DE10203997A1 - Method of production data detection in production plant especially semiconductor chip production plant, involves determining and storing part production data from part production plants - Google Patents

Abstract

A method for detecting production data in a production plant, in which part production data is determined and stored by the part production plants, and via at least one grouping table for allocating the part production data to groups of the grouping table then the part production data are displayed. In the grouping table, machines of the part production plants are grouped to at least one machine group or machine units/components of the part production plants are grouped to at least one machine component group or manufacturing formulations are grouped to at least one formulation group or manufacturing parameters are grouped to at least one parameter group. An Independent claim is given for a system for detecting production data in a production plant.

Description

The invention relates to a method and a system for Acquisition of production data in a production plant, especially in a chip production plant.

In the manufacture of highly integrated semiconductor chips are particularly affected by the ever increasing Miniaturization of the structures on the semiconductor chip always higher requirements for the production of Manufacturing equipment and semiconductor chips used Manufacturing processes occur. The stability and Reproducibility of both the manufacturing plants and the Manufacturing processes significantly influence the yield and Productivity in the context of semiconductor chip production. Nice small deviations from a target behavior of a chip Manufacturing facility as part of the production can become one significant deterioration in yield, that is, to a considerable increase in the error rate in the manufactured Lead semiconductor chips.

Thus, an essential aspect in the manufacture of Semiconductor chips, possible deviations from a target Behavior in a chip manufacturing plant or in the frame to recognize a manufacturing process very early on and take appropriate countermeasures. With that comes the Analysis and monitoring of machines, especially the Chip manufacturing facilities as well as the manufacturing processes very high economic importance. Furthermore, the Analysis and monitoring of many process steps of the Manufacturing process of significant importance because usually rarely a repair of a Intermediate after performing a process step is possible. As a rule, a functional test is one semiconductor chips produced only at the very end of Manufacturing process provided, leading to a very late Feedback of the determined results in the Manufacturing process leads.

It is also known to use inline measurements of process Intermediate results, for example the layer thicknesses of the Sheet resistance or line widths, etc. by means of so-called statistical process control (SPC). However, this leads to additional measuring steps within the scope of the entire manufacturing process and is thus time and costly.

As part of the so-called Advanced Process Control (APC) data from internal and external sensors of the Production systems in combination with the measurement technology used including in-line measured data on intermediate products, or also results of measurements on test structures after the Wafer has been fully processed, results from Function tests on the semiconductor chips, the yield faultless semiconductor chips, etc., analyzed. To this Way, both the stability of the manufacturing equipment and also the process stability and in this way also the Manufacturing productivity and product quality manufactured semiconductor chips are significantly increased.

Despite these significant advantages, the use automated data acquisition and data analysis, that is the use of, for example, APC processes the APC processes in semiconductor chip production so far only used very occasionally. This is particularly due to the large variety of different manufacturing plants and different processes in the manufacture of Semiconductor chips attributed and the associated considerable number of in different data formats recorded raw data and the significant differences the raw data due to different manufacturing facilities, Sensors and software versions of the control program of the Manufacturing plants, which the manufacturing plants or the Manufacturing processes in the context of chip production characterize.

Would be part of an automated data analysis for at least part of the recorded and monitored Sensor parameters of a manufacturing plant or one Manufacturing process an individual monitoring by means of an individual specification limit to monitor the Data used, so the number would increase monitoring parameters and the parameters to be set Monitoring algorithms multiply from the number of recorded sensor parameters, the number of within the Semiconductor chip manufacturing equipment used, the different products to be manufactured, i.e. the different semiconductor chips and the one for manufacturing used manufacturing recipes or even the individual Recipe steps result.

This shows the significant number to be analyzed and added monitoring parameters, which in practice no longer apply to cope with.

Nor will it be the case with such individual monitoring more possible, influences from individual Specification parameters to other parameters consider. So that's an analysis across several Across machines is no longer possible, in other words machine comparison no longer possible. In particular, it can no correlations between parameters of the same Process, correlations between parameters of various processes, for example a preliminary process and be determined in a post-process.

Furthermore, it is known for individual by each Sensor determined sensor sizes, i.e. the respective Raw data parameters to calculate key figures. this happens usually by means of one configuration per monitored in APC-integrated machine and per recipe used or Recipe step in the making of a Semiconductor chips.

When analyzing the parameters and monitoring the Characteristics associated with the characteristics Specification limits may have to be added according to the respective different manufactured products or Product types can be distinguished.

This means a very high configuration effort and Maintenance effort, d. H. Maintenance effort, the respective analysis, Monitoring and control tools.

For this reason, APC procedures have so far been very limited isolated at individual positions within the scope of the Manufacturing process of semiconductor chips and only in used to a very limited extent.

A systematic comparison between different ones Machines used as part of a manufacturing process, between recipes or between different ones Products or product types,. , ., is hardly in this way or not possible at all.

There is also a standardized so-called SECS interface (Semiconductor equipment communication standard Interface).

The invention is based on the problem of production data in a production plant, especially in a chip Production plant up against the state of the art Simplified and less expensive way to capture and To provide analysis.

The problem is solved by the procedure and the system Acquisition of production data in a production plant, especially in a chip production plant with which Features solved according to the independent claims.

In a method of collecting production data in a production plant with several partial production plants The partial production data becomes part production data determined and saved. Using at least one Grouping tables are assigned with the assignment of Production data for groups in the grouping table Production data mapped on compressed partial Production data. There are machines in the grouping table of the partial production plants to at least one Machine group or machine components of the part Production facilities for at least one Machine component group grouped. Alternatives are Manufacturing recipes, especially chip manufacturing recipes, for the manufacture of a product or an intermediate grouped at least one recipe group or Manufacturing parameters, especially chip Manufacturing parameters, as part of the manufacture of a Product or an intermediate to at least one Parameter group.

• - Maschinen der Teil-Produktionsanlage zu mindestens einer Maschinengruppe gruppiert, oder
• - Maschinenkomponenten der Teil-Produktionsanlagen zu mindestens einer Maschinenkomponentengruppe gruppiert, oder
• - Herstellungsrezepte, insbesondere Chip- Herstellungsrezepte, zur Herstellung eines Produkts oder eines Zwischenprodukts zu mindestens einer Herstellungsrezeptgruppe gruppiert, oder
• - Herstellungsparameter, insbesondere Chip- Herstellungsparameter, im Rahmen der Herstellung eines Produkts oder eines Zwischenprodukts zu mindestens einer Herstellungsparametergruppe gruppiert.

A system for capturing production data in a production plant has a plurality of sub-production plants, the sub-production plants generating or being able to produce partial production data. Furthermore, at least one memory is provided for storing the partial production data generated and an evaluation computer coupled to the memory, which is set up in such a way that the partial production data can be mapped to compressed using at least one grouping table with assignment of the partial production data to groups of the grouping table part-production data. In the grouping table are

• - Machines of the sub-production plant grouped into at least one machine group, or
• - Machine components of the sub-production systems grouped into at least one machine component group, or
• - Manufacturing recipes, in particular chip manufacturing recipes, grouped into at least one manufacturing recipe group for manufacturing a product or an intermediate product, or
• - Manufacturing parameters, in particular chip manufacturing parameters, grouped into at least one manufacturing parameter group in the course of manufacturing a product or an intermediate product.

In this context, under a production facility is a To understand system or an arrangement in which under Using different raw materials a product or an intermediate product is produced. It is in this Context to note that the invention is all the more efficient can be used, the more complex the manufacturing process is built when at least some of them are similar Machines, processes, recipes, or parameters used which, however, due to slightly different used nomenclature or different structure or different software version of each control program used is not readily within the scope a data acquisition are recorded and processed together can.

The invention is particularly useful in the context of semiconductor Manufacturing, d. H. for example in the production of monocrystalline or polycrystalline silicon or one other semiconductor material, or also the semiconductor chip Manufacturing, d. H. as part of the production of semiconductor chips in a chip production plant, can be used advantageously because especially in such processes the above Criteria are very well met. However, it is in this Context that the invention in any Production process can be used advantageously, in particular if many process steps are necessary and of the Production facilities automatically provide information about the Production process can be made available.

Under this is a chip production line to understand a system or an arrangement in which under Use of different raw materials, for example using semiconductor materials such as silicon or also other IV main group semiconductor materials (for example germanium) or binary, ternary or also quaternary III-V compound semiconductor materials (e.g. indium gallium arsenide phosphide, indium Gallium arsenide antimonide, etc.), or binary, ternary or also quaternary II-VI compound semiconductor materials Semiconductor components, in particular semiconductor chips are manufactured.

Under a semiconductor chip is within the scope of this description for example a memory chip, a microprocessor chip, a communication chip, a chip with an integrated Semiconductor laser element to understand as well as one on one any predefinable hardware function optimized chip like for example a communication chip for decoding received radio signals or a chip for processing of video signals.

According to the invention, the chip production system has several Part production facilities, for example different Machines that are used for the entire manufacturing process of a chip necessary physical or chemical Process steps can be carried out.

• - eine Kurzzeittemper-Vorrichtung (Rapid Thermal Processing-Vorrichtung, RTP-Vorrichtung),
• - ein Ofen zum Erhitzen der zu bearbeitenden Wafer,
• - eine Ätzvorrichtung, beispielsweise eine Plasmaätz- Vorrichtung, oder eine Trockenätz-Vorrichtung,
• - eine Lithographie-Vorrichtung,
• - eine Nassbehandlungs-Vorrichtung zum Ätzen, Lackentfernen, Reinigen oder Verändern der Produkt- Oberfläche,
• - eine CMP-Vorrichtung, d. h. eine Vorrichtung zum Durchführen chemisch-mechanischen Polierens,
• - eine Ionen-Implantations-Vorrichtung,
• - eine Abscheide-Vorrichtung zum Abscheiden von Schichten auf den Wafer, beispielsweise eine Abscheide-Vorrichtung zum physikalischen Abscheiden aus der Gasphase (Physical Vapour Deposition, PVD) oder zum chemischen Abscheiden aus der Gasphase (Chemical Vapour Deposition, CVD),
• - eine Messvorrichtung zum Messen vorgegebener Waferparameter oder Prozessparameter,
• - eine Test-Vorrichtung zum Testen hergestellter Wafer.

One example, particularly in the front-end area of chip production, is devices for carrying out the following process steps:

• a short-term tempering device (Rapid Thermal Processing device, RTP device),
• an oven for heating the wafers to be processed,
• an etching device, for example a plasma etching device, or a dry etching device,
• a lithography device,
• a wet treatment device for etching, removing paint, cleaning or changing the product surface,
• a CMP device, ie a device for performing chemical mechanical polishing,
• an ion implantation device,
• a deposition device for depositing layers on the wafer, for example a deposition device for physical deposition from the gas phase (physical vapor deposition, PVD) or for chemical deposition from the gas phase (chemical vapor deposition, CVD),
• a measuring device for measuring predetermined wafer parameters or process parameters,
• - A test device for testing manufactured wafers.

Depending on the product to be manufactured, for example depending on the desired design of the chip to be manufactured, is a variety of different devices, that is Part production plants in the chip production plant provided and coupled with each other to implement the respective necessary total semiconductor chip Manufacturing process.

In this context it should be noted that the process of individual process steps in the respective sub- Production facilities either "sequentially", i.e. H. always first in a first system group A (e.g. coating) before the second Plant group B (e.g. exposure) can be carried out for two manufacturing steps that take place one after the other should, or "parallel", d. H. in a first system B1 (e.g. Scanner type XY100) or a second system B2 (e.g. stepper Type Extra2000) for two different systems and processes that alternatively carry out one and the same manufacturing step can.

The machines can depend on their respective Properties related to machine groups with machines sufficiently similar to a similarity criterion Properties are grouped. This corresponds vividly the parallel flow of the respective process steps in different machines.

Chemical separation machines from the Gas phase as well as all other respective machines can be in different machine types can be classified. So points for example a CVD machine usually, but not necessarily, a so-called mainframe, that is, one Robot or robotic arm and one the robot or robotic arm assigned robot controller for distribution and control of the respective wafers on the individual process chambers of the CVD Machine and at least one process chamber for Processing of the respective wafers according to the in the Process chamber set procedures. In the event that no mainframe is provided, only the individual ones Process chambers specific to the process area.

• - einem Mainframe und vier Prozesskammern,
• - einem Mainframe und zwei Prozesskammern, sowie
• - nur einer Prozesskammer und keinem Mainframe.

Such a CVD machine can therefore be of a different machine type, for example a CVD machine can be differentiated into machines with:

• - a mainframe and four process chambers,
• - a mainframe and two process chambers, as well
• - only one process chamber and no mainframe.

In general, however, depending on the requirements basically any number of process chambers or other machine components one machine type each Form machine, especially a CVD machine.

A machine thus has different ones Machine components, for example the mainframe or a process chamber. Is under a process chamber for example a deposition chamber in which using gases supplied to the separation chamber Materials or layers on the wafer to be processed to be deposited to understand. Under a process chamber is also to be understood as an etching chamber in which a wafer supplied to the etching chamber using one of the Etching chamber also supplied gas or plasma or one supplied liquid structured, that is, is etched. A process chamber can also be set up in such a way that in their material epitaxially on the respective surface of the to be processed wafers.

The individual machine components can in turn be of different types, hereinafter referred to as respective Machine component type can be designated.

The machine component types usually depend on that Manufacturer of the machine component starting from a respective Provides machine component.

Part production data of each part production plant determined, usually using the respective Sensors assigned to machines or machine components, and as partial production data in one or more stored electronic files. So the partial Production data in one machine or one File clearly assigned to the machine component in particular using the SECS standards (Semiconductor equipment communication standard).

The saved partial production data are now under Use of the grouping table on compressed partial Production data mapped, the grouping of respective machines, machine components, Manufacturing processes or chip manufacturing parameters below Taking into account their respective properties and the Similarity of their respective properties to others Machines, machine components, chip manufacturing recipes or chip manufacturing parameters.

By exploiting the respective similarities of the individual Elements to each other will add a significant reduction partial production data taken into account, whereby for the first time a volume of data to be taken into account is reached, which with common personal computers, that is with usual monitoring tools, analysis tools, and Control tools analyzed, monitored and thus also can be controlled. Furthermore, according to the invention intelligent grouping of the individual elements provided which improves the statistics and a Comparability of the partial Ensures production data.

This is the first time a practicable and inexpensive, comprehensive and cross-divisional opportunity for automated data analysis and process monitoring and control, that is to say for Advanced Process Control (APC) in Framework of semiconductor chip manufacturing enabled.

Preferred developments of the invention result from the dependent claims. The further refinements of the Invention relate to both the method and the system for capturing production data in a chip Production plant.

The partial production data are according to one embodiment of the invention from part production plants to one central memory and there in at least one central file, preferably several Files for storing the partial production data are provided are, which are in directories, which are each a machine or process chamber, generally a part production plant, are assigned, saved.

In this way it becomes a centralized and therefore easy to use monitoring, easily configurable and therefore inexpensive maintainable way to semiconductor chip manufacturing process Surveillance created.

The machines can also be grouped into machine groups which are each related to a machine Similarity criterion sufficiently similar Have machine properties.

The machine components can also Machine component groups are grouped, which each with regard to a machine component Similarity criterion sufficiently similar Have machine component properties.

Furthermore, those semiconductor chip manufacturing recipes can be grouped into recipe groups, each of which regarding a semiconductor chip manufacturing recipe Similarity criterion sufficiently similar recipes exhibit.

Furthermore, those chip manufacturing parameters can be too Parameter groups are grouped, which with regard to a Chip manufacturing parameter similarity criterion sufficient have similar chip manufacturing parameters.

The groupings can alternatively or together in different or in a common Grouping table done. In the more areas one Grouping is provided, the greater the achievable Degree of compression of the amount of data to be considered.

The design of the similarity criteria depends on the respective facility or the respective parameters or recipes that are in the (chip) production plant be used.

In other words, it means that both the definition the similarity criteria as well as the grouping of the respective components to groups can vary widely and very process dependent, product dependent and also are machine dependent or machine component dependent.

According to a further embodiment, the Invention the compressed part production data of a subsequent, preferably statistical, data analysis undergo, which further improves and more precise monitoring of the entire manufacturing process and the one involved in the manufacturing process Manufacturing facilities is achieved.

The invention can be clearly seen in that in Framework of APC an approach to analysis and Monitoring of plant data and process data is provided, in which different machines and processes can be recorded together. With the help of only a few optimally formed grouping tables, which also as assignment tables or mapping tables are designated, it is possible according to the invention within a corresponding order hierarchy step by step irrelevant differences between the individual machines, machine groups, recipes or Compensate recipe parameters and similar elements summarize. A similar configuration under the APC is therefore no longer found, as in the prior art usual, per machine, machine components, recipe or Recipe step instead, but only per machine group, Machine component group, recipe group or Recipe parameter group.

In particular, this also has the considerable advantage of only minimal configuration effort and Maintenance expenditure of the monitoring device and monitoring programs used.

The raw data material thus becomes very effective Way common metrics generated that very high Information content about the properties and behavior of the respective machines and all manufacturing processes exhibit. According to the invention, therefore, is also a Long-term comparison of data from a small subset of Part production equipment with the data of the whole Group of part production equipment possible, what a quasi-continuous monitoring, despite discontinuous data the respective sub-group of the sub-production facilities allows.

This made it possible for the first time to use an automated one Process monitoring, that means APC nationwide and used profitably in semiconductor chip production. Even within a larger group of not mandatory Identical manufacturing systems can be used for a large number manufacturing processes used relevant information such as Differences also between machines / machine components a machine group, offsets, drifts, trends, outliers etc. are detected and analyzed.

In summary, the invention can thus also be seen therein be that the temporal signal curve of a sensor in Key figures, which the respective signal course and the Characterize the machine or the process, compressed can be displayed.

These key figures are configured together for a large number of different systems and processes Help from optimized, preferably hierarchical, organized Assignment tables, the grouping tables.

Even if the invention is based on the example of a Chip production line is explained in more detail on it to point out that the invention is not limited to but in all production plants with Production facilities can be used, for example also in the pharmaceutical industry in the manufacture of pharmaceutical products.

An embodiment of the invention is in the figures shown and will be explained in more detail below.

Show it

Fig. 1 is a block diagram showing the general organization of a chip production plant;

Fig. 2 is a sketch of the path of a wafer / lot represented by the chip production installation of a chip manufacturing facility according to an embodiment of the invention, wherein the complex material flow ie;

Fig. 3 is a block diagram in which the data flow is shown in the embodiment of the invention;

FIG. 4 shows a block diagram illustrating the acquisition, transmission and storage of the raw data acquired by the sensors;

Figure 5 is an extract of a log file of a machine with raw data log file which has been generated by a sensor.

Fig. 6 is a section of a file according to the PDSF format in which the logistic information is stored;

Fig. 7 shows a further file according to the PDSF format, in which the sensor parameters are stored per unit time;

Fig. 8 is a diagram of a machine with a mainframe and four process chambers;

Figs. 9a to 9c diagrams of three different types of CVD equipment, which are grouped into groups of machines according to an embodiment of the invention, wherein a first type of machine a mainframe and four process chambers (Fig. 9a), a second type of machine a mainframe and two process chambers (Figure . 9b), and a third type of machine, comprising a process chamber (9c) wherein the machine of the clustered machine to a group of types of machines are jointly configured and interrogated.

FIG. 10 is a block diagram outlined in the different grouping options;

FIG. 11 is an illustration of a grouping table are grouped into a plurality of machines to component types;

FIG. 12a-12g block diagrams showing the embodiment, the recording raw data are shown for the individual machines, that is, partial production, according to;

FIG. 13 is a table in which the allocation of the parameter sets is shown as part of the raw data record;

Fig. 14 is a table in which the parameter configuration for engines of a type of machine is shown with different mainframes;

Fig. 15 is a table, in the illustrated configuration, the parameters for all in this embodiment, deposition process chambers is shown;

Fig. 16 is a table in which the parameter configuration for all in this embodiment illustrated etch-back process chambers is shown;

FIG. 17 is a block diagram and tables in which all the machines in this group recipes used in the context of a manufacturing process of a semiconductor chip manufacturing are shown according to this embodiment;

Are in the individual Recipe groups, also referred to as a recipe associated sets 18 is a table.

Fig. 19 is a table in which the configurations of the recipe deposition process chambers is shown the machine group;

Fig. 20 is a table in which the recipe configurations of the etch-back process chambers is shown the machine group;

, Are associated with component types, as well as parameter sets recipe sets different ratios sets in the individual machine 21 is a table.

FIG. 22 is a grouping table in which the key figures configuration for a mainframe, according to this embodiment, for the mainframe Centura and P5000 shown;

Fig. 23 is a table in which the ratios configuration for the deposition process chambers is shown and

Fig. 24 is a table in which the ratios configuration for the etch-back process chambers is illustrated.

Furthermore, the figures show the same elements identical reference numerals are used.

Fig. 1 shows the organization and structure of a semiconductor chip production installation according to an embodiment of the invention in a block diagram 100.

• - einen ersten Bereich, in den die Front-End-Prozesse der Chip-Fertigung gruppiert werden (Block 102),
• - einen zweiten Bereich des Herstellungsprozesses, in den die Back-End-Prozesse gruppiert werden (Block 103),
• - einen dritten Bereich des Herstellungsprozesses, der den Support betrifft, das heißt die Unterstützung der einzelnen Herstellungsprozesse (Block 104),
• - ein vierter Bereich der die Prozesstechnologie und die Prozessintegration betrifft (Block 105).

The entire manufacturing process, designated by a first block 101 in FIG. 1, is grouped into four production areas 102 , 103 , 104 , 105 in accordance with this exemplary embodiment,

• a first area in which the front-end processes of chip production are grouped (block 102 ),
• a second area of the manufacturing process in which the back-end processes are grouped (block 103 ),
• a third area of the manufacturing process that relates to support, that is, the support of the individual manufacturing processes (block 104 ),
• - A fourth area that relates to process technology and process integration (block 105 ).

• - Ein Ofen zum Erhitzen des jeweiligen zu prozessierenden Wafers,
• - eine Vorrichtung zum Durchführen eines Kurzzeit- Temperverfahrens (Rapid Thermal Processing, RTP),
• - eine Vorrichtung zum Ätzen des Wafers, beispielsweise zum Nassätzen oder zum Trockenätzen,
• - eine Vorrichtung zum Reinigen, beispielsweise Waschen des Wafers,
• - eine Vorrichtung zur Durchführung unterschiedlicher Lithographieschritte,
• - einer Vorrichtung zum chemisch-mechanischen Polieren (Chemical Mechanical Polishing, CMP),
• - eine Einrichtung zur Durchführung einer Ionen- Implantation in vorgegebenen Bereichen des Wafers bzw. des jeweils zu fertigenden Chips,
• - Vorrichtungen zum Aufbringen von Materialien auf dem Wafer, beispielsweise Vorrichtungen zum Abscheiden von Materialien aus der Gasphase, das heißt beispielsweise Vorrichtungen zum Durchführen von Physical Vapour Deposition (PVD) oder Chemical Vapour Deposition (CDV), oder eine Vorrichtung zum epitaktischen Aufwachsen von Material auf einem Substrat,
• - Metrologie-Vorrichtungen, d. h. Messvorrichtungen,
• - Vorrichtungen zum Durchführen von Tests auf den jeweiligen Wafern.

The following process technologies and the devices set up to carry out the corresponding processes are provided in particular for the front-end processes 102 :

• An oven for heating the respective wafer to be processed,
• a device for carrying out a short-term annealing process (Rapid Thermal Processing, RTP),
• a device for etching the wafer, for example for wet etching or for dry etching,
• a device for cleaning, for example washing the wafer,
• a device for carrying out different lithography steps,
• a device for chemical mechanical polishing (CMP),
• a device for carrying out an ion implantation in predetermined areas of the wafer or of the chip to be manufactured in each case,
• - Devices for applying materials to the wafer, for example devices for separating materials from the gas phase, that is to say for example devices for carrying out physical vapor deposition (PVD) or chemical vapor deposition (CDV), or a device for epitaxially growing material a substrate,
• - metrology devices, ie measuring devices,
• - Devices for performing tests on the respective wafers.

• - Den Zusammenbau der Chips in Gehäuse,
• - den Endtest des gefertigten und gehäusten Chips,
• - das Einbringen von Informationen, beispielsweise Produktinformation, in oder an das Gehäuse des jeweiligen Chips, sowie
• - allgemein die im Bereich des Back-Ends für gehäuste und ungehäuste Chip eingesetzten Technologien.

The back-end processes particularly affect the following areas:

• - The assembly of the chips in a housing,
• - the final test of the manufactured and packaged chips,
• the introduction of information, for example product information, into or onto the housing of the respective chip, and
• - generally the technologies used in the area of the back-end for packaged and unpackaged chips.

• - CIM,
• - Prozessüberwachung,
• - ein Transportsystem zur Auslieferung der gefertigten Halbleiterchips,
• - eine Koordination der Produktion,
• - die Unterstützung der jeweiligen Fertigungsstandorte.

Support, i.e. process support, particularly affects the following areas:

• - CIM,
• - process monitoring,
• a transport system for delivery of the manufactured semiconductor chips,
• - coordination of production,
• - the support of the respective production locations.

• - die Prozessintegration von Logikbausteinen,
• - die Prozessintegration von Speicherbausteinen,
• - das Produkt-Engineering,
• - das Überwachen und Verbessern von Fehlerdichten bei der Herstellung,
• - das Überwachen elektrischer Parameter bei den hergestellten Produkten,
• - die Verbesserung der Ausbeute der hergestellten Chips,
• - eine physikalische Fehleranalyse.

Process technology and process integration particularly affect

• - the process integration of logic modules,
• - the process integration of memory modules,
• - product engineering,
• - monitoring and improving defect densities in manufacturing,
• - monitoring of electrical parameters in the manufactured products,
• improving the yield of the chips produced,
• - a physical error analysis.

Fig. 2 shows a semiconductor chip production installation, in other words a semiconductor chip factory 200 according to an embodiment of the invention having a plurality of semiconductor chip production sub-201 which become used to the processing of raw materials, such as a silicon wafer or a wafer of other semiconductor Materials (germanium, gallium arsenide, indium phosphide, etc.) to manufacture semiconductor chips from the raw materials.

A common manufacturing process for making a Semiconductor chips have hundreds of different ones Process steps in which in different Order of lithography steps, etching steps, CMP steps, Steps of applying materials to each to be processed wafers, or doping or Implantation steps of doping atoms in the processing wafers.

This results, as shown in FIG. 2 by lines 202 , which represent the path of a wafer or a lot through the semiconductor chip production system 200 . In the semiconductor chip production system 200 there are a large number of sensors which are assigned to the respective sub-production systems 201 and an even larger amount of raw data which are respectively recorded by the sensors and, as will be explained in more detail below, are processed. A respective sensor can be integrated in a respective machine (integrated sensor) or can be mounted separately on a respective machine (external sensor).

The sub-production systems 201 are also referred to below as machines 201 .

FIG. 3 shows an example of the data flow for data that are recorded on a machine 201 by means of an integrated or an external sensor 301 . Each sensor 301 , whereby any number of integrated and / or external sensors can be provided, detects the parameters of the machine 201 that are predefined for it, for example physical or chemical states in a process chamber, the position of a robot arm, etc.

The sensor 301 is coupled to a local communication network (Local Area Network, LAN) 306 via a SECS interface 302 , which is set up for data communication in accordance with the SECS standards.

In accordance with the SECS standards, files according to the PDSF format (Process Data Standard Format) are generated by the sensor 301 and the SECS interface 302, hereinafter also referred to as PDSF files 303 and log files 304 , the PDSF files 303 and the log files 304 are stored as raw data in a memory 307 , according to this exemplary embodiment for a limited period of time, preferably 6 months.

According to this exemplary embodiment, the PDSF files 303 contain analog data from up to 70 channels, that is to say from up to 70 different internal (ie integrated) and / or external sensors 301 , which can be attached to a machine 201 . According to this embodiment, approximately 150 Mbytes of data are generated per month and machine 201 and stored in the memory 307 .

Different data specific to the machine are stored in the log files 304 , for example a time indication, event details about events occurring in the machine 201 , alarms, logistical data. According to this embodiment, approximately 1 Mbyte of data is stored in a log file 304 in the memory 307 per month and machine.

The raw data stored in the memory 307 are grouped, that is to say filtered and supplied to different algorithms, as explained in more detail below, symbolized in FIG. 3 by means of a block 308, and when a predetermined alarm or message criterion is met, an alarm or a message is generated and transmitted via an alarm / message transmission unit 309 via the local communication network 306 and the SECS interface 302 to the machine 201 , which is likewise directly coupled to the SECS interface 302 , or to client computers 312 explained below.

In addition, process key figures are generated from the raw data using the filter algorithms and stored in an Oracle ™ database 310 , as will be explained in more detail below. According to this exemplary embodiment, approximately 6 Mbytes of data are stored as key figure data in the database 310 per month and machine.

Using the code numbers, different software tools, symbolized in FIG. 3 by a block 311 , are used to carry out statistical analyzes, to generate graphics, to produce reports or to provide a model of the manufacturing process for further simulation of the manufacturing process.

The corresponding data are in turn made available to a large number of client computers 312 by users, for example mechanical engineers, process engineers or product engineers, via the local communication network 306 , so that they use the analysis data to take appropriate measures for optimizing the semiconductor manufacturing process can make.

According to this exemplary embodiment, machines 201 from the field of front-end processing are described below, but it should be noted that the invention is in no way limited to the field of front-end processes, but rather relates in particular to all areas of semiconductor chip production.

• - Physikalische Abscheidung aus der Gasphase (Physical Vapour Deposition, PVD),
• - Chemische Abscheidung aus der Gasphase (Chemical Vapour Deposition, CVD),
• - Epitaxie,
• - Lithographie-Verfahren,
• - Ätzverfahren, insbesondere Plasmaätzverfahren, Trockenätzverfahren, Nassätzverfahren, etc.

As has been explained above, the semiconductor chip production system 200 in the area of the front-end processes according to this exemplary embodiment is grouped into several process areas, in particular in:

• - physical vapor deposition (PVD),
• - chemical vapor deposition (CVD),
• - epitaxy,
• - lithography process,
• - Etching processes, in particular plasma etching processes, dry etching processes, wet etching processes, etc.

According to the invention, the grouping of the machines 201 used in each case is carried out within the process areas of the front-end processes in such a way that all machines 201 which are to be jointly configurable or queryable are assigned to a machine group.

• - eine erste Maschinengruppe zur Abscheidung von TEOS,
• - eine zweite Maschinengruppe zur Abscheidung von Silan_1,
• - eine dritte Maschinengruppe zur Abscheidung von Silan_2,
• - eine vierte Maschinengruppe zum Abscheiden und zum Rückätzen von Wolfram (insbesondere Anlagen des Herstellers Applied Materials™).

For example, the process area of chemical separation from the gas phase is divided into four different machine groups, which provide different processes within the framework of a CVD process, namely:

• - a first machine group for the separation of TEOS,
• - a second machine group for the separation of Silan_1,
• - a third machine group for the separation of Silan_2,
• - a fourth machine group for the deposition and etching back of tungsten (in particular systems from the manufacturer Applied Materials ™).

The second and third machine groups differ according to this embodiment despite the same Field of application with regard to the logged and stored process parameters and the respectively used Processes so strong that a common configurability and queryability of the machines in the same Machine group would not make sense.

The example shown above shows that the grouping of the respective machines 201 used is heavily dependent on the machines 201 themselves and their respective areas of use in the context of the corresponding manufacturing process.

FIG. 1 shows the raw data recording in a block diagram 400 with seven machines 401 , 402 , 403 , 404 , 405 , 406 , 407 , each of which has one SECS interface 408 , 409 , 410 , 411 , 412 , 413 , 414 assigned to it Personal computer 415 , 416 , 417 , 418 , 419 , 420 , 421 is coupled. Via the respective SECS interface 408 , 409 , 410 , 411 , 412 , 413 , 414 , the machine 401 , 402 , 403 , 404 , 405 , 406 , 407 or the integrated and / or external sensors, which are assigned to the machine 401 , 402 , 403 , 404 , 405 , 406 , 407 , determined raw data to the respective personal computer 415 , 416 , 417 , 418 , 419 , 420 , 421 , which personal computer 415 , 416 , 417 , 418 , 419 , 420 , 421 transmit the received data to a raw data file server 422 . In the raw data file server 422 , the raw data transmitted by the personal computer 415 , 416 , 417 , 418 , 419 , 420 , 421 are each stored in a plurality of electronic files 423 , 424 , 425 , 426 , 427 , 428 , 429 are each stored in a respective directory, each of which is uniquely assigned to a machine or machine component 401 , 402 , 403 , 404 , 405 , 406 , 407 .

In other words, this means that in the raw data file server 422 in a directory 423 , 424 , 425 , 426 , 427 , 428 , 429 only the raw data from exactly one machine or machine component 401 , 402 , 403 , 404 , 405 , 406 , 407 are stored, so that a unique assignment of files stored in the raw data file server 422 in the directories 423 , 424 , 425 , 426 , 427 , 428 , 429 to the respective in the directories (folders) 423, 424 , 425, 426, 427, 428, 429 stored file generating machine 401 , 402 , 403 , 404 , 405 , 406 , 407 is possible.

In this context, it should be noted that, according to alternative embodiments of the invention, a 1: 1 assignment of SECS interface 408 , 409 , 410 , 411 , 412 , 413 , 414 to a personal computer 415 , 416 , 417 , 418 , 419 , 420 , 421 is required, but in general several personal computers for one SECS interface or one personal computer for several SECS interfaces can also be provided.

FIG. 5 clearly shows a section of a log file 304 , which is generated by the machine and the SECS interface 302 , and the extraction of key figures from the corresponding log file 304 .

For example, as shown in FIG. 5, the start of a process sequence of a machine is determined from the specification "Start Load - 17-ohne-4c", namely according to the log file 304 on 08/14/1998 at 04:08:25 ,

The time during which a pump is activated in a process chamber is determined from two events from the log file 304 , according to this exemplary embodiment from the event "Load Chamber Pumpdown Started", which occurs at a first point in time, namely 04:09:04 on August 14th .1998 and the event "Load Chamber Pumpdown Done", logged on 08/14/1998 at 04:32:19 generated by subtraction of the two logged times.

Another key figure, which is extracted from the log file 304 according to this exemplary embodiment, is the specification of a recipe, according to this exemplary embodiment of the recipe with the designation “C3-MET- 1000 ”.

• - in einer ersten Spalte 601 eine Index-Angabe,
• - in einer zweiten Spalte 602 eine Rezeptangabe,
• - in einer dritten Spalte 603 eine Angabe der Kassette, in welcher sich der jeweilige Wafer befindet, auf den sich die protokollierte Angabe bezieht,
• - in einer vierten Spalte 604 eine Angabe des Slots, in welchem sich der jeweilige bezeichnete Wafer befindet,
• - in einer fünften Spalte 605 eine Losangabe, in der das Los angegeben ist, auf welches in den der Wafer enthalten ist, auf den sich die jeweilige Angabe bezieht,
• - in einer sechsten Spalte 606 eine Angabe des jeweiligen Verfahrensschritts angegeben ist, der zu diesem Zeitpunkt gerade durchgeführt wird, sowie
• - in dem Ausschnitt der PDSF-Datei in Fig. 7 in einer Zeitspalte 701 eine Zeitangabe, über weitere Spalten 702 und 703 jeweils Verknüpfungsangaben zur Indizierung der jeweiligen Zeile des Ausschnitts aus der PDSF-Datei 303 gemäß Fig. 6 angegeben ist, sowie in weiteren Spalten 704, 705, 706, 707 die Angabe eines jeweiligen Prozessschrittes (Step A, Step B) sowie die Angabe von in dem jeweiligen Schritt in der jeweiligen Prozesskammer herrschenden Drucks (Pressure_A, Pressure_B).

In Figs. 6 and Fig. 7 shows an example of a section of PDSF file 303 is shown, wherein

• an index specification in a first column 601 ,
• in a second column 602 a recipe information,
• in a third column 603 an indication of the cassette in which the respective wafer is located, to which the logged information relates,
• in a fourth column 604 an indication of the slot in which the respective designated wafer is located,
• - in a fifth column 605, a lot information in which the lot is specified, to which the wafer is contained, to which the respective information relates,
• - In a sixth column 606, an indication of the respective method step that is currently being carried out is given, and
• 7 in the section of the PDSF file in FIG. 7 in a time column 701, via further columns 702 and 703 link information for indexing the respective line of the section from the PDSF file 303 according to FIG. 6 is given, as well as in others Columns 704 , 705 , 706 , 707 the specification of a respective process step (Step A, Step B) and the specification of the pressure prevailing in the respective step in the respective process chamber (Pressure_A, Pressure_B).

Typically about 50 different parameters recorded per machine. In addition to the parameters, how set out above, also lot information together with logistical information logged.

Thus, each data point, that is to say each line in a log file 304 or in a PDSF file 303, can be carried out clearly in one batch and corresponding logistic information such as the recipe used in each case, the respective technology or the operation carried out in a process chamber.

Physically identical parameters often have different ones Names or due to different sensors or versions The same parameters are often used by machines or sensors recorded in different physical units; for example, a first machine records the pressure in the unit Torr on, but a second machine in the Unit mTorr.

Fig. 8, the diagram shows an example of a machine 800 with a mainframe 801, and four process chambers 802, 803, 804, 805, the same or in the same way or in different ways for carrying out various processes and recipes can be designed.

Referring to FIGS. 4 and 9c which this embodiment provided in accordance with machines 401, 402, 403, 404, 405, 406, 407 machines of three different types, a shown in Fig. 9a first type of machine 9a to Fig.., A 9b shown in Fig. 9b and a third machine type shown in Fig. 9c.

According to the invention, the first machine 401 and the second machine 402 are grouped into a second machine group, according to this exemplary embodiment of a first machine type, as shown in FIG. 9b.

The machines 401 , 402 of the first machine type are a multi-chamber system from the Applied Materials ™ company of the Centura ™ type with four process chambers, a Centura ™ mainframe and in each case two loading stations for feeding and removing wafers to the machine or away from the machine.

• - eine erste Ladestation 901 als erste Ladekomponente bezeichnet mit A,
• - eine zweite Ladestation 902 als zweite Ladekomponente bezeichnet mit B,
• - ein Centura™-Mainframe 903 als Mainframe-Komponente bezeichnet mit MF (Komponente_1),
• - eine erste Prozesskammer A 904, eingerichtet als Abscheide-Prozesskammer, im Weiteren bezeichnet als Komponente_3,
• - eine zweite Prozesskammer B 905, eingerichtet ebenfalls als Abscheide-Prozesskammer, im Weiteren bezeichnet als Komponente_3,
• - eine dritte Prozesskammer C 906, eingerichtet als Rückätz-Prozesskammer, im Weiteren bezeichnet als Komponente_4,
• - eine vierte Prozesskammer D 907, eingerichtet als Rückätz-Prozesskammer, im Weiteren auch bezeichnet als Komponente_4.

According to this exemplary embodiment, the first machine 401 has the following machine components, which are each grouped into component types on the basis of the same or similar configuration:

• a first charging station 901, designated as A, with A,
• a second charging station 902 designated as a second charging component with B,
• a Centura ™ mainframe 903 designated as mainframe component with MF (component_1),
• a first process chamber A 904, set up as a separation process chamber, hereinafter referred to as component_3,
• a second process chamber B 905, also set up as a separation process chamber, hereinafter referred to as component_3,
• a third process chamber C 906, set up as an etch-back process chamber, hereinafter referred to as component_4,
• - A fourth process chamber D 907, set up as an etch-back process chamber, hereinafter also referred to as Component_4.

• - eine erste Ladestation 911 des ersten Komponententyps A,
• - eine zweite Ladestation 912 des zweiten Komponententyps B,
• - ein Centura™-Mainframe MF 913 als Komponente_1,
• - eine erste Prozesskammer A 914, eingerichtet als Abscheide-Prozesskammer (Komponente_3),
• - eine zweite Prozesskammer B 915, eingerichtet ebenfalls als Abscheide-Prozesskammer (Maschinenkomponente_3),
• - eine dritte Prozesskammer C 916, eingerichtet als Rückätz-Prozesskammer (Maschinenkomponente_4),
• - eine vierte Prozesskammer D 917, eingerichtet ebenfalls als Rückätz-Prozesskammer (Maschinenkomponente_4).

The second machine 402 has the following machine components as components, which are also grouped into component types on the basis of the same or similar configuration:

• a first charging station 911 of the first component type A,
• a second charging station 912 of the second component type B,
• - a Centura ™ mainframe MF 913 as component_1,
• a first process chamber A 914, set up as a separation process chamber (component_3),
• a second process chamber B 915, also set up as a separation process chamber (machine component_3),
• a third process chamber C 916, set up as an etch-back process chamber (machine component_4),
• - A fourth process chamber D 917, also set up as an etch-back process chamber (machine component_4).

Thus, the first machine 401 and the second machine 402 are grouped into the first machine type due to their very similar design and due to the same existing machine components of the same machine types, i.e. a machine type with a multi-chamber system with two charging stations, a mainframe and four process chambers.

According to the invention, the third machine 403 and the fourth machine 404 are grouped into a second machine group, according to this exemplary embodiment of a second machine type, as shown in FIG. 9b.

The third machine 403 and the fourth machine 404 are multi-process systems of the P5000 type with two process chambers, a P5000 ™ mainframe and two charging stations.

• - Eine erste Ladestation 921 des Komponententyps A,
• - eine zweite Ladestation 922 des Komponententyps B,
• - ein P5000-Mainframe MF 923 als Komponente_2, das heißt als eine zweite Maschinentyp-Mainframe-Komponente,
• - eine erste Prozesskammer B 924, eingerichtet als Abscheide-Prozesskammer (Komponente_3), sowie
• - eine zweite Prozesskammer D 925, eingerichtet als Rückätz-Prozesskammer (Komponente_4).

The third machine 403 has the following components of the respective following component type:

• A first charging station 921 of component type A,
• a second charging station 922 of component type B,
• a P5000 mainframe MF 923 as component_2, that is to say as a second machine type mainframe component,
• - a first process chamber B 924, set up as a separation process chamber (component_3), and
• - A second process chamber D 925, set up as an etch-back process chamber (component_4).

• - Eine erste Ladestation 931 des Komponententyps A,
• - eine zweite Ladestation 932 des Komponententyps B,
• - ein P5000™-Mainframe MF 933 als Komponente_2,
• - eine erste Prozesskammer A 934, eingerichtet als Abscheide-Prozesskammer als Maschinenkomponente_3,
• - sowie eine zweite Prozesskammer C 935, eingerichtet als Rückätz-Prozesskammer als Maschinenkomponente_4.

The fourth machine 404 has the following components:

• A first charging station 931 of component type A,
• a second charging station 932 of component type B,
• - a P5000 ™ mainframe MF 933 as component_2,
• a first process chamber A 934, set up as a separation process chamber as machine component_3,
• - and a second process chamber C 935, set up as an etch-back process chamber as machine component_4.

As can be seen from the above explanations, the third machine and the fourth machine 403 and 404 are grouped into a machine group (same machine type), since the mainframe is the same in terms of the required functionality, so that a joint examination of the generated raw data with regard to the desired monitored Data and their analysis is easily possible.

The fifth machine 405 , the sixth machine 406 and the seventh machine 407 are grouped according to the invention into a third machine group, according to this exemplary embodiment of a third machine type, as shown in FIG. 9c.

The machines of the third machine type are each one Single-chamber system with one process chamber each and only a charging station.

The fifth machine 405 has a charging station 941 and a process chamber 942 , set up as a separation process chamber (component_3).

The sixth machine 406 also has a charging station 951 and a process chamber 952 , likewise set up as a separation process chamber (component_3).

The seventh machine 407 has a charging station 961 and a process chamber 962 , likewise set up as a separating process chamber (component_3).

In this context, it should be noted that the assignment of the respective machine component to a machine component type (for example component_2, component_3, component_4) is a physical interpretation of a specialist in the respective machine, which corresponds to the corresponding specification of the machine 401 , 402 , 403 , 404 , 405 , 406 , 407 . It should be noted that the assignment can also be automated.

As shown in FIG. 10, different grouping options within a machine group can be considered according to the invention.

According to this embodiment, the machines are under grouped under the aspect of the machine itself or under the Component type aspect.

• - Rohdatenaufzeichnung pro Maschine,
• - Maschinenspezifische Probleme,
• - Vor- bzw. Nachprozess auf einer Maschine.

If the machine is grouped under the aspect of the respective machine itself and its properties, the following grouping criteria are taken into account in particular:

• - raw data recording per machine,
• - machine-specific problems,
• - Pre or post process on one machine.

• - Die identische Konfiguration für jeweils einen gleichen Komponententyp,
• - der Vergleich gleicher Komponententypen über verschiedene Maschinen hinweg.

If the machines are grouped according to the component types contained in the respective machine, the following objectives are taken into account in particular:

• - The identical configuration for the same component type,
• - the comparison of the same component types across different machines.

Fig. 10 illustrates the different grouping options according to this embodiment of the invention.

Fig. 11 shows in a grouping table 1100 an allocation of machine 1101 machine types 1102 machine components 1103 and machine components, types 1104 within a group of machines.

It should be noted in this context that the assignment both automated using appropriate Computer programs that have the similarities and Differences in machines, machine components or can automatically evaluate data generated by this as also manually by a specialist who can Machines and machine components or those of them interpreted generated data, can take place.

FIG. 11 also shows in the grouping table 1100 parameter sets 1105 , recipe sets 1106 and code number sets 1107 that are respectively assigned to the machines, which will be explained in more detail below.

Before a definition of the key figures is possible, over an assignment table differences in parameter names and in physical units by integrated and / or external sensors are used, cleaned up.

According to this exemplary embodiment, one parameter set is used for each machine component. In other words, different machine component types are assigned different parameter sets. However, several components can refer to the same parameter set. Depending on how differently the machines name and log the same parameters, there are correspondingly more or fewer parameter sets in the context of the respective grouping table 1100 .

• - Eine Zeitangabe;
• - für einen Mainframe, falls dieser vorhanden ist, der in der Transferkammer des Mainframes herrschende Druck,
• - sowie für alle Prozesskammern zusätzlich:
• - eine Rezeptschrittnummer des gerade in der Kammer ablaufenden Rezepts,
• - für die Abscheidekammern zusätzlich:
• - eine Angabe über den in der Abscheidekammer herrschenden Gasfluss, sowie
• - eine Angabe über den in der Abscheidekammer herrschenden Kammerdruck,
• - für die Rückätz-Kammern:
• - eine Angabe über die in die jeweilige Rückätzkammer eingespeiste Leistung,
• - eine Angabe über die von der jeweiligen Rückätzkammer reflektierte Leistung.

According to this exemplary embodiment, the following parameters are recorded by each machine 201 per unit of time, preferably per second:

• - A time indication;
• - for a mainframe, if there is one, the pressure prevailing in the transfer chamber of the mainframe,
• - as well as for all process chambers:
• - a recipe step number of the recipe currently running in the chamber,
• - for the separation chambers additionally:
• - an indication of the gas flow prevailing in the separation chamber, and
• - an indication of the chamber pressure prevailing in the separation chamber,
• - for the etching back chambers:
• an indication of the power fed into the respective etching back chamber,
• - An indication of the power reflected by the respective etching back chamber.

In FIGS. 12a to Fig. 12g for the respective machines 401, 402, 403, 404, 405, 406, 407, the respective raw data parameter 1201, the component types, 1202, the raw data parameter indication relate to the 1201 as well as the indication of the respective parameter sets 1203 to which the respective raw data parameter specification 1202 relates.

To explain the relationships shown in FIGS . 12a to 12g, some basic aspects of the assignments and illustrations are briefly explained below.

For example, all parameters that are necessary in the configuration of cross-chamber key figures have the same raw data parameter names for the first machine 401 for the second machine 402 .

For this reason the mainframe component references from the first machine 401 and the mainframe component of the second machine 402 to the same set of parameters, namely, the first set of parameters in 1204 (see. Fig. 12a and Fig. 12b).

According to this exemplary embodiment, all parameters that are necessary in the configuration of cross-chamber key figures have different raw data parameter names for the third machine 403 and the fourth machine 404 .

For this reason the mainframe component references the third machine 403 to a second set of parameters 1205 and the mainframe component of the fourth machine 404 to a third set of parameters in 1206 (see. Fig. 12c and Fig. 12d).

The first process chamber A 904 of the first machine 401 and the first process chamber A 914 of the second machine 402 are both set up and use as separation process chambers, ie they log the same raw data parameter names. Thus, the first process chamber A point of the first machine 401 and the first process chamber A of the second machine 402 to a same set of parameters, namely, a fourth parameter set in 1207 (see. Fig. 12a and Fig. 12b).

The assignment of different raw data parameters to different parameter sets or the same Raw data parameters for the same parameter sets and their appropriate renaming is in a common parameter machine dependent and can be automatic or by a Expert done manually.

The further connections and the references to the others Parameter sets are made in the same way as shown above and are therefore not explained in more detail.

With a corresponding assignment of the individual machine components to the individual parameter sets, the grouping table 1300 shown in FIG. 13 results.

According to this embodiment, the Raw data parameter names for all machine types / machines renamed as follows. A distinction is made between Process chamber-related raw data parameter names and Cross-process chamber raw data parameter names.

• - Zeit → TIME
• - Rezeptschrittidentifizierungsangabe, vorzugsweise Rezeptschrittnummer des gerade in der Prozesskammer ablaufenden Rezepts → STEP,
• - die Angabe des in der Prozesskammer herrschenden Gasflusses → Gas,
• - die Angabe des in der Prozesskammer herrschenden Kammerdrucks → DRUCK,
• - die Angabe der in die Prozesskammer eingespeisten Leistung → LEISTUNG-FW,
• - die Angabe der von der Prozesskammer reflektierten Leistung → LEISTUNG-BW.

The process chamber-related raw data parameter names are renamed as follows:

• - Time → TIME
• - Recipe step identification information, preferably recipe step number of the recipe currently running in the process chamber → STEP,
• - the indication of the gas flow prevailing in the process chamber → gas,
• - the specification of the chamber pressure prevailing in the process chamber → PRESSURE,
• - the specification of the power fed into the process chamber → POWER-FW,
• - the specification of the power reflected by the process chamber → LEISTUNG-BW.

• - Zeit → TIME,
• - Rezeptschrittidentifizierungsangabe, vorzugsweise Rezeptschrittnummer des gerade in der Prozesskammer ablaufenden Rezepts → STEP_A, STEP_B, STEP_C, STEP_D,
• - der in der Kammer herrschende Kammerdruck → DRUCK_A, DRUCK_B,
• - der in der Transferkammer herrschende Druck → TRANSFER_DRUCK.

The process data-spanning raw data parameter names are shown as follows:

• - time → TIME,
• - Recipe step identification information, preferably recipe step number of the recipe currently running in the process chamber → STEP_A, STEP_B, STEP_C, STEP_D,
• - the chamber pressure prevailing in the chamber → DRUCK_A, DRUCK_B,
• - the pressure prevailing in the transfer chamber → TRANSFER_DRUCK.

This image is shown in the tables in Fig. 14, Fig. 15 and Fig. 16, in which the raw data parameter names are mapped in 1401 a parameter set 1400 to the illustrated above APC parameter names 1402nd

Thus filters shown in FIGS. 14, Fig. 15 and Fig. 16 each parameter sets shown the processing performed figure provided for in the parameter sets raw data parameter names on the APC used parameter names, as set forth above, is.

This will result in a significant reduction in used parameter name reached without Information content in the analysis of the determined raw data get lost.

The processing of a wafer or simultaneously several wafers in a process chamber of a machine 401 , 402 , 403 , 404 , 405 , 406 , 407 usually takes place in one or more process steps.

The one for processing one wafer or several at the same time Process steps required for wafers become recipes summarized.

Every process step, i.e. every recipe step has one clearly assigned to the recipe step and this characterizing recipe step number. Alternatively, the Recipe step one also clearly the recipe step identifying description.

The recipe number or the recipe description is recorded in the raw data file as the "STEP" parameter. Different recipes run in a process chamber of a machine 401 , 402 , 403 , 404 , 405 , 406 , 407 , usually between 5 to 10 in a chip production system 200 for the production of memory chips and usually 50 to 100 different recipes for a chip Production plant 200 for the production of logic chips.

Also for different recipes of a process chamber type Similarities and differences are determined and exploited according to the invention to further compress the To achieve raw data.

In this context it should be noted that for the same Recipes also use different recipe names can.

Fig. 17 shows in tables seven recipe sets 1701 , 1702 , 1703 , 1704 , 1705 , 1706 , 1707 and the assignment of the respective process chambers of the machines 401 , 402 , 403 , 404 , 405 , 406 , 407 to the recipes that are in the respective Process chambers are carried out.

The similarities of recipes are brought together as generalized recipe steps according to the invention in the recipe table 1800 shown in FIG. 18. The recipe step numbers or the recipe step descriptions are generally assigned to recipe steps and thus combined into recipe groups, ie a respective recipe set. In this context, it should be noted that different recipe sets can have the same generalized recipe names, for example recipe set_1, recipe set_2,. , ., Recipe Set_7, and can contain the generalized recipe steps, for example "Stab", "Main", "Cool".

Fig. 19 shows the recipe according to assignment to the respective sets recipe for all deposition process chambers of the machine group to an embodiment of the invention.

This assignment can also be automated or by a Expert manually done with knowledge of each recipes used and the properties of those used Machines and process chambers.

Fig. 19 shows the configuration recipe for all deposition process chambers of the machine group.

Furthermore, part of the assignment is used for clarification and the principle on which the assignment is based explained.

For the first process chamber A of the first machine 401 , the "main step" of the recipe "Reci_1" is the recipe step number 3 , but for the recipe "Reci_3" this is the recipe step number 4 . On another machine, the main step of all recipes is labeled "MAIN". The assignment of which recipe step is the respective main step of the recipe can likewise be carried out automatically using appropriate knowledge or manually by a specialist on the basis of a physical interpretation of the respective process step.

Using the allocation tables 1901 , 1902 , 1903 , 1904 , 1905 shown in FIG. 19, it is now possible to define key figures independently of the recipe by referring to the generalized recipe steps. With the help of the recipe tables, that is to say the assignment tables 1901 , 1902 , 1903 , 1904 , 1905 , the generalized recipe step is stored in a clearly identifiable manner for each recipe listed there.

The same recipes can be used on different machines be labeled differently.

With the help of the recipe tables 1901 , 1902 , 1903 , 1904 , 1905 , it is possible according to the invention to rename these recipe names in such a way that the same recipes that are carried out on different machines are designated in the same way. In general, this means that recipe meta- Terms are introduced, hereinafter also referred to as APC recipes.

The mapping and mapping of one machine-specific recipe for an APC recipe is again automated possible or by a physical Interpretation done by a professional.

The further steps shown in the assignment tables 1901 , 1902 , 1903 , 1904 , 1905 are the stabilization of the conditions in a process chamber ("STAB") and the phase of cooling the process chamber after the main step ("COOL").

The recipe configuration for the recipes shown in FIG. 20, which are carried out in the etching-back process chambers of the machine group, takes place in a corresponding manner.

The process steps carried out and the corresponding mapping rules are shown in the allocation tables 2001 , 2002 . In particular, the process steps of approaching the process chamber to process conditions ("RAMP"), stabilizing the process conditions in the process chamber ("STAB"), etching as the main step of the recipe running in the process chamber ("ETCH"), and retracting the Status of the process chamber shown on normal status ("RINSE").

Thus, for etch back process chambers according to this Embodiment three generalized recipe steps defined (STAB, MAIN, COOL) as well as for Process chambers four general recipe steps (RAMP, STAB, EDGE, RINSE).

• - Abscheide-Prozesskammern auf drei unterschiedliche APC- Rezeptnamen reduziert (gemäß diesem Ausführungsbeispiel erfolgt eine Reduktion von 8 maschinenspezifischen Rezeptnamen auf drei APC-Rezeptnamen): KOMP_3_REZEPT_1, KOMP_3_REZEPT_2, KOMP_3_REZEPT_3;
• - für Rückätz-Prozesskammern auf vier unterschiedliche APC-Rezeptnamen reduziert, nämlich KOMP_4_REZEPT_1, KOMP_4_REZEPT_2, KOMP_4_REZEPT_3, KOMP_4_REZEPT_4.

Many identical recipes with different machine-specific recipe names were invented for the

• - Separation process chambers reduced to three different APC recipe names (according to this exemplary embodiment, 8 machine-specific recipe names are reduced to three APC recipe names): KOMP_3_REZEPT_1, KOMP_3_REZEPT_2, KOMP_3_REZEPT_3;
• - Reduced to four different APC recipe names for etch back process chambers, namely KOMP_4_REZEPT_1, KOMP_4_REZEPT_2, KOMP_4_REZEPT_3, KOMP_4_REZEPT_4.

Thus, according to the invention, there is also a considerable reduction regarding the recipes and recipe names used allows. In this way, with appropriate Group the machine components of the same type same parameter sets and same recipe set for one the same key figure set can be summarized together an analysis designed in the same way can be.

The assignment of machines, machine types, machine components and machine component types, parameter sets, recipe sets to the respective key figure sets are shown in accordance with this exemplary embodiment of the invention in a corresponding assignment table in 2100 in FIG. 21.

Fig. 22 shows the corresponding ratios for the configuration and the Maschinenkomponente_1 Maschinenkomponente_2 at two different mainframes.

As can be seen from the allocation table 2200 in FIG. 22, the respectively determined and grouped data are subjected to a statistical analysis, for example the check as to whether the values to be monitored lie within a predetermined admissibility interval of the monitored values or an average value determination of the determined values and the monitoring the respective determined mean value with regard to the admissibility of the value compared with predetermined target criteria. The assignment table 2200 determines how compressed key figures are generated from the raw data, ie the partial production data (data per time interval), for example the statistical mean value of a parameter in a specific recipe step, the statistical spread of this parameter in a specific recipe step, etc.

There can also be a standard deviation for those to be monitored Values are determined and the standard deviation with predefined target criteria are compared.

If the determined values deviate from the target criteria in accordance with the algorithm used, an alarm message can be generated by an additionally provided alarm generation unit and the user can be shown on the client computer 312 in which alarm generation unit furthermore alarm generation criteria are stored, that are applied by the alarm generating unit.

Further key figure configurations and the statistical analyzes are also shown for an etch-back process chamber in the configuration table 2300 in FIG. 23 and for a deposition process chamber in the configuration table 2400 in FIG. 24.

Furthermore, a brief summary of the compression that can be achieved on production data is presented:
According to the exemplary embodiment, seven machines are provided in the semiconductor production system, which are grouped into a machine group. According to this exemplary embodiment, between four and seven different recipes run on each machine, which in turn each have between three and four essential recipe steps. Between four and fourteen different raw data parameters are recorded and recorded for each machine.

• - Eine Reduktion der Parameter von 37 auf 13,
• - eine Reduktion der Rezeptnamen von 18 auf 7,
• - eine Reduktion der Rezeptschritte von 53 auf 7,
• - eine Reduktion von Kennzahlentabellen von 19 auf 3.

The following reduction results from the different assignment tables for the configuration of key figures described above:

• - a reduction of the parameters from 37 to 13,
• - a reduction of the recipe names from 18 to 7,
• - a reduction of the recipe steps from 53 to 7,
• - a reduction in key figure tables from 19 to 3.

This leads to a total reduction of 670,662 parameters to be recorded and monitored (37.18.53.19) now only 1,911 to be monitored according to the invention Parameters (13.7.7.3).

For a conventional semiconductor chip production system, in which it is assumed that 50 raw data parameters are used with three different software versions and 50 recipes with 10 to 15 essential recipe steps (with two different machine types, 50 completely different recipes) and with 15 machines in a production system (4th -Process chamber machines and with two different process chambers) leads to a reduction in data to be monitored of approximately 10,000: 1. Reference number list 100 block diagram
101 overall manufacturing process
102 front-end processes
103 back-end processes
104 support elements
105 Process technology and process integration
200 semiconductor chip production plant
201 semiconductor chip part production plant / machine
202 lines
300 block diagram
301 sensor
302 SECS interface
303 PDSF file
304 log file
305 logistics data
306 Local communication network
307 memories
308 APC filters and algorithms
309 Alarm / message sending unit
310 database
311 block
312 Client computers
400 block diagram
401 First machine
402 Second machine
403 Third machine
404 fourth machine
405 fifth machine
406 Sixth machine
407 seventh machine
408 SECS interface first machine
409 SECS interface second machine
410 SECS interface third machine
411 SECS interface fourth machine
412 SECS interface fifth machine
413 SECS interface sixth machine
414 SECS interface seventh machine
415 First personal computer
416 Second personal computer
417 Third Personal Computer
418 fourth personal computer
419 Fifth Personal Computer
420 sixth personal computer
421 Seventh Personal Computer
422 Raw data file server
423 First file
424 Second file
425 Third file
426 Fourth file
427 Fifth file
428 Sixth file
429 Seventh file
601 First column
602 Second column
603 Third column
604 fourth column
605 Fifth column
606 Sixth column
701 time
702 index column
703 Another column
704 Another column
705 Another column
706 Another column
707 Another column
800 machine
801 main frame
802 process chamber
803 process chamber
804 process chamber
805 process chamber
901 First loading station, first machine
902 second loading station first machine
903 mainframe first machine
904 First process chamber, first machine
905 Second process chamber, first machine
906 Third process chamber, first machine
907 fourth process chamber first machine
911 First loading station second machine
912 second charging station second machine
913 mainframe second machine
914 First process chamber, second machine
915 Second process chamber second machine
916 Third process chamber second machine
917 fourth process chamber second machine
921 first charging station third machine
922 second charging station third machine
923 mainframe third machine
924 First process chamber, third machine
925 second process chamber third machine
931 First charging station fourth machine
932 second charging station fourth machine
933 mainframe fourth machine
934 First process chamber fourth machine
935 second process chamber fourth machine
941 charging station fifth machine
942 process chamber fifth machine
951 charging station sixth machine
952 process chamber sixth machine
961 charging station seventh machine
962 process chamber seventh machine
1100 allocation table
1101 machine
1102 machine type
1103 machine component
1104 Machine component type
1105 parameter set
1106 recipe set
1107 key figure record
1201 raw data parameter names
1202 machine component type
1203 parameter set
1204 First parameter set
1205 Second parameter set
1206 Third parameter set
1207 Fourth parameter set
1300 grouping table
1400 parameter set
1401 raw data parameter name
1402 APC parameter name
1701 First recipe set
1702 Second recipe set
1703 Third recipe set
1704 Fourth recipe set
1705 Fifth recipe set
1706 Sixth recipe set
1707 Seventh recipe set
1800 recipe table
1901 allocation table
1902 allocation table
1903 allocation table
1904 allocation table
1905 allocation table
2001 allocation table
2002 allocation table
2100 allocation table
2200 allocation table
2300 configuration table
2400 configuration table

Claims (9)

1. Method for capturing production data in a production plant with several sub-production plants,
in which partial production data is determined and stored by the partial production systems,
in which, based on at least one grouping table with assignment of the partial production data to groups of the grouping table, the partial production data are mapped to compressed partial production data,
being in the grouping table
Machines of the sub-production plants are grouped into at least one machine group, or
Machine components of the sub-production plants are grouped into at least one machine component group, or
Manufacturing recipes are grouped into at least one recipe group, or
Manufacturing parameters are grouped into at least one parameter group. 2. The method according to claim 1,
in which partial production data from partial production systems of a chip production system are determined and stored, and
at the in the grouping table
Chip manufacturing recipes are grouped into at least one recipe group, or
Chip manufacturing parameters are grouped into at least one parameter group. 3. The method according to claim 1 or 2, where the part production data from the part Production facilities transmitted to a central store and stored there in at least one central file become. 4. The method according to any one of claims 1 to 3, where the machines are grouped into machine groups, which have sufficiently similar machine properties. 5. The method according to any one of claims 1 to 3, where the machine components form machine component groups be grouped which are sufficiently similar Have machine component properties. 6. The method according to any one of claims 1 to 3, where the manufacturing recipes are grouped into recipe groups which have sufficiently similar recipes. 7. The method according to any one of claims 1 to 3, where the manufacturing parameters to parameter groups be grouped which are sufficiently similar Have manufacturing parameters. 8. The method according to any one of claims 1 to 7, where the compressed part production data one undergo statistical analysis. 9. system for recording production data in a production plant,
with several partial production plants, which generate partial production data,
with at least one memory for storing the generated partial production data,
with an evaluation computer coupled to the memory, which is set up in such a way that on the basis of at least one grouping table, while assigning the partial production data to groups in the grouping table, the partial production data are mapped to compressed partial production data,
being in the grouping table
Machines of the sub-production plants are grouped into at least one machine group, or
Machine components of the sub-production plants are grouped into at least one machine component group, or
Manufacturing recipes are grouped into at least one recipe group, or
Manufacturing parameters are grouped into at least one parameter group.