METHOD FOR ACHIEVING AND VERIFYING INCREASED PRODUCTIVITY IN AN INDUSTRIAL PROCESS

• US 20020010563A1
• Filed: 06/15/1999
• Published: 01/24/2002
• Est. Priority Date: 06/15/1999
• Status: Abandoned Application

• Current Assignee: Shared Savings Contracts Incorporated
• Original Assignee: Shared Savings Contracts Incorporated
• Inventors: DUFFY, JOHN B., RATTEREE, S. MICHAEL
• Application Number:
  US09/333,615
• Publication Number:
  US 20020010563A1
• Time in Patent Office: Days
• US Class Current: 703/2
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G05B 19/41885 characterised by modeling, simulation of the manufacturing system
• CPC Class Codes: G05B 2219/2639 Energy management, use maximum of cheap power, keep peak load low
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: Y02P 90/82 Energy audits or management systems therefor

Abstract

A method for improving the productivity of an industrial process includes the steps of using a computer to derive a statistical mathematical model that describes a productivity-related parameter, such as energy use, consumables use, or production rate, in terms of a validated set of independent variables. A modification that will improve the productivity of the process is identified and implemented and the model is used to measure the change in the productivity-related parameter caused by the modification. Measurement of the change is carried out by determining the difference between a measured value of the productivity-related parameter and a value of the parameter predicted by the model using measured values of the independent variables that are included in the validated set.

Claims

1. A method for improving the productivity of an industrial process comprising the steps of:

deriving with a computer a statistical mathematical model that describes a productivity-related parameter for the industrial process in terms of a validated set of independent variables;

identifying a modification to improve the productivity of the process;

implementing the modification; and

measuring the change in the productivity-related parameter caused by the modification by determining the difference between a measured value of the parameter and a value of the parameter predicted by the model using measured values of each of the independent variables of the validated set.

2. The method as set forth in claim 1, where the industrial process includes process equipment having a size and in which an amount of capital is invested, and which process uses consumables, energy and labor for the production of one or more products;

wherein the productivity-related parameter is production per unit of time, production per unit of labor, production per unit of energy use, production per unit of consumables use, production per unit of process equipment size, production per unit of capital invested in the process, energy use per unit time, consumables use per unit time, or the inverse of any of these.

3. The method as set forth in claim 2, wherein the modification to improve the productivity of the process is carried out without affecting an independent variable that is included in the validated set.

4. The method as set forth in claim 2, wherein the productivity-related parameter is energy use per unit time.

5. A method as set forth in claim 4, wherein the step of deriving with a computer a statistical mathematical model that describes a productivity-related parameter for the industrial process in terms of a validated set of independent variables comprises deriving with a computer a model of production per unit of process energy use having the form:

6. A method as set forth in claim 5, wherein E_k is derived for each of the unit processes from a formula having the form:

7. The method as set forth in claim 2, wherein the productivity-related parameter is production of products per unit time.

8. The method as set forth in claim 7, wherein the step of deriving with a computer a statistical mathematical model that describes a productivity-related parameter for the industrial process in terms of a validated set of independent variables comprises deriving with a computer a model of production per unit of time having the form:

9. A method as set forth in claim 8, wherein P_k is derived for each of the unit processes from a formula having the form:

10. The method as set forth in claim 2, wherein the productivity-related parameter is consumables use per unit time.

11. The method as set forth in claim 10, wherein the step of deriving with a computer a statistical mathematical model that describes a productivity-related parameter for the industrial process in terms of a validated set of independent variables comprises deriving with a computer a model of consumables use per unit of time having the form:

12. The method as set forth in claim 11, wherein C_k is derived for each of the unit processes from a formula having the form

13. The method as set forth in claim 2, wherein a set of historical operating data has been collected for values of the productivity-related parameter and for values of one or more independent variables and such set of historical data is divided into a correlation portion and a validation portion;

and the statistical mathematical model is 5 derived by using the correlation portion; and

wherein a validated set of independent variables is selected as that set of independent variables that provides a statistical mathematical model having a monthly deviation of no larger than ±

5% when tested against the data in the validation portion.

14. The method as set forth in claim 13, wherein the validated set of independent variables is selected as that set of independent variables that provides a statistical mathematical model having a yearly deviation of no larger than ±

1% when tested against the data in the validation portion.

15. The method as set forth in claim 14, wherein the statistical mathematical model has an R-squared value of not under 0.6.

16. The method as set forth in claim 15, wherein the statistical mathematical model has an R-squared value of not under 0.7.

17. The method as set forth in claim 16, wherein the statistical mathematical model has an R-squared value of not under 0.8.

18. The method as set forth in claim 17, wherein the statistical mathematical model has an R-squared value of not under 0.9.

19. The method as set forth in claim 17, wherein the value of m=1.

20. The method as set forth in claim 1, wherein the step of identifying a modification to improve the productivity of the process comprises the steps of:

using the model to predict productivity changes by simulating the results of one or more proposed modifications of the process; and

selecting at least one of the proposed modifications on the basis of the degree to which the predicted productivity changes are an improvement to the process productivity.

21. The method as set forth in claim 19, wherein the step of implementing the modification comprises the purchase and installation of capital equipment.

22. The method as set forth in claim 21, wherein the industrial process is owned by an owner having a balance sheet and the capital equipment is purchased and installed by a contractor.

23. The method as set forth in claim 22, wherein funds for the purchase and installation of the capital equipment are obtained by the contractor under a loan from a lender, thereby providing that the debt does not appear on the balance sheet of the owner.

24. The method as set forth in claim 23, wherein the loan is a general obligation loan.

25. The method as set forth in claim 19, further comprising the step of calculating the value in terms of money of the change in the productivity-related parameter caused by the modification.

26. The method as set forth in claim 25, wherein the industrial process is owned by an owner and at least some part of the cost of the modification has been funded by contractor.

27. The method as set forth in claim 26, wherein the industrial process is owned by an owner and at least a substantial part of the cost of the modification has been funded by contractor.

28. The method as set forth in claim 27, wherein the industrial process is owned by an owner and all of the cost of the modification has been funded by contractor.

29. The method as set forth in claim 28, wherein the savings that result from the modification is shared between the owner and the contractor.

30. The method as set forth in claim 29, wherein the excess of the value of the change in the productivity-related parameter caused by the modification over the cost of the modification is shared between the owner and the contractor on an equal basis for a negotiated period of time.

31. The method as set forth in claim 29, wherein a negotiated portion of the excess of the value of the change in the productivity-related parameter caused by the modification over the cost of the modification is shared between the owner and the contractor.

32. The method as set forth in claim 2, further comprising measuring the value of the productivity-related parameter and the independent variables of the validated set on a regular basis;

and plotting the measured value of the productivity-related parameter, the value of the productivity-related parameter predicted by the model using the measured values of the independent variables; and

the difference therebetween, as a function of time, thereby providing a tool to track and visually present the impact of the modification.

33. The method as set forth in claim 2, further comprising measuring the value of the productivity-related parameter and the independent variables of the validated set on a regular basis;

calculating the value of the productivity-related parameter predicted by the model using the measured values of the independent variables;

where the difference therebetween is a measure of the impact of the modification upon the productivity-related parameter; and

determining whether the process is statistically out of control by testing the impact versus time data against Western Electric Zone Tests.

34. The method as set forth in claim 2, further comprising measuring the value of the productivity-related parameter and the one or more independent variables on a regular basis;

and plotting the measured value of the productivity-related parameter, the value of the productivity-related parameter predicted by the model using the measured values of the independent variables of the validated set; and

the difference therebetween, as a function of time, thereby providing a tool to help identify any trend of the productivity-related parameter due to the impact of the modification.