Method for providing control to an industrial process using one or more multidimensional variables

• US 7,136,716 B2
• Filed: 05/25/2005
• Issued: 11/14/2006
• Est. Priority Date: 03/10/2000
• Status: Expired due to Term

• Current Assignee: Smiths Detection (Smiths Group International Holdings Ltd.)
• Original Assignee: Smiths Detection (Smiths Group International Holdings Ltd.)
• Inventors: Steinthal, Michael Gregory, Hsiung, Chang-Meng B., Vicic, Michael Allen, Zhang, Shou-Hua, Sunshine, Steven A., Roy, Ajoy Kumar, Munoz, Bethsabeth
• Primary Examiner(s): Picard, Leo
• Assistant Examiner(s): Masinick, Michael D.
• Application Number:
  US11/136,474
• Publication Number:
  US 20050216114A1
• Time in Patent Office: 538 Days
• Field of Search: 700/110, 700/108, 700/109, 700/78, 700/80
• US Class Current: 700/104
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 19/042 using digital processors G05B19/05 takes precedence
• CPC Class Codes: G05B 19/4093 characterised by part programming, e.g. entry of geometrical information as taken from a technical drawing, combining this with machining and material information to obtain control information, named part programme, for the NC machine
• CPC Class Codes: G05B 19/41855 by local area network [LAN], network structure
• CPC Class Codes: G05B 19/41865 characterised by job scheduling, process planning, material flow
• CPC Class Codes: G05B 19/41875 characterised by quality surveillance of production
• CPC Class Codes: G05B 2219/31265 Control process by combining history and real time data
• CPC Class Codes: G05B 2219/31337 Failure information database
• CPC Class Codes: G05B 2219/31435 Paging support with display board, status monitoring and report compiling
• CPC Class Codes: G05B 2219/31457 Factory remote control, monitoring through internet
• CPC Class Codes: G05B 2219/32129 Select program for specified machine from library, file server
• CPC Class Codes: G05B 2219/32194 Quality prediction
• CPC Class Codes: G05B 2219/32196 Store audit, history of inspection, control and workpiece data into database
• CPC Class Codes: G05B 2219/32201 Build statistical model of past normal proces, compare with actual process
• CPC Class Codes: G05B 2219/32404 Scada supervisory control and data acquisition
• CPC Class Codes: G05B 2219/33209 Protocol, mailbox, email, mail system
• CPC Class Codes: G05B 2219/35095 Features library
• CPC Class Codes: G05B 23/0221 Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
• CPC Class Codes: G05B 23/0235 based on a comparison with predetermined threshold or range, e.g. "classical methods", carried out during normal operation; threshold adaptation or choice; when or how to compare with the threshold
• CPC Class Codes: G05B 23/0243 model based detection method, e.g. first-principles knowledge model
• CPC Class Codes: G05B 23/0254 : based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks
• CPC Class Codes: G05B 23/0286 : Modifications to the monitored process, e.g. stopping operation or adapting control
• CPC Class Codes: G05B 23/0294 : Optimizing process, e.g. process efficiency, product quality
• CPC Class Codes: Y02A 90/10 : Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
• CPC Class Codes: Y02P 90/02 : Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
• CPC Class Codes: Y02P 90/80 : Management or planning

Abstract

A method for controlling an industrial process. The method includes outputting a plurality of parameters from a process for manufacture of a substance. The method also uses each of the plurality of parameters in a computer aided process, which compares at least two of the plurality of parameters against a training set of parameters. The training set of parameters is generally predetermined. A step of determining if the at least two of the plurality of parameters are within a predetermined range of the training set of parameters also is included. Additionally, the method includes outputting a result based upon the determining step.

Claims

1. A method for controlling an industrial process, the method comprising;

inputting a plurality of parameters from a process for manufacture of a substance, the process for manufacture of a substance being controlled by a process controller;

coupling an external system to the process controller;

using each of the plurality of parameters in a computer aided process, the computer aided process comparing at least two of the plurality of parameters against a training set of parameters, the training set of parameters being predetermined;

determining if the at least two of the plurality of parameters are within a predetermined range of the training set of parameters; and

outputting a result based upon the determining step and the external system,

wherein the external system corresponds to a second process that is substantially duplicative of the process for manufacture of a substance.

2. The method of claim 1 wherein the substance is selected from a petroleum product, a chemical product, a food product, a health product, a cleaning product, a biological product, and other fluid or objects.

3. The method of claim 1 wherein the plurality of parameters are selected from an intrinsic element or an extrinsic element of the process.

4. The method of claim 1 wherein the using, determining, and outputting are provided in a computer software program.

5. The method of claim 1 wherein the computer aided process includes an algorithm selected from PCA, HCA, KNN CV KNN Prd, SIMCA CV, SIMCA Prd, Canon Prd, SCREAM, and Fisher CV.

6. The method of claim 1 further comprising normalizing each of the plurality of parameters before the using step.

7. The method of claim 1 further comprising adjusting a base line of each of the plurality of parameters before the using step.

8. The method of claim 1 wherein the result is an affirmative response or a negative response, where the response is displayed on a terminal.

9. The method of claim 1 wherein the computer aided process is selected from a library comprising a plurality of processes for performing the comparing step.

10. The method of claim 9 wherein the plurality of processes includes at least a comparing process, a contrasting process, and a functional process.

11. A method for monitoring an industrial process for the manufacture of materials, the method comprising:

inputting a plurality of process parameters from a process for manufacture of a substance, the process for manufacture of a substance being controlled by a process controller;

coupling an external system to the process controller;

selecting one of a plurality of computer aided processes, each of the computer aided processes being capable of determining an output based upon a training set of the plurality of process parameters;

using each of the plurality of parameters in the selected computer aided process, the selected computer aided process comparing at least two of the plurality of process parameters against a training set of parameters;

determining if the at least two of the plurality of process parameters are within a predetermined range of the training set of parameters; and

outputting a result based upon the determining step and the external system,

wherein the external system corresponds to a second process that is substantially duplicative of the process for manufacture of a substance.

12. The method of claim 11 wherein the substance is selected from a petroleum product, a chemical product, a food product, a health product, a cleaning product, a biological product, and other fluid or objects.

13. The method of claim 11 wherein the plurality of process parameters are selected from an intrinsic element or an extrinsic element of the process.

14. The method of claim 11 wherein the using, determining, and outputting are provided in a computer software program.

15. The method of claim 11 wherein the computer aided process includes an algorithm selected from PCA, HCA, KNN CV KNN Prd, SIMCA CV, SIMCA Prd, Canon Prd, SCREAM, and Fisher CV.

16. The method of claim 11 further comprising normalizing each of the plurality of parameters before the using step.

17. The method of claim 11 further comprising adjusting a base line of each of the plurality of parameters before the using step.

18. The method of claim 11 wherein the result is an affirmative response or a negative response, where the response is displayed on a terminal.

19. The method of claim 11 wherein the computer aided process is selected from a library comprising a plurality of processes for performing the comparing step.

20. The method of claim 19 wherein the plurality of processes includes at least a comparing process, a contrasting process, and a functional process.

21. A method for identifying a mode of operation in an industrial process, the method comprising:

running an industrial process, the industrial process being characterized by a plurality of parameters at an in-process state of a substance or object being manufactured, each of the parameters defining a characteristic of the substance or the object in the in-process state;

converting each of the parameters into an electronic form;

processing the preprocessed parameters through a first computer aided process to form at least a first descriptor and a second descriptor from the preprocessed parameters, the first computer aided process being selected from a plurality of computer aided processes based upon a first training set of parameters;

determining if the first descriptor and the second descriptor are within a selected class from a plurality of classes and are in agreement with each other; and

if the first descriptor and the second descriptor are in agreement with each other, outputting a first result based upon the determining step; and

if the first descriptor and the second descriptor are not in agreement with each other, then;

processing the preprocessed parameters through a second computer aided process different from the first computer aided process, the second computer aided process being selected from a plurality of computer aided processes based upon a second training set of parameters; and

outputting a second result based upon the processing performed through the second computer aided process.

22. A method for determining an acceptability of a process, the method comprising:

identifying a plurality of process parameters from a process for manufacture of a substance;

using one of the selected computer aided processes out of a plurality of computer aided processes, the selected computer aided process being derived from a training set of the plurality of process parameters;

determining an acceptability of the process using each of the plurality of parameters in the selected computer aided process, the selected computer aided process comparing at least two of the plurality of process parameters against a training set of parameters; and

if the two of the plurality of process parameters are within acceptable ranges with respect to the training set of parameters and are in agreement with each other, outputting a result indicating an acceptable process;

if the two of the plurality of process parameters are either not within acceptable ranges with respect to the training set of parameters or are not in agreement with each other, using another of the selected computer aided processes to determine a level of uncertainty in the process.