CA2656305A1 - An automated reporting system - Google Patents
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- CA2656305A1 CA2656305A1 CA 2656305 CA2656305A CA2656305A1 CA 2656305 A1 CA2656305 A1 CA 2656305A1 CA 2656305 CA2656305 CA 2656305 CA 2656305 A CA2656305 A CA 2656305A CA 2656305 A1 CA2656305 A1 CA 2656305A1
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Abstract
An automated reporting system is disclosed which comprises means for receiving quality control/quality assurance related data on-line from a remote location, means for facilitating on-line definition by a user of report criteria for a quality control/quality assurance report based on the received data, and a report engine arranged to produce a quality control/quality assurance report according to the defined criteria and based on the received data. A corresponding method is also disclosed.
Description
AN AUTOMATED REPORTING SYSTEM
Field of the Invention The present invention relates to an automated reporting system and, in particular, to an automated reporting system for use in generating quality assurance/quality control reports from mining related data.
Background of the Invention Quality assurance/quality control reports have traditionally taken significant amounts of time to complete, are often inconsistent and in some cases include mathematically incorrect data.
Summary of the Invention In accordance with an aspect of the present invention, there is provided an automated reporting system comprising:
means for receiving quality control/quality assurance related data on-line from a remote location;
means for facilitating on-line definition by a user of report criteria for a quality control/quality assurance report based on the received data; and a report engine arranged to produce a quality control/quality assurance report according to the defined criteria and based on the received data.
In one embodiment, the quality control/quality assurance related data is assay data, and may be mining related data, laboratory related data, metallurgy related data, or any other data derived from at least one quality control/quality assurance test.
In one embodiment, the means for facilitating definition by a user of report criteria comprises a web interface accessible through the Internet. The web interface may comprise a web server.
In one embodiment, the means for receiving quality control/quality assurance related data on-line is arranged to receive quality control/quality assurance related data by email.
In one embodiment, the means for receiving quality control/quality assurance related data on-line is arranged to receive quality control/quality assurance related data through the web interface.
In one embodiment, the system further comprises a system database arranged to store quality control/quality assurance related data received from at least one client.
In addition, or alternatively, the means for receiving quality control/quality assurance related data on-line is arranged to extract quality control/quality assurance data from a client hosted database. With this embodiment, the system may further comprise a data abstraction layer arranged to directly interact with the client database.
The means for receiving quality control/quality assurance related data of this embodiment may be arranged to extract quality control/quality assurance data from a client hosted database on-the-fly based on criteria defined for a client report.
The means for facilitating definition by a user of report criteria may be arranged to facilitate selection on-line by a user of extraction criteria defining data to be included in a report.
The extraction criteria may include one or more of project name, sample taken date or sample reported date, element or compound, test type, laboratory, batch number, analytical method, blank type, standard name, field duplicate name or laboratory duplicate name.
The means for facilitating definition by a user of report criteria may be arranged to facilitate definition of an exception profile indicative of the level at which test data suggests a potential area of concern.
The exception profile may be effective for all elements and compounds included in the or each test.
The means for facilitating definition by a user of report criteria may be arranged to facilitate definition of at least one exception parameter specific to one or more element or compound and for at least one test.
In one arrangement, the system comprises at least one report procedure usable by the report engine to produce a report.
The report engine may comprise at least one report application usable to create required report content and/or present report content, such as a chart generation application and a format generator application usable to export a report in a desired format.
The system may be arranged to facilitate downloading of a report by a user.
The system may comprise a control unit arranged to control and coordinate operations in the system.
Brief Description of the Drawings The present invention will now be described, by way of example only, with reference to the accompanying drawings, in which:
Figure 1 is a schematic block diagram of an automated reporting system in accordance with an embodiment of the present invention;
Figure 2 is a diagrammatic representation of a log in screen produced by the system shown in Figure 1;
Figure 3 is a diagrammatic representation of a home page produced by the system shown in Figure 1, and showing an exception profiles box;
Figure 4 is a diagrammatic representation of a profile definition screen produced by the system shown in Figure 1;
Figure 5 is a diagrammatic representation of a compounds box produced by the system shown in Figure 1;
Figure 6 is a diagrammatic representation of an element parameters box produced by the system shown in Figure 1;
Figure 7 is a diagrammatic representation of a home page produced by the system shown in Figure 1 and showing a criteria box;
Figure 8 is a diagrammatic representation of a home page produced by the system shown in Figure 1 and showing an advanced criteria box;
Figure 9 is a diagrammatic representation of a home page produced by the system shown in Figure 1 and showing a report box;
Figure 10 is a diagrammatic representation of a report summary produced by the system shown in Figure 1;
Figure 11 is a diagrammatic representation of a home page produced by the system shown in Figure 1 and showing a quality control report;
Figure 12 is a diagrammatic representation of a sizing graph produced by the system shown in Figure 1;
Figure 13 is a diagrammatic representation of a contamination graph produced by the system shown in Figure 1;
Figure 14 is a diagrammatic representation of a standards graph produced by the system shown in Figure 1;
Figure 15 is a diagrammatic representation of a multiple elements standard graph produced by the system shown in Figure 1;
Figure 16 is a diagrammatic representation of an individual run chart produced by the system shown in Figure 1;
Figures 17 to 22 show field repeatability charts produced by the system shown in Figure 1;
Figures 23 to 25 show laboratory repeatability charts produced by the system shown in Figure 1; and Figure 26 is a schematic block diagram of an automated reporting system in accordance with an alternative embodiment of the present invention Description of an Embodiment of the Invention Referring to the drawings, in Figure 1 there is shown a schematic block diagram of an automated reporting system 10 usable on line to generate quality control/quality assurance reports based on stored data.
In this example, an embodiment is described wherein the stored data is mining related data derived from mining related tests and the reports are quality assurance/quality control (QA/QC) reports based on the mining related data. However, it will be understood that the system may also be arranged to produce QA/QC reports based on other types of data, such as metallurgy related data, laboratory related data, or any other data derived from at least one quality control/quality assurance test.
The system 10 includes a database 12 arranged to store data used to form the basis of a report, and a web interface device 14, which in this example includes a web server 15, for facilitating interaction with the system 10 by remote computing devices 16 through a communications network, in this example the Internet 18. The web interface also includes an upload application 17 arranged to facilitate uploading of QA/QC data from a user personal computing device 16.
In this example, the upload application 17 is arranged to facilitate reception of QA/QC data from a client by email, or by any suitable file transfer mechanism which may be implemented through the web interface.
It will be understood that the computing devices 16 may be any communications enabled computing device such as personal computing devices, PDAs, web enabled mobile phones, and so on.
The system 10 also includes a control unit 20 which may include a processor and associated operational software for controlling and coordinating operations in the system 10 including controlling operation of the web interface 14, controlling operation of the upload application 17, and controlling communications between the web interface 14 and the database 12.
The control unit 20 also interacts with a report engine 22 arranged to generate reports in response to instructions received from the control unit 20. The report engine 22 operates in accordance with procedures stored in a procedures database 24, the procedures defining the framework for extraction of desired data from the database 12, processing of the data so as to produce transformed data as required, and presentation of the extracted data in a report. The report engine 22 may include one or more dependent applications usable to create required report content from the extracted data and/or to create particular content presentation. In this example, the report engine 22 includes a chart generator application 26 which is executed by the report engine 22 as required to generate defined charts from the extracted data, and a format generator application 28 which may be executed to export a report in a selected format.
It will be appreciated that the database 12 may include data associated with one or multiple users, or data associated with multiple organisations such that only authorised users or authorised users associated with an organisation are permitted to access the respective data.
Hereinafter, individual users, multiple users and users associates with organizations will be referred to as "users" for ease of reference.
During use, a user desiring to create a report from data stored in the database 12 connects to the web interface 14 through the Internet 18 using a computing device 16.
After appropriate identification of the user at a log in screen 40 shown in Figure 2, for example by entering user name and password details into log in boxes 42 and clicking a log in button 44, the user is granted access to data associated with the user stored on the database 12.
In particular, a user is able to use the web interface 14 to define criteria for a desired report and to subsequently view the created report on the web interface 14.
When the report criteria have been defined, the report criteria are passed from the web interface 14 to the report engine 22 by the control unit 20 and the report engine 22, using the procedures stored in the procedures database 24, extracts the required data from the database 12 according to the report criteria. The report engine 22 then creates a report using the extracted data and using any required report application, such as the chart generator 26. The created report is then passed back to the web interface 14 through the control unit 20 and is served to the user's computing device 16 through the Internet 18 for viewing on the computing device 16.
A specific example of the system 10 during operation will now be described in relation to Figures 3 to 25 which represent screens served to a user computing device 16 by the web server 15 during use.
After successful log in using a log in screen 40 as shown in Figure 2, a home page 50 as shown in Figure 3 is served to the user's computing device 16 by the web server 15.
It will be understood that the home page 50 includes information and selection options which are specific to the user in that only data associated with the user is accessible, and user specific profiles and other user defined report specific information are displayed, as discussed in more detail below.
The home page 50 in this example is displayed using a conventional web browser and, as such, includes an address box 52 usable to enter a web page address, and navigation buttons 54 usable to navigate between web pages. The home page 50 also includes a links bar 56 on which several links 57 are disposed, the links being usable to navigate to different parts of the system.
The home page 50 also includes a report definition section 58 which is used to define profiles and criteria for a report to be created by the system 10, and in this example includes an exception profiles button 60, a criteria button 62, an advanced criteria button 64, a run/export button 66 and a notes button 68.
Activation of the exception profiles button 60, for example using a mouse, causes a profiles box 70 to be displayed as shown in Figure 2, the profiles box 70 including a profile selection drop down box 72 usable to select from one or more existing predefined profiles.
Selection of a predefined profile causes profile parameters 74 to be displayed.
The report profile parameters displayed in the profiles box 70 define boundary limits for report data indicative of the level at which a particular test indicates an exception, that is, test results which indicate a potential area of concern.
In the present example, the data stored in the database relates to the following tests:
i) a sizing test usable to determine the efficiency of particle size reduction processes and whether the process conforms to specification;
ii) a contamination test usable to test for contamination introduced between taking the sample and carrying out analysis. Blanks may be introduced into the laboratory either as coarse material that will require sample preparation, or as a pulp that will require digestion and analysis;
iii) an accuracy test useable to determine the accuracy of a particular laboratory over time in detecting an analyte by using one or more standards wherein the amount of an analyte present in the standard is known;
iv) a field repeatability test usable to determine process sampling precision by comparing original and duplicate samples;
v) a laboratory repeatability test usable to determine the sampling precision of a laboratory by comparing results obtained at the laboratory from original and duplicate samples.
An exception profile may be modified and new profiles may be added by activating an open button 80, which causes a profile definition screen 82 as shown in Figure 4 to be displayed. The profile definition screen 82 includes an element selection box 84 usable to select elements to be included in the exception profile and thereby made available for selection in a report created based on the exception profile. In this example, selected elements 86, elements available for selection 88 and elements not available for selection 90 are represented differently so that they are distinguishable from each other by a user.
An exception profile which is applicable for all selected elements in the profile is definable using a profile parameters box 92 which permits selection of an exception parameter for each available test.
In this example, the exception parameters include a sizing parameter 94 which defines the percentage amount of particles passing a maximum size limit, such as 2mm for coarse crush particles and 75pm for pulp; a standards parameter 96 which defines an exception limit based on a percentage deviation from an expected value or based on a specific number multiple of standard deviations from the expected value; a field repeatability parameter 98 which defines a percentage relative difference between duplicate samples, or is based on an expected relative error model;
a laboratory repeatability parameter 100 which defines either a specific number multiple of the analytical detection limit, a percentage relative difference between duplicate samples, or defines an expected relative error model; a blank parameter 102 which relates to a contamination test and defines a maximum limit based on a specific number multiple of an analytical detection limit or based on an absolute value. A profile name may be defined using a profile name box 108.
If an element is selected having compounds associated with it, clicking on the element will cause a compounds box 110 as shown in Figure 5 to be displayed. Using the compounds box 110, a user is able to select an element and/or one or more compounds including the element to be included in the profile by marking check boxes 112.
It will be understood that the profile definition screen 82 is used to define exception profiles to apply to all elements and compounds in a report. However, exception parameters specific to one or more elements or compounds io may alternatively be defined by activating an individual analyte button 114. This causes an element parameters box 116 as shown in Figure 6 to be displayed.
The element parameters box 116 enables the type of test model for use in a particular test to be selected and also enables individual exception parameters to be selected for each element using parameter selection boxes 120.
In the present example, the models available for the contamination test are based on a specific number multiple of the analytical detection limit (x DL) or based on an absolute value (Abs Val), the models available for the accuracy test are based on an exception limit for a percentage deviation from an expected value (%EV) or based on a specific number multiple of standard deviations from an expected value (SD), the models available for the field repeatability test are based on a percentage relative difference between duplicate samples (%RD), or based on an expected relative error model (%RE), and the models available for the laboratory repeatability test are based on a percentage relative difference between duplicate samples (%RD), or based on an expected relative error model (%RE).
Selection of the criteria button 62 causes a criteria box 122 as shown in Figure 7 to be displayed. The criteria box 122 is usable to define the data to be included in the report and, for this purpose, a project selection box 124 is provided so as to allow a user to include data in the report from all projects associated with the user or select particular projects associated with the user, a date range usable to restrict data in the report based on dates reported or dates sampled and a specified date range using date selection fields 126, an elements selection box 128 usable to select one or more elements to be included in the report, and a report sections drop down box 130 usable to select the report sections to be included in the report, each report section in this example relating to a particular test.
Selection of the advanced criteria button 64 causes an advanced criteria box 140 as shown in Figure 8 to be displayed, the advanced criteria box 140 including advanced criteria buttons 142 usable to define the data to be included in the report with more granularity.
The system may also enable a user to select an appropriate scale for plots, charts, and so on, created by the system so that the report data is represented in a more meaningful way.
Selection of the run/export buttons 66 causes a report box 150 as shown in Figure 9 to be displayed. The report box 150 includes a summary button 152, a view report button 154, an export type drop down box 156, an export report button 158, and an extract data button 160.
Activation of the summary button 152 causes a report summary 170 as shown in Figure 10 to be displayed. The report summary 170 provides an indication of the projects to be included in the report, and the amount of data to be included for the selected tests. This allows a user to obtain an indication of the nature and size of a report before the report is initiated, and in particular of the type and quantum of QC data associated with the report.
Activation of the view report button 154 causes the control unit 20 to send a communication to the report engine 22 to extract data from the database 12 according to the report criteria defined using the criteria box 122 and the advanced criteria box 140, and to create a report according to report creation procedures defined in the procedures database 24 and including exception profiles defined by the selected exception profile.
Using the extract data button 160, a user is able to extract raw data from the system.
As shown in Figure 11, the created report 180 is displayed in a report window 181 and the report may be navigated using report navigation icons 182 and report navigation buttons 184. Each of the report navigation icons 182 includes a heading 186 representing a section of the report, and, in particular, each test included in the report has an associated heading. Each heading may be expanded so as to provide sub-headings which may be used to navigate to specific sub-sections of the report.
The results 190 of an exemplary sizing test represented in bar chart form are shown in Figure 12. In this example, the test relates to pulp, the selected exception parameter, that is the percentage of pulp passing a given sieve size, is 90%, and the sieve size is 75pm. The exception parameter is represented by horizontal exception line 192. As can be seen, in this example 29.79% of samples fail the test, although the graph shows an improvement in pulverizing performance over time.
The section of the report relating to contamination is organized by blank type (coarse or pulp), laboratory analytical method, and analyte combination. The results 196 of a contamination test represented in bar chart form are shown in Figure 13. In this example, the test relates to 17 samples analysed by Lab 1 in relation to element Au and method FA. The selected exception parameter is 10 times the detection limit and is represented by horizontal exception line 198. In this test, no samples exceed the exception line 198 and, accordingly, no samples fail the test.
The section of the report relating to accuracy is divided into two summary sections, multiple standards per laboratory, element and method, and multiple elements per standard, lab and method.
The results of an accuracy test are shown in a standards graph 200 shown in Figure 14. The standards graph 200 represents all standards for a laboratory analysed for the same analyte by the same method. In this example, the test relates to three standards analysed by Lab 1 for element Fe using method XRF1. The standards graph includes guide lines 202 at +/- 10% deviation from an expected value and guide lines 204 at +/- 20% deviation from an expected value. The average of the percent relative difference between analytical values and the expected value for each standard in a batch is calculated and plotted against the batch in batch submission order.
It will be understood. that the chart provides a display of the variability of laboratory over time for a single element for multiple standards, and any bias affecting the whole grade range, or a specific standard or grade range will be apparent.
An alternative standards graph 210 showing the results of an accuracy test is shown in Figure 15. The standards graph 210 represents multiple analytes for a standard, laboratory and method using box and whisker plots 212.
Field of the Invention The present invention relates to an automated reporting system and, in particular, to an automated reporting system for use in generating quality assurance/quality control reports from mining related data.
Background of the Invention Quality assurance/quality control reports have traditionally taken significant amounts of time to complete, are often inconsistent and in some cases include mathematically incorrect data.
Summary of the Invention In accordance with an aspect of the present invention, there is provided an automated reporting system comprising:
means for receiving quality control/quality assurance related data on-line from a remote location;
means for facilitating on-line definition by a user of report criteria for a quality control/quality assurance report based on the received data; and a report engine arranged to produce a quality control/quality assurance report according to the defined criteria and based on the received data.
In one embodiment, the quality control/quality assurance related data is assay data, and may be mining related data, laboratory related data, metallurgy related data, or any other data derived from at least one quality control/quality assurance test.
In one embodiment, the means for facilitating definition by a user of report criteria comprises a web interface accessible through the Internet. The web interface may comprise a web server.
In one embodiment, the means for receiving quality control/quality assurance related data on-line is arranged to receive quality control/quality assurance related data by email.
In one embodiment, the means for receiving quality control/quality assurance related data on-line is arranged to receive quality control/quality assurance related data through the web interface.
In one embodiment, the system further comprises a system database arranged to store quality control/quality assurance related data received from at least one client.
In addition, or alternatively, the means for receiving quality control/quality assurance related data on-line is arranged to extract quality control/quality assurance data from a client hosted database. With this embodiment, the system may further comprise a data abstraction layer arranged to directly interact with the client database.
The means for receiving quality control/quality assurance related data of this embodiment may be arranged to extract quality control/quality assurance data from a client hosted database on-the-fly based on criteria defined for a client report.
The means for facilitating definition by a user of report criteria may be arranged to facilitate selection on-line by a user of extraction criteria defining data to be included in a report.
The extraction criteria may include one or more of project name, sample taken date or sample reported date, element or compound, test type, laboratory, batch number, analytical method, blank type, standard name, field duplicate name or laboratory duplicate name.
The means for facilitating definition by a user of report criteria may be arranged to facilitate definition of an exception profile indicative of the level at which test data suggests a potential area of concern.
The exception profile may be effective for all elements and compounds included in the or each test.
The means for facilitating definition by a user of report criteria may be arranged to facilitate definition of at least one exception parameter specific to one or more element or compound and for at least one test.
In one arrangement, the system comprises at least one report procedure usable by the report engine to produce a report.
The report engine may comprise at least one report application usable to create required report content and/or present report content, such as a chart generation application and a format generator application usable to export a report in a desired format.
The system may be arranged to facilitate downloading of a report by a user.
The system may comprise a control unit arranged to control and coordinate operations in the system.
Brief Description of the Drawings The present invention will now be described, by way of example only, with reference to the accompanying drawings, in which:
Figure 1 is a schematic block diagram of an automated reporting system in accordance with an embodiment of the present invention;
Figure 2 is a diagrammatic representation of a log in screen produced by the system shown in Figure 1;
Figure 3 is a diagrammatic representation of a home page produced by the system shown in Figure 1, and showing an exception profiles box;
Figure 4 is a diagrammatic representation of a profile definition screen produced by the system shown in Figure 1;
Figure 5 is a diagrammatic representation of a compounds box produced by the system shown in Figure 1;
Figure 6 is a diagrammatic representation of an element parameters box produced by the system shown in Figure 1;
Figure 7 is a diagrammatic representation of a home page produced by the system shown in Figure 1 and showing a criteria box;
Figure 8 is a diagrammatic representation of a home page produced by the system shown in Figure 1 and showing an advanced criteria box;
Figure 9 is a diagrammatic representation of a home page produced by the system shown in Figure 1 and showing a report box;
Figure 10 is a diagrammatic representation of a report summary produced by the system shown in Figure 1;
Figure 11 is a diagrammatic representation of a home page produced by the system shown in Figure 1 and showing a quality control report;
Figure 12 is a diagrammatic representation of a sizing graph produced by the system shown in Figure 1;
Figure 13 is a diagrammatic representation of a contamination graph produced by the system shown in Figure 1;
Figure 14 is a diagrammatic representation of a standards graph produced by the system shown in Figure 1;
Figure 15 is a diagrammatic representation of a multiple elements standard graph produced by the system shown in Figure 1;
Figure 16 is a diagrammatic representation of an individual run chart produced by the system shown in Figure 1;
Figures 17 to 22 show field repeatability charts produced by the system shown in Figure 1;
Figures 23 to 25 show laboratory repeatability charts produced by the system shown in Figure 1; and Figure 26 is a schematic block diagram of an automated reporting system in accordance with an alternative embodiment of the present invention Description of an Embodiment of the Invention Referring to the drawings, in Figure 1 there is shown a schematic block diagram of an automated reporting system 10 usable on line to generate quality control/quality assurance reports based on stored data.
In this example, an embodiment is described wherein the stored data is mining related data derived from mining related tests and the reports are quality assurance/quality control (QA/QC) reports based on the mining related data. However, it will be understood that the system may also be arranged to produce QA/QC reports based on other types of data, such as metallurgy related data, laboratory related data, or any other data derived from at least one quality control/quality assurance test.
The system 10 includes a database 12 arranged to store data used to form the basis of a report, and a web interface device 14, which in this example includes a web server 15, for facilitating interaction with the system 10 by remote computing devices 16 through a communications network, in this example the Internet 18. The web interface also includes an upload application 17 arranged to facilitate uploading of QA/QC data from a user personal computing device 16.
In this example, the upload application 17 is arranged to facilitate reception of QA/QC data from a client by email, or by any suitable file transfer mechanism which may be implemented through the web interface.
It will be understood that the computing devices 16 may be any communications enabled computing device such as personal computing devices, PDAs, web enabled mobile phones, and so on.
The system 10 also includes a control unit 20 which may include a processor and associated operational software for controlling and coordinating operations in the system 10 including controlling operation of the web interface 14, controlling operation of the upload application 17, and controlling communications between the web interface 14 and the database 12.
The control unit 20 also interacts with a report engine 22 arranged to generate reports in response to instructions received from the control unit 20. The report engine 22 operates in accordance with procedures stored in a procedures database 24, the procedures defining the framework for extraction of desired data from the database 12, processing of the data so as to produce transformed data as required, and presentation of the extracted data in a report. The report engine 22 may include one or more dependent applications usable to create required report content from the extracted data and/or to create particular content presentation. In this example, the report engine 22 includes a chart generator application 26 which is executed by the report engine 22 as required to generate defined charts from the extracted data, and a format generator application 28 which may be executed to export a report in a selected format.
It will be appreciated that the database 12 may include data associated with one or multiple users, or data associated with multiple organisations such that only authorised users or authorised users associated with an organisation are permitted to access the respective data.
Hereinafter, individual users, multiple users and users associates with organizations will be referred to as "users" for ease of reference.
During use, a user desiring to create a report from data stored in the database 12 connects to the web interface 14 through the Internet 18 using a computing device 16.
After appropriate identification of the user at a log in screen 40 shown in Figure 2, for example by entering user name and password details into log in boxes 42 and clicking a log in button 44, the user is granted access to data associated with the user stored on the database 12.
In particular, a user is able to use the web interface 14 to define criteria for a desired report and to subsequently view the created report on the web interface 14.
When the report criteria have been defined, the report criteria are passed from the web interface 14 to the report engine 22 by the control unit 20 and the report engine 22, using the procedures stored in the procedures database 24, extracts the required data from the database 12 according to the report criteria. The report engine 22 then creates a report using the extracted data and using any required report application, such as the chart generator 26. The created report is then passed back to the web interface 14 through the control unit 20 and is served to the user's computing device 16 through the Internet 18 for viewing on the computing device 16.
A specific example of the system 10 during operation will now be described in relation to Figures 3 to 25 which represent screens served to a user computing device 16 by the web server 15 during use.
After successful log in using a log in screen 40 as shown in Figure 2, a home page 50 as shown in Figure 3 is served to the user's computing device 16 by the web server 15.
It will be understood that the home page 50 includes information and selection options which are specific to the user in that only data associated with the user is accessible, and user specific profiles and other user defined report specific information are displayed, as discussed in more detail below.
The home page 50 in this example is displayed using a conventional web browser and, as such, includes an address box 52 usable to enter a web page address, and navigation buttons 54 usable to navigate between web pages. The home page 50 also includes a links bar 56 on which several links 57 are disposed, the links being usable to navigate to different parts of the system.
The home page 50 also includes a report definition section 58 which is used to define profiles and criteria for a report to be created by the system 10, and in this example includes an exception profiles button 60, a criteria button 62, an advanced criteria button 64, a run/export button 66 and a notes button 68.
Activation of the exception profiles button 60, for example using a mouse, causes a profiles box 70 to be displayed as shown in Figure 2, the profiles box 70 including a profile selection drop down box 72 usable to select from one or more existing predefined profiles.
Selection of a predefined profile causes profile parameters 74 to be displayed.
The report profile parameters displayed in the profiles box 70 define boundary limits for report data indicative of the level at which a particular test indicates an exception, that is, test results which indicate a potential area of concern.
In the present example, the data stored in the database relates to the following tests:
i) a sizing test usable to determine the efficiency of particle size reduction processes and whether the process conforms to specification;
ii) a contamination test usable to test for contamination introduced between taking the sample and carrying out analysis. Blanks may be introduced into the laboratory either as coarse material that will require sample preparation, or as a pulp that will require digestion and analysis;
iii) an accuracy test useable to determine the accuracy of a particular laboratory over time in detecting an analyte by using one or more standards wherein the amount of an analyte present in the standard is known;
iv) a field repeatability test usable to determine process sampling precision by comparing original and duplicate samples;
v) a laboratory repeatability test usable to determine the sampling precision of a laboratory by comparing results obtained at the laboratory from original and duplicate samples.
An exception profile may be modified and new profiles may be added by activating an open button 80, which causes a profile definition screen 82 as shown in Figure 4 to be displayed. The profile definition screen 82 includes an element selection box 84 usable to select elements to be included in the exception profile and thereby made available for selection in a report created based on the exception profile. In this example, selected elements 86, elements available for selection 88 and elements not available for selection 90 are represented differently so that they are distinguishable from each other by a user.
An exception profile which is applicable for all selected elements in the profile is definable using a profile parameters box 92 which permits selection of an exception parameter for each available test.
In this example, the exception parameters include a sizing parameter 94 which defines the percentage amount of particles passing a maximum size limit, such as 2mm for coarse crush particles and 75pm for pulp; a standards parameter 96 which defines an exception limit based on a percentage deviation from an expected value or based on a specific number multiple of standard deviations from the expected value; a field repeatability parameter 98 which defines a percentage relative difference between duplicate samples, or is based on an expected relative error model;
a laboratory repeatability parameter 100 which defines either a specific number multiple of the analytical detection limit, a percentage relative difference between duplicate samples, or defines an expected relative error model; a blank parameter 102 which relates to a contamination test and defines a maximum limit based on a specific number multiple of an analytical detection limit or based on an absolute value. A profile name may be defined using a profile name box 108.
If an element is selected having compounds associated with it, clicking on the element will cause a compounds box 110 as shown in Figure 5 to be displayed. Using the compounds box 110, a user is able to select an element and/or one or more compounds including the element to be included in the profile by marking check boxes 112.
It will be understood that the profile definition screen 82 is used to define exception profiles to apply to all elements and compounds in a report. However, exception parameters specific to one or more elements or compounds io may alternatively be defined by activating an individual analyte button 114. This causes an element parameters box 116 as shown in Figure 6 to be displayed.
The element parameters box 116 enables the type of test model for use in a particular test to be selected and also enables individual exception parameters to be selected for each element using parameter selection boxes 120.
In the present example, the models available for the contamination test are based on a specific number multiple of the analytical detection limit (x DL) or based on an absolute value (Abs Val), the models available for the accuracy test are based on an exception limit for a percentage deviation from an expected value (%EV) or based on a specific number multiple of standard deviations from an expected value (SD), the models available for the field repeatability test are based on a percentage relative difference between duplicate samples (%RD), or based on an expected relative error model (%RE), and the models available for the laboratory repeatability test are based on a percentage relative difference between duplicate samples (%RD), or based on an expected relative error model (%RE).
Selection of the criteria button 62 causes a criteria box 122 as shown in Figure 7 to be displayed. The criteria box 122 is usable to define the data to be included in the report and, for this purpose, a project selection box 124 is provided so as to allow a user to include data in the report from all projects associated with the user or select particular projects associated with the user, a date range usable to restrict data in the report based on dates reported or dates sampled and a specified date range using date selection fields 126, an elements selection box 128 usable to select one or more elements to be included in the report, and a report sections drop down box 130 usable to select the report sections to be included in the report, each report section in this example relating to a particular test.
Selection of the advanced criteria button 64 causes an advanced criteria box 140 as shown in Figure 8 to be displayed, the advanced criteria box 140 including advanced criteria buttons 142 usable to define the data to be included in the report with more granularity.
The system may also enable a user to select an appropriate scale for plots, charts, and so on, created by the system so that the report data is represented in a more meaningful way.
Selection of the run/export buttons 66 causes a report box 150 as shown in Figure 9 to be displayed. The report box 150 includes a summary button 152, a view report button 154, an export type drop down box 156, an export report button 158, and an extract data button 160.
Activation of the summary button 152 causes a report summary 170 as shown in Figure 10 to be displayed. The report summary 170 provides an indication of the projects to be included in the report, and the amount of data to be included for the selected tests. This allows a user to obtain an indication of the nature and size of a report before the report is initiated, and in particular of the type and quantum of QC data associated with the report.
Activation of the view report button 154 causes the control unit 20 to send a communication to the report engine 22 to extract data from the database 12 according to the report criteria defined using the criteria box 122 and the advanced criteria box 140, and to create a report according to report creation procedures defined in the procedures database 24 and including exception profiles defined by the selected exception profile.
Using the extract data button 160, a user is able to extract raw data from the system.
As shown in Figure 11, the created report 180 is displayed in a report window 181 and the report may be navigated using report navigation icons 182 and report navigation buttons 184. Each of the report navigation icons 182 includes a heading 186 representing a section of the report, and, in particular, each test included in the report has an associated heading. Each heading may be expanded so as to provide sub-headings which may be used to navigate to specific sub-sections of the report.
The results 190 of an exemplary sizing test represented in bar chart form are shown in Figure 12. In this example, the test relates to pulp, the selected exception parameter, that is the percentage of pulp passing a given sieve size, is 90%, and the sieve size is 75pm. The exception parameter is represented by horizontal exception line 192. As can be seen, in this example 29.79% of samples fail the test, although the graph shows an improvement in pulverizing performance over time.
The section of the report relating to contamination is organized by blank type (coarse or pulp), laboratory analytical method, and analyte combination. The results 196 of a contamination test represented in bar chart form are shown in Figure 13. In this example, the test relates to 17 samples analysed by Lab 1 in relation to element Au and method FA. The selected exception parameter is 10 times the detection limit and is represented by horizontal exception line 198. In this test, no samples exceed the exception line 198 and, accordingly, no samples fail the test.
The section of the report relating to accuracy is divided into two summary sections, multiple standards per laboratory, element and method, and multiple elements per standard, lab and method.
The results of an accuracy test are shown in a standards graph 200 shown in Figure 14. The standards graph 200 represents all standards for a laboratory analysed for the same analyte by the same method. In this example, the test relates to three standards analysed by Lab 1 for element Fe using method XRF1. The standards graph includes guide lines 202 at +/- 10% deviation from an expected value and guide lines 204 at +/- 20% deviation from an expected value. The average of the percent relative difference between analytical values and the expected value for each standard in a batch is calculated and plotted against the batch in batch submission order.
It will be understood. that the chart provides a display of the variability of laboratory over time for a single element for multiple standards, and any bias affecting the whole grade range, or a specific standard or grade range will be apparent.
An alternative standards graph 210 showing the results of an accuracy test is shown in Figure 15. The standards graph 210 represents multiple analytes for a standard, laboratory and method using box and whisker plots 212.
Each box and whisker plot 212 represents a highest value 214, a lowest value 216, an average value 218, a median value 220, and upper 222 and lower 224 boundaries of 50%
of the results.
It will be understood that the chart provides a snapshot of the performance of all of the selected analytes in a particular standard or laboratory method combination.
An individual run chart 230 showing a temporal plot of analytical results of an element for a particular standard is shown in Figure 16. The charts are grouped by laboratory, standard, method and element, with each combination shown on a separate plot. Each run chart 230 also includes a 3-point moving average 232, an expected value line 234, and standard deviation lines 236.
Also shown in Figure 16 is a table 238 which displays the plotted data average bias %CV, plot % bias, plot %CV and the % of values outside the control limits.
In the present example shown in Figure 16, the standard is STDO1, the laboratory is Lab 1, the method is FA and the element is Au.
The section of the report relating to precision is organized into two categories - field repeatability and laboratory repeatability, with sub-categories for each duplicate type (such as blasthole duplicates, RC
duplicates and soil duplicates), element and method.
The results of a field repeatability test are shown in a linear original vs duplicate scatter chart 240 using a linear/linear scale and a log scatter chart 242 using a log/log scale in Figure 17. Guide lines 246 are shown at -20%, -10%, 0%, +10% and +20% which presents as lines with a slope of 0.8, 0.9, 1, 1.1 and 1.2 on the linear/linear chart and parallel lines on the log/log plot.
The field repeatability test results may also be represented using linear/linear 250 and linear/log 252 %
relative difference vs mean concentration plots as shown in Figure 18. The plots 250, 252 display the % difference of an original value derived from a first sample and a duplicate value from a duplicate sample. Guide lines are drawn at -20%, -10%, 0, +10% and +20%. These plots will show whether there is an analytical bias, as it would be expected that there are approximately the same number of points above and below the zero line.
The field repeatability test results may also be represented using plots 260 of calculated coefficient of variation (CV%) versus the order in which the samples were analysed as shown in Figure 19. This plot shows a time plot of analytical performance.
An error model plot 270 as shown in Figure 20 may also be produced. The error model plot 270 displays the calculated CV% versus the ranking % of the CV% sorted in ascending order. A table 272 is also displayed showing the number of pairs available after filtering for data close to the detection limit or above a specified absolute value and the associated calculated RMS CV% and robust CV%. The curved lines 274 represent the pattern that the CVs should make if the analytical data conforms respectively to 1, 2, 5, 10, 20, 30, 40 or 50 % relative error, assuming normally distributed errors.
For the field repeatability test, a user is able to define, on an element by element basis, an exception limit based on a multiple of the analytical detection limit, or based on a percent relative difference or an expected relative error model.
of the results.
It will be understood that the chart provides a snapshot of the performance of all of the selected analytes in a particular standard or laboratory method combination.
An individual run chart 230 showing a temporal plot of analytical results of an element for a particular standard is shown in Figure 16. The charts are grouped by laboratory, standard, method and element, with each combination shown on a separate plot. Each run chart 230 also includes a 3-point moving average 232, an expected value line 234, and standard deviation lines 236.
Also shown in Figure 16 is a table 238 which displays the plotted data average bias %CV, plot % bias, plot %CV and the % of values outside the control limits.
In the present example shown in Figure 16, the standard is STDO1, the laboratory is Lab 1, the method is FA and the element is Au.
The section of the report relating to precision is organized into two categories - field repeatability and laboratory repeatability, with sub-categories for each duplicate type (such as blasthole duplicates, RC
duplicates and soil duplicates), element and method.
The results of a field repeatability test are shown in a linear original vs duplicate scatter chart 240 using a linear/linear scale and a log scatter chart 242 using a log/log scale in Figure 17. Guide lines 246 are shown at -20%, -10%, 0%, +10% and +20% which presents as lines with a slope of 0.8, 0.9, 1, 1.1 and 1.2 on the linear/linear chart and parallel lines on the log/log plot.
The field repeatability test results may also be represented using linear/linear 250 and linear/log 252 %
relative difference vs mean concentration plots as shown in Figure 18. The plots 250, 252 display the % difference of an original value derived from a first sample and a duplicate value from a duplicate sample. Guide lines are drawn at -20%, -10%, 0, +10% and +20%. These plots will show whether there is an analytical bias, as it would be expected that there are approximately the same number of points above and below the zero line.
The field repeatability test results may also be represented using plots 260 of calculated coefficient of variation (CV%) versus the order in which the samples were analysed as shown in Figure 19. This plot shows a time plot of analytical performance.
An error model plot 270 as shown in Figure 20 may also be produced. The error model plot 270 displays the calculated CV% versus the ranking % of the CV% sorted in ascending order. A table 272 is also displayed showing the number of pairs available after filtering for data close to the detection limit or above a specified absolute value and the associated calculated RMS CV% and robust CV%. The curved lines 274 represent the pattern that the CVs should make if the analytical data conforms respectively to 1, 2, 5, 10, 20, 30, 40 or 50 % relative error, assuming normally distributed errors.
For the field repeatability test, a user is able to define, on an element by element basis, an exception limit based on a multiple of the analytical detection limit, or based on a percent relative difference or an expected relative error model.
An exception model plot 280 for a lower cut value and based on a percent relative difference is shown in Figure 21. The plot 280 shows exception zones 282 defined by exception parameters of 10 x the detection limit (10xDL) represented by vertical exception line 284 and 20%
relative difference represented by horizontal exception lines 286.
An exception model plot 290 for a lower cut value and based on an expected relative error model is shown in Figure 22. The plot 290 shows a control line 292 below which 90% of the plotted CV values would be expected to occur given a 1 standard deviation relative error model of o.
The results of a lab repeatability test are shown in a linear original vs duplicate scatter chart 300 using a linear/linear scale and a log scatter chart 302 using a log/log scale in Figure 23. Guide lines 304 are shown at -10%, -5%, 0%, +5%, and +10% which presents as lines with a slope of 0.8, 0.9, 1, 1.1 and 1.2 on the linear/linear chart and parallel lines on the log/log plot. Laboratory repeatability is different to field repeatability because sub-sampling is done after a particle size reduction and, in general, the sampling errors between duplicates are much reduced relative to the sampling errors obtained for field repeatability.
The lab repeatability test results may also be represented using linear/linear 310 and linear/log 312 % relative difference vs mean concentration plots as shown in Figure 24. The plots 310, 312 display an original value derived from a first sample and a duplicate value from a duplicate sample. Guide lines are drawn at -20%, -10%, 0, +10% and +20%. These plots will show whether there is an analytical bias, as it would be expected that there are approximately the same number of points above and below the zero line.
The lab repeatability test results may also be represented using plots 320 of calculated coefficient of variation (CV%) versus the order in which the samples were analysed as shown in Figure 25. This plot shows a time plot of analytical performance.
Error model plots and exception model plot of the type shown in Figures 20 and 21 in relation to field repeatability may also be produced for lab repeatability.
The system is arranged to group lab repeatability results by laboratory and, using the expandable headings 186 in the report 180, a user is able to view results specific to a particular laboratory.
It will be appreciated that the present system allows a user to quickly obtain a customized accurate and reproducible QA/QC report based on received QA/QC data and to obtain the report on-line from a remote location.
Since all processing is carried out at a central location remote from the users, for example by operators of the system, the users are required only to have on-line access to the system, for example through the Internet, in order to obtain the reports.
It will also be appreciated that the system enables a user to obtain an automatically structured report, wherein the structure is determined and modified according to the type of data to be included in the report. In addition, by defining user selectable and modifiable pre-defined exception profiles, the system also ensures that the exception profiles applied to the data are consistent. In this way, the format and content of the report is consistent and reproducible.
relative difference represented by horizontal exception lines 286.
An exception model plot 290 for a lower cut value and based on an expected relative error model is shown in Figure 22. The plot 290 shows a control line 292 below which 90% of the plotted CV values would be expected to occur given a 1 standard deviation relative error model of o.
The results of a lab repeatability test are shown in a linear original vs duplicate scatter chart 300 using a linear/linear scale and a log scatter chart 302 using a log/log scale in Figure 23. Guide lines 304 are shown at -10%, -5%, 0%, +5%, and +10% which presents as lines with a slope of 0.8, 0.9, 1, 1.1 and 1.2 on the linear/linear chart and parallel lines on the log/log plot. Laboratory repeatability is different to field repeatability because sub-sampling is done after a particle size reduction and, in general, the sampling errors between duplicates are much reduced relative to the sampling errors obtained for field repeatability.
The lab repeatability test results may also be represented using linear/linear 310 and linear/log 312 % relative difference vs mean concentration plots as shown in Figure 24. The plots 310, 312 display an original value derived from a first sample and a duplicate value from a duplicate sample. Guide lines are drawn at -20%, -10%, 0, +10% and +20%. These plots will show whether there is an analytical bias, as it would be expected that there are approximately the same number of points above and below the zero line.
The lab repeatability test results may also be represented using plots 320 of calculated coefficient of variation (CV%) versus the order in which the samples were analysed as shown in Figure 25. This plot shows a time plot of analytical performance.
Error model plots and exception model plot of the type shown in Figures 20 and 21 in relation to field repeatability may also be produced for lab repeatability.
The system is arranged to group lab repeatability results by laboratory and, using the expandable headings 186 in the report 180, a user is able to view results specific to a particular laboratory.
It will be appreciated that the present system allows a user to quickly obtain a customized accurate and reproducible QA/QC report based on received QA/QC data and to obtain the report on-line from a remote location.
Since all processing is carried out at a central location remote from the users, for example by operators of the system, the users are required only to have on-line access to the system, for example through the Internet, in order to obtain the reports.
It will also be appreciated that the system enables a user to obtain an automatically structured report, wherein the structure is determined and modified according to the type of data to be included in the report. In addition, by defining user selectable and modifiable pre-defined exception profiles, the system also ensures that the exception profiles applied to the data are consistent. In this way, the format and content of the report is consistent and reproducible.
It will also be appreciated that the data which forms the basis of a report is stored in one location only, which ensures that reports created based on the stored data are consistent and reproducible.
In a variation of the above embodiment, instead of facilitating reception of quality control/quality assurance data from a client, for example by enabling a client to send data to the system using the web interface, the system may be configured to retrieve quality control/quality assurance data from a client database in response to a request by a user such as in response to definition by a user of report criteria, automatically based on predefined criteria, or in any other way. The retrieved data may be stored in the database 12 for subsequent use in generating one or more reports, or the quality control/quality assurance data may be retrieved directly from a client database when required by the report engine 22.
An example of an alternative automated reporting system 400 is shown in Figure 26. Like and similar features are indicated with like reference numerals.
The system 400 comprises a data abstraction layer 404 arranged to communicate directly with a client database 406 in order to retrieve quality control/quality assurance data from the client database 406 when the data is required during report creation.
It will be appreciated that with this embodiment the client database 406 is hosted by a client and, as such, the quality control/quality assurance data stored in the client 406 database is under the client's control.
During use, a user associated with a client desiring to create a report from data stored in the client database 12 connects to the web interface 14 through the Internet 18 using a computing device 16 remotely located relative to the client, or using a client computing device 410 at the same location as the client database 406. After appropriate identification of the user at a log in screen 40 shown in Figure 2, the user is granted access to the system 400 and is able to view high level information relating to projects associated with the client. The project information is stored at the client database 406 and is retrieved from the client database after user login has occurred. Using the web interface 14, the user is able to select one or more of the client projects which are to form the basis of a report.
As with the previous embodiment described in relation to Figures 1 to 25, a user is able to use the web interface 14 to define criteria for the desired report and to subsequently view the created report on the web interface 14.
With the present embodiment, when the report criteria have been defined, the report engine 22 instructs the data abstraction layer 404 to retrieve from the client database 406 data which is required in order to generate the desired report according to the defined report criteria, and the data abstraction layer interacts directly with the client database 406 over the Internet 18 and extracts the required data from the client database 406. In order to facilitate interaction with the client database, a network interface 408 is provided.
It will be understood that the report criteria may be defined using a computing device 16 disposed at a location remote from the client database 406, or using a client computing device 410 disposed locally.
The data abstraction layer 404 may have an associated database 412 for temporarily storing data as the data is extracted from the client database 406.
The report engine 22 then creates a report using the extracted data and using any required report application, such as the chart generator 26. The created report is then passed back to the web interface 14 through the control unit 20 and is served to the user's computing device 16 through the Internet 18 for viewing on the computing device 16.
It will be appreciated that with this embodiment quality control/quality assurance data for each client is stored by the client and data required by the system to create a report is extracted from the client database when required. In this way, it is not necessary for the system to include a database for storing client data. Moreover, since the client database 406 is queried directly by the data abstraction layer 404, compatibility issues between client data and system database requirements are minimized.
In the claims which follow and in the preceding description of the invention, except where the context requires otherwise due to express language or necessary implication, the word "comprise" or variations such as "comprises" or "comprising" is used in an inclusive sense, i.e. to specify the presence of the stated features but not to preclude the presence or addition of further features in various embodiments of the invention.
It is to be understood that, if any prior art publication is referred to herein, such reference does not constitute an admission that the publication forms a part of the common general knowledge in the art, in Australia or any other country.
In a variation of the above embodiment, instead of facilitating reception of quality control/quality assurance data from a client, for example by enabling a client to send data to the system using the web interface, the system may be configured to retrieve quality control/quality assurance data from a client database in response to a request by a user such as in response to definition by a user of report criteria, automatically based on predefined criteria, or in any other way. The retrieved data may be stored in the database 12 for subsequent use in generating one or more reports, or the quality control/quality assurance data may be retrieved directly from a client database when required by the report engine 22.
An example of an alternative automated reporting system 400 is shown in Figure 26. Like and similar features are indicated with like reference numerals.
The system 400 comprises a data abstraction layer 404 arranged to communicate directly with a client database 406 in order to retrieve quality control/quality assurance data from the client database 406 when the data is required during report creation.
It will be appreciated that with this embodiment the client database 406 is hosted by a client and, as such, the quality control/quality assurance data stored in the client 406 database is under the client's control.
During use, a user associated with a client desiring to create a report from data stored in the client database 12 connects to the web interface 14 through the Internet 18 using a computing device 16 remotely located relative to the client, or using a client computing device 410 at the same location as the client database 406. After appropriate identification of the user at a log in screen 40 shown in Figure 2, the user is granted access to the system 400 and is able to view high level information relating to projects associated with the client. The project information is stored at the client database 406 and is retrieved from the client database after user login has occurred. Using the web interface 14, the user is able to select one or more of the client projects which are to form the basis of a report.
As with the previous embodiment described in relation to Figures 1 to 25, a user is able to use the web interface 14 to define criteria for the desired report and to subsequently view the created report on the web interface 14.
With the present embodiment, when the report criteria have been defined, the report engine 22 instructs the data abstraction layer 404 to retrieve from the client database 406 data which is required in order to generate the desired report according to the defined report criteria, and the data abstraction layer interacts directly with the client database 406 over the Internet 18 and extracts the required data from the client database 406. In order to facilitate interaction with the client database, a network interface 408 is provided.
It will be understood that the report criteria may be defined using a computing device 16 disposed at a location remote from the client database 406, or using a client computing device 410 disposed locally.
The data abstraction layer 404 may have an associated database 412 for temporarily storing data as the data is extracted from the client database 406.
The report engine 22 then creates a report using the extracted data and using any required report application, such as the chart generator 26. The created report is then passed back to the web interface 14 through the control unit 20 and is served to the user's computing device 16 through the Internet 18 for viewing on the computing device 16.
It will be appreciated that with this embodiment quality control/quality assurance data for each client is stored by the client and data required by the system to create a report is extracted from the client database when required. In this way, it is not necessary for the system to include a database for storing client data. Moreover, since the client database 406 is queried directly by the data abstraction layer 404, compatibility issues between client data and system database requirements are minimized.
In the claims which follow and in the preceding description of the invention, except where the context requires otherwise due to express language or necessary implication, the word "comprise" or variations such as "comprises" or "comprising" is used in an inclusive sense, i.e. to specify the presence of the stated features but not to preclude the presence or addition of further features in various embodiments of the invention.
It is to be understood that, if any prior art publication is referred to herein, such reference does not constitute an admission that the publication forms a part of the common general knowledge in the art, in Australia or any other country.
Modifications and variations as would be apparent to a skilled addressee are deemed to be within the scope of the present invention.
Claims (40)
1. An automated reporting system comprising:
means for receiving quality control/quality assurance related data on-line from a remote location;
means for facilitating on-line definition by a user of report criteria for a quality control/quality assurance report based on the received data; and a report engine arranged to produce a quality control/quality assurance report according to the defined criteria and based on the received data.
means for receiving quality control/quality assurance related data on-line from a remote location;
means for facilitating on-line definition by a user of report criteria for a quality control/quality assurance report based on the received data; and a report engine arranged to produce a quality control/quality assurance report according to the defined criteria and based on the received data.
2. An automated reporting system as claimed in claim 1, wherein the quality control/quality assurance related data is assay data.
3. An automated reporting system as claimed in claim 2, wherein the quality control/quality assurance related data comprises mining related data, laboratory related data, or metallurgy related data.
4. An automated reporting system as claimed in any one of the preceding claims, wherein the means for facilitating definition by a user of report criteria comprises a web interface accessible through the Internet.
5. An automated reporting system as claimed in claim 4, wherein the web interface comprises a web server.
6. An automated reporting system as claimed in any one of the preceding claims, wherein the means for receiving quality control/quality assurance related data on-line is arranged to receive quality control/quality assurance related data by email.
7. An automated reporting system as claimed in any one of the preceding claims, wherein the means for receiving quality control/quality assurance related data on-line is arranged to receive quality control/quality assurance related data through the web interface.
8. An automated reporting system as claimed in any one of the preceding claims, wherein the system further comprises a system database arranged to store quality control/quality assurance related data received from at least one client.
9. An automated reporting system as claimed in any one of the preceding claims, wherein the means for receiving quality control/quality assurance related data on-line is arranged to extract quality control/quality assurance data from a client hosted database.
10. An automated reporting system as claimed in claim 9, comprising a data abstraction layer arranged to directly interact with the client database.
11. An automated reporting system as claimed in claim 9 or claim 10, wherein the means for receiving quality control/quality assurance related data of this embodiment is arranged to extract quality control/quality assurance data from a client hosted database on-the-fly based on criteria defined for a client report.
12. An automated reporting system as claimed in any one of the preceding claims, wherein the means for facilitating definition by a user of report criteria is arranged to facilitate selection on-line by a user of extraction criteria defining data to be included in a report.
13. An automated reporting system as claimed in claim 12, wherein the extraction criteria include one or more of project name, sample taken date or sample reported date, element or compound, test type, laboratory, batch number, analytical method, blank type, standard name, field duplicate name or laboratory duplicate name.
14. An automated reporting system as claimed in any one of the preceding claims, wherein the means for facilitating definition by a user of report criteria is arranged to facilitate definition of an exception profile indicative of the level at which test data suggests a potential area of concern.
15. An automated reporting system as claimed in claim 14, wherein the exception profile is effective for all elements and compounds included in the or each test.
16. An automated reporting system as claimed in any one of the preceding claims, wherein the means for facilitating definition by a user of report criteria is arranged to facilitate definition of at least one exception parameter specific to one or more element or compound and for at least one test.
17. An automated reporting system as claimed in any one of the preceding claims, wherein the system comprises at least one report procedure usable by the report engine to produce a report.
18. An automated reporting system as claimed in any one of the preceding claims, wherein the report engine comprises a report application usable to create required report content and/or present report content.
19. An automated reporting system as claimed in any one of the preceding claims, wherein the report engine comprises a format generator application usable to export a report in a desired format.
20. An automated reporting system as claimed in any one of the preceding claims, wherein the system is arranged to facilitate downloading of a report by a user.
21. A method of generating a quality control/quality assurance report comprising:
receiving quality control/quality assurance related data on-line from a remote location;
facilitating on-line definition by a user of report criteria for a quality control/quality assurance report based on the received data; and producing a quality control/quality assurance report according to the defined criteria and based on the received data.
receiving quality control/quality assurance related data on-line from a remote location;
facilitating on-line definition by a user of report criteria for a quality control/quality assurance report based on the received data; and producing a quality control/quality assurance report according to the defined criteria and based on the received data.
22. A method as claimed in claim 21, wherein the quality control/quality assurance related data is assay data.
23. A method as claimed in claim 22, wherein the quality control/quality assurance related data comprises mining related data, laboratory related data, or metallurgy related data.
24. A method as claimed in any one of claims 21 to 23, wherein the step of facilitating definition by a user of report criteria comprises providing a web interface accessible through the Internet.
25. A method as claimed in claim 24, wherein the web interface comprises a web server.
26. A method as claimed in any one of claims 21 to 24, comprising receiving quality control/quality assurance related data by email.
27. A method as claimed in any one of the preceding claims, comprising receiving quality control/quality assurance related data through the web interface.
28. A method as claimed in any one of claims 21 to 27, comprising storing quality control/quality assurance related data received from at least one client.
29. A method as claimed in any one of claims 21 to 28, comprising extracting quality control/quality assurance data from a client hosted database.
30. A method as claimed in claim 29, comprising providing a data abstraction layer arranged to directly interact with the client database.
31. A method as claimed in claim 29 or claim 30, comprising extracting quality control/quality assurance data from a client hosted database on-the-fly based on criteria defined for a client report.
32. A method as claimed in any one of claims 21 to 31, facilitating selection on-line by a user of extraction criteria defining data to be included in a report.
33. A method as claimed in claim 32, wherein the extraction criteria include one or more of project name, sample taken date or sample reported date, element or compound, test type, laboratory, batch number, analytical method, blank type, standard name, field duplicate name or laboratory duplicate name.
34. A method as claimed in any one of claims 21 to 33, comprising facilitating definition of an exception profile indicative of the level at which test data suggests a potential area of concern.
35. A method as claimed in claim 34, wherein the exception profile is effective for all elements and compounds included in the or each test.
36. A method as claimed in any one of claims 21 to 35, comprising facilitating definition of at least one exception parameter specific to one or more element or compound and for at least one test.
37. A method as claimed in any one of claims 21 to 36, comprising providing at least one report procedure usable to produce a report.
38. A method as claimed in any one of claims 21 to 37, comprising facilitating downloading of a report by a user.
39. An automated reporting system substantially as hereinbefore described with reference to, and as shown in, the accompanying drawings.
40. A method of generating a quality control/quality assurance report substantially as hereinbefore described with reference to, and as shown in, the accompanying drawings.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CA 2656305 CA2656305A1 (en) | 2009-02-24 | 2009-02-24 | An automated reporting system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CA 2656305 CA2656305A1 (en) | 2009-02-24 | 2009-02-24 | An automated reporting system |
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|---|---|
| CA2656305A1 true CA2656305A1 (en) | 2010-08-24 |
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|---|---|---|---|
| CA 2656305 Abandoned CA2656305A1 (en) | 2009-02-24 | 2009-02-24 | An automated reporting system |
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| CA (1) | CA2656305A1 (en) |
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2009
- 2009-02-24 CA CA 2656305 patent/CA2656305A1/en not_active Abandoned
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