by anomalous event judges that the whether normal mode of the operation of hardware component monitors initial failure parts, instead of the existence event control mode in correlation technique.The exception of our early detection machining tool hardware can be helped by this preferred embodiment, avoid scrapping of a large amount of wafer.By the system that this is integrated, data analysis can also be made more effective, thus save a large amount of working times.
Obviously, those skilled in the art should be understood that, above-mentioned of the present invention each module or each step can realize with general calculation element, they can concentrate on single calculation element, or be distributed on network that multiple calculation element forms, alternatively, they can realize with the executable program code of calculation element, thus, they can be stored and be performed by calculation element in the storage device, or they are made into each integrated circuit modules respectively, or the multiple module in them or step are made into single integrated circuit module to realize.Like this, the present invention is not restricted to any specific hardware and software combination.
More than above are only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (10)
1. a hardware Early Failure Detection method, is characterized in that comprising:
Obtain the raw data of wafer process lathe processed wafer;
According to described raw data, add up the predetermined event information of described wafer process lathe, wherein, described predetermined event information comprises: the type of scheduled event and the frequency of occurrences of described scheduled event;
According to described predetermined event information, determine the initial failure situation with the hardware corresponding to described type in described wafer process lathe.
2. method according to claim 1, is characterized in that, described scheduled event comprises: by the abnormality alarming event of described machining tool alarm module statistics, and/or, by the wafer scrap event of scrapping wafers integrated data status system statistics.
3. method according to claim 1, is characterized in that, according to described predetermined event information, determines to comprise with the initial failure situation of the hardware corresponding to described type in described wafer process lathe:
Judge whether the described frequency of occurrences exceeds predetermined threshold;
When judged result is for exceeding predetermined threshold, determine that the hardware corresponding to described type is in initial failure state.
4. method according to claim 1, is characterized in that, according to described predetermined event information, determines to comprise with the initial failure situation of the hardware corresponding to described type in described wafer process lathe:
Described predetermined event information is sent to failure mode and effect analysis (FMEA) system;
By described failure mode and effect analysis (FMEA) system, determine the initial failure situation with the hardware corresponding to described type in described wafer process lathe.
5. method according to claim 4, is characterized in that, by described failure mode and effect analysis (FMEA) system, determines to comprise with the initial failure situation of the hardware corresponding to described type in described wafer process lathe:
Described failure mode and effect analysis (FMEA) system judges whether the described frequency of occurrences exceeds the predetermined threshold arranged in described failure mode and effect analysis (FMEA) system;
When judged result is for exceeding predetermined threshold, described failure mode and effect analysis (FMEA) system determines according to described type the hardware being in initial failure state.
6. the method according to claim 2 or 4, is characterized in that, described method also comprises:
Change the hardware being in initial failure state.
7. a hardware Early Failure Detection device, is characterized in that comprising:
Acquisition module, for obtaining the raw data of wafer process lathe processed wafer;
Statistical module, for according to described raw data, add up the predetermined event information of described wafer process lathe, wherein, described predetermined event information comprises: the type of scheduled event and the frequency of occurrences of described scheduled event;
Determination module, for according to described predetermined event information, determines the initial failure situation with the hardware corresponding to described type in described wafer process lathe.
8. device according to claim 7, is characterized in that, described determination module comprises:
Judging unit, for judging whether the described frequency of occurrences exceeds predetermined threshold;
Determining unit, for when judged result is for exceeding predetermined threshold, determines that the hardware corresponding to described type is in initial failure state.
9. device according to claim 7, is characterized in that, described determination module comprises:
Transmitting element, for being sent to failure mode and effect analysis (FMEA) system by described predetermined event information;
Second determining unit, for by described failure mode and effect analysis (FMEA) system, determines the initial failure situation with the hardware corresponding to described type in described wafer process lathe.
10. device according to claim 8 or claim 9, it is characterized in that, described device also comprises:
Change module, for changing the hardware being in initial failure state.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201410101114.5A CN104932428A (en) | 2014-03-18 | 2014-03-18 | Method and device for detecting early failure of hardware |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201410101114.5A CN104932428A (en) | 2014-03-18 | 2014-03-18 | Method and device for detecting early failure of hardware |
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| CN104932428A true CN104932428A (en) | 2015-09-23 |
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| CN201410101114.5A Pending CN104932428A (en) | 2014-03-18 | 2014-03-18 | Method and device for detecting early failure of hardware |
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| CN102270271A (en) * | 2011-05-03 | 2011-12-07 | 北京中瑞泰科技有限公司 | Equipment failure early warning and optimizing method and system based on similarity curve |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| US6615367B1 (en) * | 1999-10-28 | 2003-09-02 | General Electric Company | Method and apparatus for diagnosing difficult to diagnose faults in a complex system |
| CN1433535A (en) * | 2000-01-29 | 2003-07-30 | Abb研究有限公司 | Method for automatic fault tree synthesis |
| WO2006000110A1 (en) * | 2004-06-28 | 2006-01-05 | Abb Research Ltd | System and method for suppressing redundant alarms |
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Application publication date: 20150923 |