WO2002066967A1

WO2002066967A1 - Contaminating particle classification system and method

Info

Publication number: WO2002066967A1
Application number: PCT/IT2001/000084
Authority: WO
Inventors: Gianfranco Curti
Original assignee: MEMC Electronic Materials SpA; SunEdison Inc
Current assignee: MEMC Electronic Materials SpA; SunEdison Inc
Priority date: 2001-02-21
Filing date: 2001-02-21
Publication date: 2002-08-29
Anticipated expiration: 2003-08-21

Abstract

A system and method for classifying contaminating particles on a wafer surface. The present invention collects first and second sets of data with the locations and sizes of contaminating particles upon a surface of a semiconductor wafer at a first time and a second time, respectively. An intervening process may alter the contaminating particle landscape of the wafer surface, altering the number and location of contaminating particles between the first and second times. To understand this change, the invention then compares the locations and sizes of the contaminating particles and further classifies the particles as belonging to one of three categories: fixed, removed and added. The results of this process are then compiled into various output forms. These data comparisons and classifications allow users to understand the source and impact of contaminating particles, so that the intervening may be altered, if required, to reduce the impact of contaminating particles.

Description

CONTAMINATING PARTICLE CLASSIFICATION SYSTEM AND METHOD

Background of the Invention

This invention relates to a system and method for evaluating the contaminating particles of a surface, and more specifically to such a system and method that compare detected particle locations on the surface at two different times.

Processing an article to produce a surface that is highly reflective and damage free has application in many fields. A particularly smooth and damage free surface is required when processing semiconductor wafers in preparation for printing circuits on the wafer by an electron beam-lithographic or photolithographic process. Even tiny particulate matter adhering to the wafer surface is undesirable. Under current processing techniques, wafers may be scanned at various times during processing to detect the number of particles on a particular wafer surface. Comparing the number of particles found at these different times will show whether particles have been added to the surface due to the processing of the wafer. We call such an analysis a particle addition test. If the wafer surface has the same or fewer particles from an earlier time to a later time, then by the particle addition test, the intervening process is acceptable, since no particles were added to the wafer surface. Often the intervening process is a cleaning process designed to remove particulate matter from the wafer surface. A cleaning process typically requires the application and removal of a cleaning fluid, which although designed to aid in particle removal, may inadvertently add some particulate matter to the surface.

The particle addition test is a simple test for determining the total number of contaminating particles added to or subtracted from the wafer surface between two points in time. Although the test is a valid indicator of more or less total contaminating particles on a wafer, it cannot provide information concerning what happened to the contaminating particles during cleaning. If particles were only removed and were never also added to the wafer surface by a cleaning process, then the particle addition test would be a valid method of showing whether the process could remove contaminating particles. The standard particle addition test, however, cannot distinguish among the three possible event classes, namely removed particles, added particles or fixed particles. Simply having an equivalent particle count before and after cleaning does not show that the process performed well. A more realistic model of the movement of contaminating particles introduces the potential for contaminating particles to be added, removed or fixed to the wafer surface during cleaning. By monitoring these events, the user can gather more information about the contaminant removal or addition capabilities of the cleaning process. In addition, monitoring the location of these events can help the user to identify potential wafer processing problems or areas for improvement.

Summary of the Invention

Among the several objects and features of the present invention may be noted the provision of a system and method for classifying contaminating particles on a surface; the provision of such a system and method which classify contaminating particles into groups to facilitate identifying contamination sources; the provision of such a system and method which provide surface area maps depicting the locations of contaminating particles; and the provision of such a system and method which provide for tracking of contaminating particle trends over time.

Generally, a system of the present invention is disclosed for classifying contaminating particles on a surface. The system comprises a first memory of a first set of data including the locations of contaminating particles upon a surface at a first time and a second memory of a second set of data including the locations of contaminating particles upon the surface at a second time, later than the first time.

The system also comprises a digital processor for collecting and storing the first and second sets of data, comparing the locations of the contaminating particles of the first set of data with the locations of the contaminating particles of the second set of data, and classifying at least some of the contaminating particles in the first and second sets of data as a function of the comparing step.

In another aspect of the present invention, a method is disclosed for classifying contaminating particles on a surface. The method comprises the steps of collecting a first set of data including the locations of contaminating particles upon a surface at a first time and collecting a second set of data including the locations of contaminating particles upon the surface at a second time, later than the first time.

The method additionally comprises the step of comparing the locations of the contaminating particles of the first set of data with the locations of the contaminating particles of the second set of data. The method includes the step of classifying at least some of the contaminating particles in the first and second sets of data as a function of the comparing step.

In a final aspect of the present invention, a system is disclosed for classifying contaminating particles on a surface. The system comprises means for collecting a first set of data including the locations of contaminating particles upon a surface at a first time. Additionally, means for collecting a second set of data including the locations of contaminating particles upon said surface at a second time, later than the first time, is included. Means for comparing the locations of the contaminating particles of the first set of data with the locations of the contaminating particles of the second set of data is also included. Finally, means for classifying at least some of the contaminating particles in the first and second data sets of data as a function of the comparing step is disclosed.

Other objects and features of the present invention will be in part apparent and in part pointed out hereinafter.

Brief Description of the Drawings

FIG. 1 is a schematic of the present invention; FIG. 2 is a flowchart illustrating the operation of the present invention; FIG. 3 is a partial data table with contaminating particle information stored from a first time; FIG. 4 is a partial data table with contaminating particle information stored from a second time;

FIG. 5 is a schematic of a location tolerance margin box surrounding a contaminating particle;

FIG. 6 is a schematic of a size tolerance area about a contaminating particle; FIG. 7 is a partial data table with contaminating particle information on particles fixed from a first time to a second time; FIG. 8 is a schematic of a user interface;

FIG. 9 is a set of graphs depicting sample weekly trends of the contaminating particles; FIG. 10 is a set of sample wafer maps showing the locations of contaminating particles on the wafer surfaces; and

FIG. 11 is an additional set of sample wafer maps showing the locations of contaminating particles on the wafer surfaces. Corresponding reference characters indicate corresponding parts throughout the several views of the drawings.

Detailed Description of the Preferred Embodiments

The preferred system and method for classifying a plurality of contaminating particles are discussed in detail below. In addition, it is contemplated that other methods of classifying unique contaminating particles into particle groups would not depart from the scope of the present invention. The computerized methodology disclosed herein is illustrative of one way of compiling and comparing data, and other collection and comparison methods are contemplated as part of the present invention. The purpose of the present invention is to classify contaminating particles found on smooth surfaces into three main categories: added, fixed or removed. By monitoring these three categories, the precise movement of contaminating particles may be studied, and the user may more easily identify the root cause of any problems or potential process enhancements. This process and its benefits will be discussed in greater detail below. The tool also allows a spatial analysis so that the locations of the particles may be reviewed easily to better identify contamination sources or failures in removing contaminating particles.

Referring now to FIG. 1 , a system for classifying contaminating particles on a surface, generally indicated 15, comprises a first memory 15a, a second memory 15b, and a digital processor 15c. The surface may be any surface, but preferably is a surface substantially free of defects, such as the polished surface of a semiconductor wafer. The first memory 15a contains a first set of data, gathered by an optical data acquisition device 15d, which includes the locations of contaminating particles upon the surface at a first time. The first memory 15a may also include other information about the contaminating particles, as described in greater detail below. The second memory 15b contains a second set of data, gathered by the optical data acquisition device 15d, which includes the locations of contaminating particles upon the surface at a second time. The second time is preferably later than the first time, so that an intervening process or step imparted on the wafer may have altered the contaminating particles on the surface. In the preferred embodiment, the intervening process is a cleaning process. This intervening process, however, may be any number of processes or merely the passage of time during which the wafer is in storage. Other intervening processes are contemplated (e.g., storage, shipping, pre-cleaning, cleaning and final cleaning processes), while the following discussion will focus on the preferred process, wafer cleaning. The system also includes the digital processor 15c for collecting the data, comparing the data and classifying any contaminating particles found on the wafer surface. As will be described in greater detail below and is shown schematically in FIG. 1 , the system 15 collects and stores the first and second sets of data and then compares the locations of the contaminating particles of the first set of data with the locations of the contaminating particles of the second set of data. The digital processor 15c classifies at least some of the contaminating particles as a function of the comparing step and makes those classifications available to the user in the form of output date 15e.

Referring now to FIG. 2, a flowchart of the system and method of the present invention is indicated generally by 16. Initially, the optical data acquisition device 15d collects a first set of data 17 concerning contaminating particle size and location from a population of wafers. The wafers are then processed 18 in any number of ways, as will be discussed in greater detail below. After processing, the data acquisition device 15d collects a second data set 19, recording the size and location of any contaminating particles remaining of the wafers after processing. This procedure of recording a first and second set of data on a particular set of wafers ^' may be repeated numerous times on multiple wafer sets. Each time, the data acquisition device 15d records the location and size of contaminating particles on each particular wafer. Once the data is collected and stored, a user may issue a run command 19a to launch the program of the present invention, initiating the following chain of events. Several pieces of data that were collected by the data acquisition device 15d are recorded in a database for each contaminating particle (FIG. 3). Each particle is initially identified with an identification number 21. Data indicating the month 23 and week 25 of the measurement also are recorded to identify the time when each measurement was taken. In addition, particular processing parameters by which the wafers are processed may be recorded with each data point (e.g., front or rear position within a cleaning tank). For instance, a processing parameter 27 such as front or rear could be used to indicate which location a wafer was processed inside a particular processing device having, for example, front and rear cleaning positions. Each contaminating particle also may receive a slot designation 31 to identify its location within the wafer carrier. Wafers are preferably held in wafer carriers that hold a plurality of wafers, typically twenty-five. The slot designation 31 indicates in what slot a particular wafer resides, particularly identifying the location of each wafer. Any number of other identifiers may be added to the data sets to adequately describe the wafer and contaminating particles, depending upon the processing methods of a particular situation.

In addition, the location of each contaminating particle on the wafer surface is also recorded. In the preferred embodiment, a Cartesian coordinate plane divides the wafer surface so that two recorded values, an x-coordinate and a y-coordinate, readily identify the location of each particle. Preferably, the zero axis crossing of the coordinate plane passes through the center of the wafer surface with positive and negative values lying on either side of the axes, respectively. The particles recorded in FIG. 3 are shown using such a system, where "xb" represents the x-coordinate 33, "yb" represents the y-coordinate 35 and both values are recorded in millimeters. Other methods of identifying particle locations on a wafer surface are also contemplated as within the scope of the present invention (e.g., polar coordinate systems, etc.).

The final piece of data collected and stored is the size of the contaminating particle, denoted by "sb" 37 in FIG. 3. Contaminating particles may form in various shapes, although most can be estimated to be mounds of about circular perimeter. The size is expressed as the diameter, or width, of the mound in units of microns. Once collected, these data are preferably stored in two data tables, named BEF (before cleaning), generally indicated at 39, and AFT (after cleaning), generally indicated at 41. Portions of these tables 39, 41 are shown in FIGS. 3 and 4, and they are schematically illustrated in FIG. 2. The BEF table 39 contains data on particles that are potentially either fixed events or removed events while the AFT table 41 contains data on particles that are potentially either fixed events or added events.

Collecting contaminating particle data of this sort from wafers is well known in the art. Modern systems use automatic means for detecting the sizes and locations of contaminating particles on a wafer surface and typically store the particle information digitally, within computer memories. Several different automatic data acquisition devices 15d are suitable for such a task. For example, the AOS Constellation Series is manufactured by ADE Optical Systems (AOS) of Charlotte, North Carolina, U.S.A., a subsidiary of ADE Corporation of Newton, Massachusetts, U.S.A. Another suitable product is the KLA-Tencor SP1 Series, manufactured by KLA-Tencor Corporation of San Jose, California, U.S.A. Both devices can collect the data discussed above. The data acquisition devices 15d described above are limited in their capability of determining particle size. For instance, where the diameter of the particle exceeds a certain value, the KLA-Tencor device can no longer detect the exact particle size. As an approximation, the device calculates an approximate diameter of the particle that may be larger than the actual particle diameter. For instance, where the diameter of the contaminating particle is larger than 2.0 microns (79 microinches), the particle size is expressed as an area, with units of millimeters squared, so that the particle size results in a value of less than 0.1 (when expressed in millimeters squared). For example, a large particle may receive an estimated diameter of 250 microns (9,800 microinches) with an approximate area of 49,000 square microns (76 million square microinches). Because the measuring device is approximating this area, however, the reported area may be quite larger than the actual particle area. In any event, the system must record these particles because they represent significant surface defects. Thus, the system converts the particle area from units of square microns to units of square millimeters. In the present example, the unit change would alter the reported particle area to 0.049 millimeters squared (76 milli-inches squared). This unit transformation ensures that the reported particle size, in square millimeters, is less than 0.1 so that the scale of the reported size is comparable to the typical contaminating particle. As such, the program logic must account for this difference in units when classifying the contaminating particles, to ensure that larger particles are included in the wafer maps.

Once the BEF and AFT tables 39, 41 contain the contaminating particle data are completed, the locations of the contaminating particles on the wafers in the first set of data can be compared with the locations of the contaminating particles in the second set of data. A series of data manipulation steps must be performed to compare the data properly. The digital processor 15c of the present invention is specifically designed to perform such data manipulations. The present invention comprises a computer macro program written in Microsoft Access, a programmable data management program, as designed and distributed by Microsoft Corporation of Redmond, Washington, U.S.A. Other computer programs or processing apparatus capable of performing the tasks outlined below are also contemplated as within the scope of the present invention. The present invention also contemplates performing the following steps by any method, including those not involving a computer, such as by hand.

The first step involves comparing 45 and classifying 47 (FIG. 2) each contaminating particle included in both sets of data as fixed on the surface from a first time to a second time. Preferably, the data from the first time and the second time is sorted by month 23, week 25, location identifier 27 and slot designation 31 , ordering both sets of contaminating particle data for comparisorj of the position and size of the contaminating particles. Figures 5 and 6 illustrate certain aspects of the classification procedure, which preferably requires that two parameters be met in order for a particle to be classified as being "fixed." First, a particle 61 included in the second set of data must lie within the tolerance box surrounding the particle found in the first set of data, as shown by the shaded area in FIG. 5. Second, the particle's size must lie within the size tolerance range, as shown by the shaded area in FIG. 6. Particles 61 classified as fixed from a first time to a second time must meet these two parameters. First, the location of the particle 61 in each data set must be the same, within a location tolerance margin 63; and second, the size of the particle in each data set must be the same, within a size tolerance margin 65. A typical range for a location tolerance margin 63 would range from about 0.20 microns (7.9 microinches) to about 0.30 microns (12 microinches), however the preferred location tolerance margin is 0.25 microns (9.8 microinches). The same location tolerance margin 63 is typically used for both the x-coordinate and the y- coordinate, creating a tolerance box 71 surrounding each particle 61 identified at a first time (FIG. 5). A particle 61 found at the second time having coordinates within the tolerance box 71 is classified as a matched location particle 75, and will be considered a potentially matching particle. A particle 61 outside the tolerance box 71 is an unmatched location particle 79, and will not be considered a potentially matching particle. A user may alter the location tolerance margin 63 to increase or decrease the size of the box, depending upon the application. Moreover, the tolerance margin 63 may be carried out as a radius, such that the tolerance box 71 becomes a tolerance circle (not shown). Turning to the second parameter, particle size, the relative sizes of the contaminating particles 61 must then be compared to decide if the particle found in the second set of data is likely to be the same particle recorded in the first data set. The size tolerance 65 helps rule out new particles 61 , while identifying those particles that are the same, although they may have slightly changed size between the first time and the second time. The size tolerance margin 65 for particle size requires that the difference in size between two particles 61 be less than a fixed size tolerance margin. A typical range for a size tolerance margin 65 would be from about 0.08 microns (3 microinches) to about 0.12 microns (4.7 microinches), however the preferred size tolerance is 0.1 microns (4 microinches). The size tolerance margin 65 creates a tolerance ring 83 about the particle from a first time, within which a matching particle 85 must fit to be considered the same. For instance, unmatched particle 87 is too large and unmatched particle 89 is too small to fit within the tolerance ring 83. Two particles 61 having a greater size differential than the size tolerance 65 do not satisfy the second parameter and are assumed to be different particles.

The tolerance margins 63, 65 may be altered depending upon the processes applied to the wafer between the first time and the second time. For instance, where the intervening process is epitaxial deposition, the size tolerance would likely need to be much larger than the size tolerance for an intervening cleaning process, because the epitaxial process adds matter to the wafer surface, likely altering the size of the contaminating particle. A typical size tolerance for an intervening cleaning process might be 0.1 microns (4 microinches), while a size tolerance for an intervening epitaxial process may be 0.5 microns (20 microinches) or more. In addition, the size tolerance may be increased to an extremely large number (e.g., 10,000 microns (400,000 microinches)) so that essentially all particles will meet the size tolerance of a given particle. In such a case, the two parameter test collapses into a one parameter test where only the locations of the contaminating particles are used to match particles from a first time to a second time. By applying these tolerances 63,65 to the two data sets, as recorded in the

BEF and AFT tables 39, 41 , the system compares the contaminating particles from each set and determine whether each contaminating particle resides in both data sets, within the given size and location tolerances. If both parameters are met, the system categorizes the particles as the same and are set forth in a data table called MATCH 93 as the locations and sizes of contaminating particles fixed between the first time and the second time (FIG. 7). The MATCH table 93 contains the wafer identifying parameters 21 , 23, 25, 27, 31 , location data 33, 35 and size data 37 for each contaminating particle. With the MATCH table 93 constructed, the 5 contaminating particles fixed on the wafer are identified and may be produced to an output set of data 15e which indicates the classification of each particle for use in analyzing the effects of wafer processing, as will be discussed in greater detail below.

Next, the system classifies each contaminating particle included in the first set 0 of data but not in the second set of data as 'removed' from the surface from a first time to a second time, indicated at 95, in the overall process flow of FIG. 2. Additionally, the system classifies each contaminating particle included in the second set of data but not in the first set of data as 'added' to the surface from the first time to the second time. Here the analysis involves comparing the MATCH 5 table 93 with either the BEF table 39 or the AFT table 41 to determine which particles 61 are added and which are removed, respectively. These comparisons are preferably performed with respect to only a particular portion of the data, as directed by the user. For instance, it is often desirable to view only those contaminating particles larger than a certain value. For instance, the preferred 0 embodiment of the present invention allows the user to restrict the query to only those particles larger than 0.12 microns (4.7 microinches), 0.16 microns (6.3 microinches), 0.20 microns (7.9 microinches) and 0.30 microns (12 microinches). As discussed previously, each of these data queries includes any of the area defects larger than 2.0 microns (79 microinches) where the particle size is expressed as an 5 area, with units of millimeters squared (inches squared), as discussed above.

For example, one query determines which contaminating particles larger than 0.12 microns (4.7 microinches) were added from the first time to the second time. This query first reviews the AFT table 41 and considers those data points having a particle size greater than 0.12 microns (4.7 microinches). Then the query subtracts o any data points remaining in the AFT table 41 that are also found in the MATCH table 93. By removing those data points that appear in the MATCH table 93 (i.e., both data sets) the query keeps those points found only in the AFT table 41 , or those added to the wafer surface. The queries for other particle sizes work similarly, limiting the AFT table 41 to a different set of particles, depending upcn particle size. Similarly, the queries for determining those particles removed from the wafer function similarly, except that the MATCH table 93 is subtracted from the BEF table 39 rather than from the AFT table 41. As with the AFT table, certain contaminating particles recorded in the BEF table 39 are removed by the query, first if they are smaller than a certain particle size threshold, and second if they also appear in the MATCH table 93. The remaining points represent those larger than a certain particle size and removed from the first time to the second time. As with the added particle queries, the removed queries preferably allow the user to restrict the query to only those particles larger than 0.12 microns (4.7 microinches), 0.16 microns (6.3 microinches), 0.20 microns (7.9 microinches) and 0.30 microns (12 microinches).

The present invention also includes several formats for displaying output sets of data 15e to the user. For instance, the output set of data may be in an output table showing a descriptor for each contaminating particle, the coordinates of each contaminating particle on the surface and the size of each contaminating particle. These tables would be similar in form to the BEF table 39 and the AFT table 41. The output set of data may also be a map of the surface indicating the locations of the contaminating particles on the surface, as will be discussed below.

Referring now to FIG. 8, the user interface of the present system contains a variety of command buttons allowing the user to choose the output format of the data. Although these data output forms represent the preferred outputs, other output sets of data are also contemplated as within the scope of the present invention. Any number of graphical, pictorial or textual output data sets may be used to display information regarding contaminating particles on the wafers.

One group of command buttons on the user interface, labeled 'Cdc >xxx μm' 101 , where "xxx" is a certain minimum particle size, run similar queries that each tabulate the average added and removed events per wafer for each week of production and plot these results. Such a plot, formed when the command button labeled Cdc > 0.12 μm is selected, is shown in FIG. 9 to comprise three charts. A first chart 111 shows added contaminating particles, a second chart 113 shows removed contaminating particles and a third chart 115 shows fixed particles. Each chart contrasts the data from the front and rear processing position within a processing tank. These positions correspond to the location of wafer carriers within a cleaning tank. The present invention should not be read as limited to the front and rear configuration disclosed. Rather, any parameters, such as wafer carrier position, cleaning parameters, wafers parameters or other environmental differences between wafer groups, may be similarly contrasted, while remaining within the scope of the present invention. These charts are helpful to a manufacturer or processor of semiconductor wafers because they offer a comparison of defects removed or added over time. With this information, the user can analyze the wafer defects at a gross level and correct problems affecting wafer contamination appropriately.

Another group of command buttons, labeled 'Maps >xxx μm' 121 , where "xxx" may be any minimum particle size, runs another set of queries which graphically depict the locations of contaminating particles on a wafer map. Each wafer map shows a different category of contaminating particles by placing a small dot on the wafer surface map at the location of each contaminating particle, as shown in FIG. 10, which depicts the wafer map displayed when the Maps > 0.12 μm button is selected. These wafer maps show the location and number of particles added, removed or fixed so that the user can easily note trends in the data that may lead to process improvements. For instance, where a cleaning step adds unwanted contaminating particles to a particular portion of the wafer surface (e.g., boat marks or contact areas 125 between the wafers and their carrier), a user could easily identify that portion of the surface due to the greater number of contaminating particles shown in that area. As discussed previously, prior art methods of reviewing particle data only compared the total number of particles between two separate times, without regard to particle location or whether those particles were removed, added or fixed. With those methods, it was difficult to correct processing problems because the user generally could not detect what was happening to the contaminating particles during cleaning. Another group of command buttons, labeled 'Last Week Maps >xxx μm' 131 , where "xxx" may be any minimum particle size, runs a query similar to the map query discussed previously, except that the data is limited to only the data recorded in the past week. These maps allow the user to view the locations of only those contaminating particles found on all examined wafers during the previous week. Because the data is preferably loaded into the system regularly, a reviewer monitoring data from the previous week can readily detect any recent trends of the contaminating particles.

Finally, one additional query tool allows the user to construct wafer maps showing added particles by prompting the user to enter which weeks of data the user would like to include and a minimum size for the included particles. The command button labeled "Customize Added Maps" 135 shown in FIG. 8 executes such a query. Once the command button is selected, the user is prompted for a time range for data review. In the preferred embodiment, the user enters a beginning week number and an ending week number, and the query limits the data reviewed to data gathered in that period. Other time units such as days or months may also be used without departing from the scope of the present invention. The user must then enter a maximum value for the particle diameter, such as 0.25 microns (9.8 microinches). The user may be required to enter similar data sets for comparison with other wafers, such as comparing those in a front or rear position in the cleaning tank as described previously. Referring now to FIG. 11 , the results of such a query are shown as two wafer maps with added particles indicated. This query button allows the user to enter various time intervals and minimum contaminating particle sizes to customize the output maps. A user may select one query, view the output data, and then request another query to view, as shown generally in FIG. 2 as 151.

Other user interface features allow for full customization of the program to a user's needs. The details of those customization options will not be included here, but would be well understood by those skilled in the relevant art. As stated previously, other software programs or hand calculations that achieve similar results are contemplated as within the scope of the present invention.

In view of the above, it will be seen that the several objects of the invention are achieved and other advantageous results attained.

When introducing elements of the present invention or the preferred embodiment(s) thereof, the articles "a", "an", "the" and "said" are intended to mean that there are one or more of the elements. The terms "comprising", "including" and "having" are intended to be inclusive and mean that there may be additional elements other than the listed elements.

As various changes could be made in the above without departing from the scope of the invention, it is intended that all matter contained in the above description and shown in the accompanying drawings shall be interpreted as illustrative and not in a limiting sense.

Claims

WHAT IS CLAIMED IS:

1. A system for classifying contaminating particles on a surface comprising: a first memory of a first set of data including the locations of contaminating particles upon a surface at a first time; a second memory of a second set of data including the locations of contaminating particles upon said surface at a second time, later than the first time; and a digital processor for: collecting and storing the first and second sets of data; comparing the locations of the contaminating particles of the first set of data with the locations of the contaminating particles of the second set of data; and classifying at least some of the contaminating particles in the first and second sets of data as a function of the comparing step.

2. The system of claim 1 wherein the classifying step further comprises classifying each contaminating particle included in both sets of data as fixed on said surface from a first time to a second time.

3. The system of claim 2 wherein the processor further generates an output set of data which indicates the classification of each particle.

4. The system of claim 3 wherein the output set of data is in the form of an output table including a descriptor for each contaminating particle, the coordinates of each contaminating particle on said surface and the size of each contaminating particle.

5. The system of claim 3 wherein the output set of data is in the form of a map of said surface indicating the locations of the contaminating particles on said surface.

6. The system of claim 3 wherein the output set of data is in the form of a chart indicating the number of contaminating particles found over a particular time period, for tracking contaminating particle trends over time.

7. The system of claim 1 wherein the classifying step further comprises classifying each contaminating particle included in the first set of data but not included in the second set of data as removed from said surface from a first time to a second time.

8. The system of claim 7 wherein the processor further generates an output set of data which indicates the classification of each particle.

9. The system of claim 8 wherein the output set of data is in the form of an output table including a descriptor for each contaminating particle, the coordinates of each contaminating particle on said surface and the size of each contaminating particle.

10. The system of claim 8 wherein the output set of data is in the form of a map of said surface indicating the locations of the contaminating particles on said surface.

11. The system of claim 8 wherein the output set of data is in the form of a chart indicating the number of contaminating particles found over a particular time period, for tracking contaminating particle trends over time.

12. The system of claim 1 wherein the classifying step further comprises classifying each contaminating particle included in the second set of data but not in the first set of data as added to said surface from a first time to a second time.

13. The system of claim 12 wherein the processor further generates an output set of data which indicates the classification of each particle.

14. The system of claim 13 wherein the output set of data is in the form of an output table including a descriptor for each contaminating particle, the coordinates of each contaminating particle on said surface and the size of each contaminating particle.

15. The system of claim 13 wherein the output set of data is in the form of a map of said surface indicating the locations of the contaminating particles on said surface.

16. The system of claim 3 wherein the output set of data is in the form of a chart indicating the number of contaminating particles found over a particular time period, for tracking contaminating particle trends over time.

17. The system of claim 1 wherein the classifying step further comprises classifying any contaminating particle included in both sets of data as fixed on said surface from a first time to a second time, classifying any contaminating particle included in the first set of data but not included in the second set of data as removed • from said surface from a first time to a second time, and classifying any contaminating particle included in the second set of data but not in the first set of data as added to said surface from a first time to a second time.

18. The system of claim 17 wherein the processor further generates an output set of data which indicates the classification of each particle.

19. The system of claim 18 wherein the output set of data is in the form of an output table including a descriptor for each contaminating particle, the coordinates of each contaminating particle on said surface and the size of each contaminating particle.

20. The system of claim 18 wherein the output set of data is in the form of a map of said surface indicating the locations of the contaminating particles on said surface.

21. The system of claim 18 wherein the output set of data is in the form of a chart indicating the number of contaminating particles found over a particular time period, for tracking contaminating particle trends over time.

22. A method for classifying contaminating particles on a surface comprising: collecting a first set of data including the locations of contaminating particles upon a surface at a first time; collecting a second set of data including the locations of contaminating particles upon said surface at a second time, later than the first time; comparing the locations of the contaminating particles of the first set of data with the locations of the contaminating particles of the second set of data; and classifying at least some of the contaminating particles in the first and second data sets of data as a function of the comparing step.

23. The method of claim 22 further comprising a processing step performed on said surface between the first time and the second time.

24. The method of claim 23 wherein the processing step further comprises cleaning said surface.

25. The method of claim 24 wherein the classifying step further comprises classifying each contaminating particle included in both sets of data as fixed on said surface from a first time to a second time.

26. The method of claim 25 wherein the first set of data further comprises a first set of digital data, the second set of data further comprises a second set of digital data, and the comparing step further comprises digitally comparing the locations of the contaminating particles of the first set of data with the locations of the contaminating particles of the second set of data.

27. The method of claim 24 wherein the classifying step further comprises classifying each contaminating particle included in the first set of data but not in the second set of data as removed from said surface from a first time to a second time.

28. The method of claim 27 wherein the first set of data further comprises a first set of digital data, the second set of data further comprises a second set of digital data, and the comparing step further comprises digitally comparing the locations of the contaminating particles of the first set of data with the locations of the contaminating particles of the second set of data.

29. The method of claim 24 wherein the classifying step further comprises classifying each contaminating particle included in the second set of data but not in the first set of data as added to said surface from a first time to a second time.

30. The method of claim 29 wherein the first set of data further comprises a first set of digital data, the second set of data further comprises a second set of digital data, and the comparing step further comprises digitally comparing the locations of the contaminating particles of the first set of data with the locations of the contaminating particles of the second set of data.

31. The method of claim 24 wherein the classifying step further comprises classifying each contaminating particle included in both sets of data as fixed on said surface from a first time to a second time, wherein it is permissible that no contaminating particles will be classified as fixed, classifying each contaminating particle included in the first set of data but not included in the second set of data as removed from said surface from a first time to a second time, wherein it is permissible that no contaminating particles will be classified as removed, and classifying each contaminating particle included in the second set of data but not in the first set of data as added to said surface from a first time to a second time, wherein it is permissible that no contaminating particles will be classified as added.

32. The method of claim 31 wherein the first set of data further comprises a first set of digital data, the second set of data further comprises a second set of digital data, and the comparing step further comprises digitally comparing the locations of the contaminating particles of the first set of data with the locations of the contaminating particles of the second set of data.

33. A system for classifying contaminating particles on a surface comprising: means for collecting a first set of data including the locations of contaminating particles upon a surface at a first time; means for collecting a second set of data including the locations of contaminating particles upon said surface at a second time, later than the first time; means for comparing the locations of the contaminating particles of the first set of data with the locations of the contaminating particles of the second set of data; and means for classifying at least some of the contaminating particles in the first and second data sets of data as a function of the comparing step.

34. The system of claim 33 wherein said means for classifying further classifies each contaminating particle included in both sets of data as fixed on said surface from a first time to a second time.

35. The system of claim 33 wherein said means for classifying further classifies each contaminating particle included in the first set of data but not in the second set of data as removed from said surface from a first time to a second time.

36. The system of claim 33 wherein said means for classifying further classifies each contaminating particle included in the second set of data but not in the first set of data as added to said surface from a first time to a second time.

37. The system of claim 33 wherein said means for classifying further classifies each contaminating particle included in both sets of data as fixed on said surface from a first time to a second time, classifies each contaminating particle included in the first set of data but not included in the second set of data as removed from said surface from a first time to a second time, and classifies each contaminating particle included in the second set of data but not in the first set of data as added to said surface from a first time to a second time.