Analytical evaluation tool for continuous process plants

• US 8,855,968 B1
• Filed: 12/10/2013
• Issued: 10/07/2014
• Est. Priority Date: 12/10/2012
• Status: Active Grant

• Current Assignee: Timothy Lynn Gillis
• Original Assignee: Timothy Lynn Gillis
• Inventors: Gillis, Timothy Lynn
• Primary Examiner(s): Le, John H
• Application Number:
  US14/101,832
• Time in Patent Office: 301 Days
• Field of Search: 702/81, 702/84, 702/127, 702179-183, 702/187, 702/193, 702/45, 370/215, 548/491, 700/29, 700/79, 700/108, 700/103, 700/266, 703/2, 703/13, 705/7.38, 705/26.1, 705/7.39, 706/12, 706/20, 706/25
• US Class Current: 702/182
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations

Abstract

A method for evaluating the operation of a continuous process plant uses operational data. The operational data includes data points representing the quantity of a substance processed by the continuous process plant during a plurality of time periods. The quantity of substance processed during these time periods is compared to a goal value. A reliability score is calculated. A banked opportunity score is calculated. An equivalent lost stream days score is calculated. The average quantity processed during periods that equaled or exceeded the goal is calculated. The average quantity processed during periods that were below the goal is calculated. The components of the equipment or machinery of the continuous process plant are classified and correlated to the quantity of lost opportunity. The scores are reported. The scores are also compared to historical data.

Claims

1. A method of evaluating operation of a continuous process plant, comprising:

loading operational data for a continuous process plant, wherein the operational data comprises a plurality of data points, each of the data points in the plurality of data points representing a time period and a quantity processed during that time period;

identifying a goal value;

processing the operational data to identify cut-rate data points, the cut-rate data points representing time periods with a quantity processed that is less than the goal value;

calculating a cut-rate lost opportunity, wherein the cut-rate lost opportunity corresponds to the sum of the difference between the goal value and the quantity processed for each of the cut-rate data points;

calculating, by a computing device, a score for the continuous process plant, wherein the score corresponds to the quotient of the cut-rate lost opportunity divided by the goal value;

processing the operational data to identify banked-opportunity data points, the banked-opportunity data points representing time periods with a quantity processed that is greater than the goal value; and

calculating a banked opportunity, wherein the banked opportunity corresponds to the sum of the difference between the quantity processed and the goal value for each of the banked-opportunity data points.

2. The method of claim 1, further comprising:

determining a reliability score, wherein the reliability score corresponds to a percent of the data points in the plurality of data points having a quantity processed that is equal to or greater than the goal value.

3. The method of claim 1, further comprising:

determining a first count value, wherein the first count value corresponds to a number of data points in the plurality of data points having a quantity processed that is equal to or greater than the goal value;

determining a second count value, wherein the second count value corresponds to a number of data points in the plurality of data points having a quantity processed that is less than the goal value.

4. The method of claim 3, further comprising:

displaying, on a display device, the score for the processing plant, the banked opportunity, the first count value, and the second count value.

5. The method of claim 1, further comprising:

loading historical operational data for a continuous process plant, wherein the historical operational data comprises a plurality of historical data points; and

comparing the operational data to the historical operational data.

6. The method of claim 1, wherein the continuous process plant is a refinery.

7. The method of claim 1, wherein the continuous process plant is a petrochemical plant.

8. The method of claim 1, wherein the continuous process plant is a fertilizer plant.

9. The method of claim 1, wherein each of the data points in the plurality of data points represent a time period with a duration of one day.

10. The method of claim 1, wherein each of the data points in the plurality of data points represent a time period with a duration of one shift.

11. The method of claim 1, wherein the goal value is identified by receiving a user input.

12. The method of claim 1, wherein the goal value is identified based on historical data.

13. The method of claim 1, further comprising:

loading equipment operational data, wherein the equipment operational data identifies a component of the continuous process plant that limited the quantity processed in at least one of the data points; and

classifying equipment in the continuous process plant using the operational data and the equipment operational data.

14. A continuous process plant comprising:

processing machinery, the processing machinery being configured to process at least one substance; and

a computing device, the computing device comprising;

a processing unit; and

a set of computer-readable data storage media comprising at least one computer-readable data storage medium, the set of computer-readable data storage media storing software instructions that, when executed by the processing unit, cause the computing device to;

load operational data for a continuous process plant, wherein the operational data comprises a plurality of data points, each of the data points in the plurality of data points representing a time period and a quantity processed during that time period;

identify a goal value;

process the operational data to identify cut-rate data points, the cut-rate data points representing time periods with a quantity processed that is less than the goal value;

calculate a cut-rate lost opportunity, wherein the cut-rate lost opportunity corresponds to the sum of the difference between the goal value and the quantity processed for each of the cut-rate data points;

calculate a score for the continuous process plant, wherein the score corresponds to the quotient of the cut-rate lost opportunity divided by the goal value;

process the operational data to identify banked-opportunity data points, the banked-opportunity data points representing time periods with a quantity processed that is greater than the goal value; and

calculate a banked opportunity, wherein the banked opportunity corresponds to the sum of the difference between the quantity processed and the goal value for each of the banked-opportunity data points.

15. The plant of claim 14, wherein the software instructions further cause the computing device to:

determine a reliability score, wherein the reliability score corresponds to a percent of the data points in the plurality of data points having a quantity processed that is equal to or greater than the goal value.

16. The plant of claim 14, wherein the software instructions further cause the computing device to:

determine a first count value, wherein the first count value corresponds to a number of data points in the plurality of data points having a quantity processed that is equal to or greater than the goal value; and

determine a second count value, wherein the second count value corresponds to a number of data points in the plurality of data points having a quantity processed that is less than the goal value.

17. The plant of claim 16, wherein the software instructions further cause the computing device to:

display the score for the processing plant, the banked opportunity, the first count value, and the second count value.

18. A method of evaluating operation of a continuous process plant, comprising:

loading operational data for a continuous process plant, wherein the operational data comprises a plurality of data points, each of the data points in the plurality of data points representing a time period and a quantity processed during that time period;

identifying a goal value;

processing the operational data to identify cut-rate data points, the cut-rate data points representing time periods with a quantity processed that is less than the goal value;

calculating a cut-rate lost opportunity, wherein the cut-rate lost opportunity corresponds to the sum of the difference between the goal value and the quantity processed for each of the cut-rate data points;

calculating, by a computing device, a score for the continuous process plant, wherein the score corresponds to the quotient of the cut-rate lost opportunity divided by the goal value;

processing the operational data to identify banked-opportunity data points, the banked-opportunity data points representing time periods with a quantity processed that is greater than the goal value;

calculating a banked opportunity, wherein the banked opportunity corresponds to the sum of the difference between the quantity processed and the goal value for each of the banked-opportunity data points;

determining a reliability score, wherein the reliability score corresponds to the percent of the data points in the plurality of data points having a quantity processed that is equal to or greater than the goal value;

determining a first count value, wherein the first count value corresponds to a number of data points in the plurality of data points having a quantity processed that is equal to or greater than the goal value;

determining a second count value, wherein the second count value corresponds to a number of data points in the plurality of data points having a quantity processed that is less than the goal value;

loading historical operational data for a continuous process plant, wherein the historical operational data comprises a plurality of historical data points; and

comparing the operational data to the historical operational data.