Method and device for optimizing processes

• US 20060010018A1
• Filed: 08/11/2003
• Published: 01/12/2006
• Est. Priority Date: 08/23/2002
• Status: Active Grant

• Current Assignee: Siemens AG
• Original Assignee: Siemens AG
• Inventors: Bouriant, Alexandre
• Granted Patent: US 8,126,573 B2
• Time in Patent Office: Days
• US Class Current: 705/7
• CPC Class Codes: G05B 13/024 in which a parameter or coefficient is automatically adjusted to optimise the performance
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations

Abstract

The invention relates to a process-optimizing device, particularly a manufacturing execution system device. Such a process-optimizing MES device is mounted between an enterprise production planning system, especially an enterprise resource planning device, and a control system, particularly a process instrumentation and control device. The inventive MES device comprises at least one optimization unit for influencing one or several process parameters of the control system, especially the PLT device, at least one data-determining unit for monitoring the process parameter/s, and at least one evaluation unit for automatically determining an optimization of the process parameter/s, which is created by the optimization unit/s.

Claims

1-19. -19. (canceled)

20. A device for process optimization, comprising:

at least an optimization entity for influencing at least a process parameter;

at least a monitoring entity for monitoring the process parameter; and

at least an evaluation entity for automatically determining an optimization of the process parameter, wherein the optimization is effected by the optimization entity.

21. The device according to claim 20, wherein the process parameter which must be optimized, and which is influenced by the optimization entity, is assigned an evaluation entity such that the optimization which is effected on the process parameter by the optimization entity can be determined by the evaluation entity online and/or in real time.

22. The device according to claim 20, wherein the evaluation entity has at least one evaluation module for automatically determining an optimization of a corresponding process parameter, wherein the optimization is effected by a specific optimization entity.

23. The device according to claim 22, wherein the evaluation module is used for automatically determining a yield increase which is effected in relation to a relevant process parameter or for automatically determining a cost saving which is effected in relation to a relevant process parameter.

24. The device according to claim 22, wherein the number of evaluation modules in an evaluation entity which is assigned to a process parameter is dependent on the number of optimization entities which influence the process parameter concerned.

25. The device according to claim 22, wherein the evaluation modules provide an absolute optimization value and a time-related optimization value as output values, thereby allowing absolute and time-related recording of the optimization which is effected for relevant process parameter by each optimization entity.

26. The device according to claim 20, wherein all evaluation entities are connected to an overall evaluation entity, such that the effected overall optimization of all process parameters can be determined online and in real time by the overall evaluation entity.

27. The device according to claim 20, wherein at least one time normalization entity is provided for normalizing time quantities.

28. The device according to claim 20, wherein at least one process-quantity normalization entity is provided for normalizing the process quantities which are used by all entities.

29. The device according to claim 28, wherein the process-quantity normalization entity is used for normalizing variables and/or parameters.

30. The device according to claim 20, wherein a display entity for visualizing the effected optimization of the or each process parameter and/or for visualizing the effected overall optimization of all process parameters.

31. The device according to claim 30, wherein the display entity simultaneously depicts the effected optimization of each individual process parameter and the effected overall optimization of all process parameters online and/or in real time in a dynamic spider diagram.

32. An MES (manufacturing execution system) device for optimizing processes, wherein the MES device is connected between an enterprise and production planning system and a monitoring and control system, the MES device comprising:

at least one optimization entity for influencing one or more process parameters of the monitoring and control system;

at least one data determining entity for monitoring the or each process parameter; and

at least one evaluation entity for automatically determining an optimization of the or each process parameter, said optimization having been effected by the or each optimization entity.

33. The MES device according to claim 32, wherein the enterprise and production planning system is an ERP (enterprise resource planning) device, and wherein the monitoring and control system is a PLT (process instrumentation and control) device.

34. The MES device according to claim 32, wherein each process parameter of the monitoring and control system, which process parameter must be optimized and which process parameter is influenced by one or more optimization entities, is assigned an evaluation entity such that the optimization which is effected on the relevant process parameter by the corresponding optimization entities can be determined by the evaluation entity, so that an ROI (return of investment) value which is achieved by the relevant optimization entity can be determined online and/or in real time.

35. The MES device according to claim 32, wherein the or each evaluation entity has at least one evaluation module for automatically determining an ROI value of a respective process parameter, said ROI value being achieved by a respective optimization entity.

36. The MES device according to claim 32, wherein all evaluation entities are connected to an overall evaluation entity, such that the effected overall optimization of all process parameters, namely an overall ROI value of the MES device, can be determined online and/or in real time by the overall evaluation entity.

37. The MES device according to claim 32, wherein a display entity simultaneously displays the ROI values which have been achieved by the relevant optimization entities and the overall ROI value of the MES device online and/or in real time in a dynamic spider diagram.

38. A method for process optimization, comprising:

optimizing one or more process parameters by at least one optimization entity;

monitoring the process parameters by at least one monitoring entity; and

automatically determining the effected optimization of the or each process parameter by at least one evaluation entity.

39. The method according to claim 38, wherein a process parameter is optimized by one or more optimization entities, and wherein the optimization which is effected by each optimization entity for the relevant process parameter is determined online and/or in real time.

40. The method according to claim 38, wherein the effected overall optimization of all process parameters is determined online and/or in real time, and as an absolute and/or time-related quantity.