CN106600088A - System and method for enhancing production capacity - Google Patents
System and method for enhancing production capacity Download PDFInfo
- Publication number
- CN106600088A CN106600088A CN201510672882.0A CN201510672882A CN106600088A CN 106600088 A CN106600088 A CN 106600088A CN 201510672882 A CN201510672882 A CN 201510672882A CN 106600088 A CN106600088 A CN 106600088A
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- Prior art keywords
- board
- production capacity
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- failure
- inline
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
- G06Q10/06375—Prediction of business process outcome or impact based on a proposed change
Abstract
The invention provides a system and a method for enhancing production capacity. The system comprises an analysis model module and a production forecasting module, wherein the analysis model module is used for collecting historical failure data and inline data of a machine component, so as to establish a forecasting model for failures and the inline data of the machine component; and the production forecasting module is used for forecasting capacity level of a machine by means of the forecasting model, and arranging a priority order of the machine. The system can discover the failures of the machine component timely, thereby enhancing the capacity level and reducing the risk of failure. The method for enhancing the production capacity has the same advantages.
Description
Technical field
The present invention relates to semiconductor production field, produces energy for being lifted in particular to a kind of
The system of power and the method for lifting production capacity.
Background technology
Factory monitors the production capacity of factory with inline monitor (inline monitor) at present
(Cpk).But, when board component malfunction or performance are unstable, often result in production
Ability declines, or even the risk of (OOC/OOS) can be scrapped with large-tonnage product.
The unit failure (alarm) of board often affects its production capacity unstable, but, now
Production model be only, when production capacity is bad, Improving Measurements to be taken to board, so
Often not prompt enough and risk may expand.
It is current only bad in board production capacity or when scrapping, just Improving Measurements are taken for board,
Not prompt enough and risk may expand.Each factory is only for board prescription (recipe) at present
Parameter be predicted tune machine system (automatically process control, Automatic Process Control,
APC system) improving production capacity；But for the unstable or frequent failure of board part is caused
Production capacity declines, and does not but effectively prevent and improves system, often waits until that Cpk is bad,
Just it is the discovery that board part is unstable caused, it is late.
Accordingly, it is desirable to provide a kind of system for lifting production capacity and for lifting production
The method of ability, to solve issue noted above at least in part.
The content of the invention
For the deficiencies in the prior art, the present invention proposes a kind of system for lifting production capacity
With the method for lifting production capacity, which can find board unit failure and take to change in time
Kind measure, so as to lifting capacity level and reducing failure risk.
One embodiment of the present of invention provides a kind of system for lifting production capacity, the system
System includes：Analysis model module, for collecting the historical failure data and inline number of board part
According to set up the failure of the board part and the forecast model of the inline data；And it is raw
Prediction module is produced, the production capacity water of the board is predicted for by the forecast model
It is flat, and arrange the priority of the board.
Exemplarily, the analysis model module is additionally operable to set up Mishap Database inline with product
Monitoring data base, and define production website and corresponding inline monitor.
Exemplarily, the analysis model module be additionally operable to define the failure of the website board with
And resultant fault level, summation of the resultant fault level equal to each failure level.
Exemplarily, the analysis model module is additionally operable to obtain the resultant fault level and life
The forecast model of level of ability is produced, and by leader's majority correcting the model.
Exemplarily, the system also improves module including board, for bad to production capacity
Board improved.
Another embodiment of the present invention provides a kind of method for lifting production capacity, methods described bag
Include：Step S101：The historical failure data and inline data of board part are collected, to set up
The failure of the board part and the forecast model of the inline data；And step S102：
The capacity level of the board is predicted for by the forecast model, and arranges institute
State the priority of board.
Exemplarily, in step S101, Mishap Database and the inline prison of product are set up
Depending on data base, and define production website and corresponding inline monitor.
Exemplarily, in step S101, define the website board failure and
Resultant fault level, the resultant fault level are equal to the summation of each failure level.
Exemplarily, in step S101, the resultant fault level is obtained with production
The forecast model of level of ability, and by leader's majority correcting the model.
Exemplarily, also including step S103 after step S102：To production capacity
Bad board is improved.
The system for lifting production capacity of the present invention can find board unit failure in time
And Improving Measurements are taken, so as to lifting capacity level and reducing failure risk.This is used to carry
The method for rising production capacity equally has above-mentioned advantage.
Description of the drawings
The drawings below of the present invention is used to understand the present invention in this as the part of the present invention.It is attached
Embodiments of the invention and its description are shown in figure, for explaining the principle of the present invention.
In accompanying drawing：
Schematic diagrams of the Fig. 1 for the production critical stage stream of the embodiment of the present invention；
Schematic diagrams for lift the system of production capacity of the Fig. 2 for the embodiment of the present invention；
Schematic diagrams of the Fig. 3 for the forecast model of the embodiment of the present invention；
Schematic diagrams of the Fig. 4 for the gold path of the embodiment of the present invention；And
Schematic diagrams of the Fig. 5 for the board improvement of the embodiment of the present invention.
Specific embodiment
In the following description, a large amount of concrete details are given to provide to the present invention more
Thoroughly understand.It is, however, obvious to a person skilled in the art that of the invention
Can be carried out without the need for one or more of these details.In other examples, in order to keep away
Exempt to obscure with the present invention, for some technical characteristics well known in the art are not described.
It should be appreciated that the present invention can be implemented in different forms, and it is not construed as office
It is limited to embodiments presented herein.Disclosure will be made thoroughly and complete on the contrary, providing these embodiments
Entirely, and those skilled in the art be will fully convey the scope of the invention to.In the accompanying drawings,
In order to clear, the size and relative size in Ceng He areas may be exaggerated.It is identical attached from start to finish
Icon note represents identical element.
The purpose of term as used herein is only that description specific embodiment and not as this
Bright restriction.When here is used, " one " of singulative, " one " and " described/should "
It is also intended to include plural form, unless context is expressly noted that other mode.It is also to be understood that art
Language " composition " and/or " including ", when using in this specification, determine the feature,
The presence of integer, step, operation, element and/or part, but be not excluded for it is one or more its
The presence or addition of its feature, integer, step, operation, element, part and/or group.
When here is used, term "and/or" includes any and all combination of related Listed Items.
In order to thoroughly understand the present invention, detailed step and in detail will be proposed in following description
Thin structure, to explain technical scheme.Presently preferred embodiments of the present invention is retouched in detail
State it is as follows, but except these detailed description in addition to, the present invention can also have other embodiment.
One embodiment of the present of invention provide the present invention for the system that lifts production capacity.Should
System can find board unit failure in time and take Improving Measurements, so as to lift production capacity
Level simultaneously reduces failure risk.
Below, it is used to carry come the one kind for specifically describing embodiments of the invention referring to figs. 1 to Fig. 5
The system for rising production capacity.Wherein, Fig. 1 is the production critical stage stream of the embodiment of the present invention
Schematic diagram.Schematic diagrams for lift the system of production capacity of the Fig. 2 for the embodiment of the present invention.
Schematic diagrams of the Fig. 3 for the forecast model of the embodiment of the present invention.Huangs of the Fig. 4 for the embodiment of the present invention
The schematic diagram of golden path (golden path).Fig. 5 is the board improvement of the embodiment of the present invention
Schematic diagram.
One embodiment of the present of invention provides a kind of system for lifting production capacity, the system
System includes：Analysis model module, for collecting the historical failure data and inline number of board part
According to set up the failure of the board part and the forecast model of the inline data；And it is raw
Prediction module is produced, the production capacity water of the board is predicted for by the forecast model
It is flat, and arrange the priority of the board.Referring to Fig. 1, analysis model module carries out event
Barrier/inline monitor data is collected and is built with board unit failure/production capacity Relationship Prediction model
It is vertical, and production forecast module carries out capacity level and judges and production board priority peace
Row.
Exemplarily, the analysis model module is additionally operable to set up Mishap Database inline with product
Monitoring data base, and define production website and corresponding inline monitor.Exemplarily, divide
Analysis model module, sets up " Mishap Database " (device malfunction data base, Tool alarm of part
Database) with " product measures data base " (the inline monitoring data base of wafer, Wafer inline
Monitor database), and define crucial production website (for example, metal deposit, metal
Photograph, metal etch etc.) with corresponding inline monitor (metal THK, ADI CD, AEI CD
Deng).
Exemplarily, the analysis model module be additionally operable to define the failure of the website board with
And resultant fault level, summation of the resultant fault level equal to each failure level.It is exemplary
Ground, the critical failure of each website board of the analysis model module definition, and define " comprehensive event
Barrier level (ppm) "=" each critical failure ppm summation ".
Exemplarily, the analysis model module is additionally operable to obtain the resultant fault level and life
The forecast model of level of ability is produced, and by leader's majority (leading lots) to correct
State model.Exemplarily, analysis module analysis of history critical failure data and inline data, obtain
To the Relationship Prediction model of " resultant fault level " and corresponding " capacity level ", and
Carry out correction model with leader's majority is crossed.
Exemplarily, as shown in figure 3, analysis module is according to history board fault data and wafer
Data analysiss are defining board " resultant fault level (ppm) " and corresponding " production capacity
Level " relational model, and feed back to production dispatching system.Wherein, resultant fault level is
The summation of each part critical failure ppm of each board.Exemplarily, can also self-defining it is comprehensive
Close failure level.
Exemplarily, the production forecast module is defined on forecast model in dispatching system, assigns
After system receives the instant resultant fault level (ppm) of each board of Database Feedback, by model
To predict the capacity level of each board, and each website production board priority is arranged, allowed
Subsequent product first crosses the good board of production capacity, it is to avoid board part shakiness causes Cpk to decline.
Exemplarily, as shown in figure 4, according to instant " resultant fault level " data, dispatching system
Model prediction board capacity level, and each website production board priority is arranged, after allowing
Continuous product first crosses the good board of production capacity, improves production capacity with this.
Exemplarily, the system also improves module including board, for bad to production capacity
Board improved.The board improves module and requires board Improving Measurements in time.Exemplarily,
When occurring the bad board of production capacity when predicting the outcome, dispatching system feeds back the information of the board
To PM systems (appliance id, resultant fault level, the capacity level that may be affected etc.),
Carry out requirement by PM systems to shut down and corresponding board part Improving Measurements, it is to avoid risk expands,
Increase the quantity that board can be run in gold path.As shown in figure 5, by Improving Measurements, can be with
Avoid board risk from expanding, improve each board in time, increase the board number that gold path can be run
Amount.
The system for lifting production capacity of the present invention can find board unit failure in time
And Improving Measurements are taken, so as to lifting capacity level and reducing failure risk.
Next, the flow process of the lifting productivity of the embodiment of the present invention is illustrated with reference to Fig. 2.
As shown in Fig. 2 methods described includes：Step S101：Collect the history of board part
Fault data and inline data, to set up the failure of the board part and the inline data
Forecast model (correspondence 1 to 4)；And step S102：For by the forecast model come
The capacity level of the board is predicted, and arranges the priority (correspondence of the board
5)。
Exemplarily, in step S101, Mishap Database and the inline prison of product are set up
Depending on data base, and define production website and corresponding inline monitor (corresponding 1).
Exemplarily, in step S101, define the website board failure and
Resultant fault level, the resultant fault level are equal to the summation (correspondence 2) of each failure level.
Exemplarily, in step S101, the resultant fault level is obtained with production
The forecast model of level of ability, and by leader's majority come correct the model (correspondence 3 to
4)。
Exemplarily, also including step S103 after step S102：To production capacity
Bad board is improved (correspondence 6 to 7).
The method for lifting production capacity of the present invention can find board unit failure in time
And Improving Measurements are taken, so as to lifting capacity level and reducing failure risk.
The modules of the embodiment of the present invention can be realized with hardware, or with one or many
The software module run on individual processor is realized, or is realized with combinations thereof.This area
It will be appreciated by the skilled person that microprocessor or digital signal processor can be used in practice
(DSP) realizing some in the system for lifting the productivity according to embodiments of the present invention
Or some or all functions of whole parts.The present invention is also implemented as performing this
In described method some or all equipment or program of device (for example, calculate
Machine program and computer program).Such program for realizing the present invention can be stored in meter
On calculation machine computer-readable recording medium, or there can be the form of one or more signal.Such letter
Number can download from internet website and to obtain, or provide on memory carrier, or to appoint
What other forms is provided.
The present invention is illustrated by above-described embodiment, but it is to be understood that, it is above-mentioned
Embodiment is only intended to citing and descriptive purpose, and is not intended to limit the invention to described
Scope of embodiments in.In addition it will be appreciated by persons skilled in the art that the present invention not office
It is limited to above-described embodiment, teaching of the invention can also be made more kinds of modifications and repair
Change, within these variants and modifications all fall within scope of the present invention.The present invention's
Protection domain is defined by the appended claims and its equivalent scope.
Claims (10)
1. a kind of system for lifting production capacity, it is characterised in that the system includes：
Analysis model module, for collecting the historical failure data and inline data of board part,
To set up the failure of the board part and the forecast model of the inline data；And
Production forecast module, predicts the production energy of the board for by the forecast model
Power level, and arrange the priority of the board.
2. the system for lifting production capacity is used for as claimed in claim 1, it is characterised in that
The analysis model module is additionally operable to set up Mishap Database and the inline monitoring data base of product, and
And define production website and corresponding inline monitor.
3. the system for lifting production capacity is used for as claimed in claim 1, it is characterised in that
The analysis model module is additionally operable to the failure and resultant fault water for defining the website board
Flat, the resultant fault level is equal to the summation of each failure level.
4. the system for lifting production capacity as claimed in claim 3, it is characterised in that institute
State analysis model module and be additionally operable to obtain the resultant fault level pre- with capacity level
Model is surveyed, and by leader's majority correcting the model.
5. the system of the lifting production capacity as any one of Claims 1-4, its
It is characterised by, the system also improves module including board, for the machine bad to production capacity
Platform is improved.
6. a kind of method for lifting production capacity, it is characterised in that methods described includes：
Step S101：The historical failure data and inline data of board part are collected, to set up
The failure of the board part and the forecast model of the inline data；And
Step S102：The production capacity of the board is predicted for by the forecast model
Level, and arrange the priority of the board.
7. the method for being used for as claimed in claim 6 lifting production capacity, it is characterised in that
In step S101, Mishap Database and the inline monitoring data base of product are set up, and
Definition production website and corresponding inline monitor.
8. the method for being used for as claimed in claim 6 lifting production capacity, it is characterised in that
In step S101, the failure and resultant fault level of the website board are defined,
The resultant fault level is equal to the summation of each failure level.
9. the method for being used for as claimed in claim 8 lifting production capacity, it is characterised in that
In step S101, the prediction of the resultant fault level and capacity level is obtained
Model, and by leader's majority correcting the model.
10. as any one of claim 6 to 9 for the method that lifts production capacity,
Characterized in that, also including step S103 after step S102：To production capacity not
Good board is improved.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510672882.0A CN106600088A (en) | 2015-10-16 | 2015-10-16 | System and method for enhancing production capacity |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510672882.0A CN106600088A (en) | 2015-10-16 | 2015-10-16 | System and method for enhancing production capacity |
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| Publication Number | Publication Date |
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| CN106600088A true CN106600088A (en) | 2017-04-26 |
Family
ID=58553750
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510672882.0A Pending CN106600088A (en) | 2015-10-16 | 2015-10-16 | System and method for enhancing production capacity |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110378503A (en) * | 2018-11-21 | 2019-10-25 | 天津京东深拓机器人科技有限公司 | The method and apparatus for predicting multilayer shuttle shelf production capacity |
| CN111891687A (en) * | 2020-07-29 | 2020-11-06 | 惠科股份有限公司 | Cargo carrying method and system |
| CN114742332A (en) * | 2022-06-13 | 2022-07-12 | 合肥新晶集成电路有限公司 | Productivity analysis method and productivity analysis system |
| CN116862299A (en) * | 2023-07-05 | 2023-10-10 | 杭州意博科技有限公司 | Data processing system and data processing method for intelligent factory |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102193836A (en) * | 2011-04-18 | 2011-09-21 | 电子科技大学 | Dynamic preventative maintenance method for electromechanical equipment |
| CN104636826A (en) * | 2015-01-27 | 2015-05-20 | 中国石油化工股份有限公司 | Method for optimizing reliability and maintenance strategy of chemical refining equipment |
-
2015
- 2015-10-16 CN CN201510672882.0A patent/CN106600088A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102193836A (en) * | 2011-04-18 | 2011-09-21 | 电子科技大学 | Dynamic preventative maintenance method for electromechanical equipment |
| CN104636826A (en) * | 2015-01-27 | 2015-05-20 | 中国石油化工股份有限公司 | Method for optimizing reliability and maintenance strategy of chemical refining equipment |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110378503A (en) * | 2018-11-21 | 2019-10-25 | 天津京东深拓机器人科技有限公司 | The method and apparatus for predicting multilayer shuttle shelf production capacity |
| CN110378503B (en) * | 2018-11-21 | 2022-06-07 | 北京京东乾石科技有限公司 | Method and device for predicting production capacity of multi-layer shuttle shelf |
| CN111891687A (en) * | 2020-07-29 | 2020-11-06 | 惠科股份有限公司 | Cargo carrying method and system |
| CN111891687B (en) * | 2020-07-29 | 2021-09-10 | 惠科股份有限公司 | Cargo carrying method and system |
| CN114742332A (en) * | 2022-06-13 | 2022-07-12 | 合肥新晶集成电路有限公司 | Productivity analysis method and productivity analysis system |
| CN114742332B (en) * | 2022-06-13 | 2022-09-13 | 合肥新晶集成电路有限公司 | Productivity analysis method and productivity analysis system |
| CN116862299A (en) * | 2023-07-05 | 2023-10-10 | 杭州意博科技有限公司 | Data processing system and data processing method for intelligent factory |
| CN116862299B (en) * | 2023-07-05 | 2024-02-23 | 杭州意博科技有限公司 | Data processing system and data processing method for intelligent factory |
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