Global Integrated improvement planning tool

• US 20040249688A1
• Filed: 06/09/2003
• Published: 12/09/2004
• Est. Priority Date: 06/09/2003
• Status: Abandoned Application

• Current Assignee: ExxonMobil Chemical Patents Inc. (Exxon Mobil Corporation)
• Original Assignee: ExxonMobil Chemical Patents Inc. (Exxon Mobil Corporation)
• Inventors: Fields, Rodger L., Sanders, Elizabeth F.
• Application Number:
  US10/457,343
• Publication Number:
  US 20040249688A1
• Time in Patent Office: Days
• US Class Current: 705/7
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

A tool which gathers relevant improvement data at each particular plant location, for each particular technology and line. This improvement data can be the various underlying data needed for analysis and can include the intended or estimated efficiency increase for given areas of effort, with the relevant costs, manpower and so on. When all of the data for the relevant plants around the world has been inputted, this information is then transferred to a global storage location so that all data from all plants can be accessed simultaneously. With this multi-line, multi-facility data available, reporting structures are developed to allow simplified analysis of the particular improvements and related costs, resources and other factors. Reporting results can be easily developed along a myriad of relationships, such as by geography, by technology, by resource, and so on. Reviewing the derived report selections, at various levels of detail as desired, of all of the facilities around the world, an analyst can readily determine the optimal use of capital and resources to improve overall global system efficiency.

Claims

1. A system for collective process improvement optimization at a plurality of locations, each of the locations having processes and identified improvements and at least some of the locations including processes having common and disparate elements, the system comprising:

data storage related to each location;

a plurality of data entry systems, each data entry system to receive location data relevant to improvements to a location process from a user for a location and storing received location data in the related data storage for the location;

collective data storage coupled to the data storage of each location for collectively storing all of the data received for each location;

a collective data selection system to allow a user to select various data from the collectively stored data at varied detail levels; and

a collective data visualization system to allow a user to view the selected data at the selected detail level in a plurality of formats to allow easy analysis of the data.

2. The system of claim 1, wherein the collective data storage includes:

a data warehouse storing all of the data for each location; and

analysis data storage including a copy of all of the data for each location provided from the data warehouse.

3. The system of claim 1, wherein the data storage related to each location is logically separated.

4. The system of claim 1, further comprising:

a plurality of local data visualization systems, each local data visualization system to allow a user to view stored data for that location in a plurality of formats.

5. The system of claim 1, wherein each local data entry system further includes a calculation entity to develop calculated data related to the location and stored in the related data storage for the location.

6. The system of claim 1, wherein the process improvements for the plurality of locations can be organized in a plurality of ways and the collective data selection system allows selection using at least some of the plurality of ways.

7. The system of claim 6, wherein the collective data selection system allows selection using each of the plurality of ways.

8. The system of claim 6, wherein the locations are geographically dispersed and the processes are of a plurality of types, the types being organized at various levels of generality, and wherein the collective data selection system allows selection by geography and by process type.

9. The system of claim 8, wherein the geography and process type can be selected at various levels of generality.

10. The system of claim 9, wherein the type includes intermediates at the highest level of generality;

includes fluids and synthetics at the next lower level of generality; and

includes oxy fluids and hydrocarbon fluids and esters, low viscosity polyalphaolefins and high viscosity polyalphaolefins at the next lower level of generality.

11. The system of claim 9, wherein the geography includes Americas, Asia Pacific and Europe at the highest level of generality;

and includes Sarnia, Beaumont, Baytown and Baton Rouge;

Singapore; and

Antwerp, Fawley and Rotterdam at the next lower level of generality.

12. The system of claim 1, wherein the location process improvement data includes data over a series of time periods and for a series of improvement levels and wherein the data entry system receives data for each of the time periods and each of the improvement levels for the each process improvement.

13. The system of claim 1, wherein the formats of the collective data visualization system include charts and reports.

14. The system of claim 13, wherein a chart can be viewed using different selected data for an axis for a given set of selected data.

15. The system of claim 13, wherein collective data visualization system can further select data sorting parameters for reports.

16. A method for collective process improvement optimization at a plurality of locations, each of the locations having processes and identified improvements and at least some of the locations including processes having common and disparate elements, the method comprising:

receiving data relevant to improvements to a process from a plurality of data entry systems, each data entry system receiving location data relevant to improvements to a location process from a user for a location;

storing received location data in data storage related to the location;

collectively storing all of the data received for each location in collective data storage;

selecting various data from the collectively stored data at varied detail levels; and

viewing the selected data at the selected detail level in a plurality of formats to allow easy analysis of the data.

17. The method of claim 16, wherein collectively storing includes:

storing all of the data for each location in a data warehouse; and

storing a copy of all of the data for each location provided from the data warehouse in analysis data storage.

18. The method of claim 16, wherein the data storage related to each location is logically separated.

19. The method of claim 16, further comprising:

viewing stored data for a location in a plurality of formats.

20. The method of claim 16, further comprising:

developing calculated data related to the location and storing it in the related data storage for the location.

21. The method of claim 16, wherein the process improvements for the plurality of locations can be organized in a plurality of ways and the collectively stored data can be selected using at least some of the plurality of ways.

22. The method of claim 21, wherein the locations are geographically dispersed and the processes are of a plurality of types, the types being organized at various levels of generality, and wherein the collectively stored data can be selected by geography and by process type.

23. The method of claim 22, wherein the geography and process type can be selected at various levels of generality.

24. The method of claim 23, wherein the type includes intermediates at the highest level of generality;

includes fluids and synthetics at the next lower level of generality; and

includes oxy fluids and hydrocarbon fluids and esters, low viscosity polyalphaolefins and high viscosity polyalphaolefins at the next lower level of generality.

25. The method of claim 23, wherein the geography includes Americas, Asia Pacific and Europe at the highest level of generality;

and includes Sarnia, Beaumont, Baytown and Baton Rouge;

Singapore; and

Antwerp, Fawley and Rotterdam at the next lower level of generality.

26. The method of claim 16, wherein the location process improvement data includes data over a series of time periods and for a series of improvement levels and wherein the data entry system receives data for each of the time periods and each of the improvement levels for the each process improvement.

27. The method of claim 16, wherein the plurality of formats for viewing collective data include charts and reports.

28. The method of claim 27, wherein a chart can be viewed using different selected data for an axis for a given set of selected data.

29. The method of claim 27, wherein the user can further select data sorting parameters for reports.

30. The method of claim 16, further comprising:

prioritizing identified improvements after selecting and viewing the collectively stored data.

31. The method of claim 16, further comprising:

optimizing identified improvements after selecting and viewing the collectively stored data.