Method and device for optimizing processes

• US 8,126,573 B2
• Filed: 08/11/2003
• Issued: 02/28/2012
• Est. Priority Date: 08/23/2002
• Status: Expired due to Fees

• Current Assignee: Siemens AG
• Original Assignee: Siemens AG
• Inventors: Bouriant, Alexandre
• Primary Examiner(s): Decady, Albert
• Assistant Examiner(s): Lin, Jason
• Application Number:
  US10/524,950
• Publication Number:
  US 20060010018A1
• Time in Patent Office: 3,123 Days
• Field of Search: 700/1, 700/291, 700/28, 700/36, 705/7, 705/7.37, 705/7.38, 705/7.11, 705/7.12, 705/7.29, 705/7.17
• US Class Current: 700/1
• 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. A device for process optimization, comprising:

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

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

at least one evaluation entity for automatically determining an optimization of the process parameter, each evaluation entity comprises at least one evaluation module, a number of evaluation models is determined by a number of optimization entities that influence a particular process parameter with each evaluation module comprising a comparator to compare a reference value of a specific process parameter with an actual value of the process parameter and a first multiplier configured to apportion a difference between the reference value and the actual value using a third input quantity, the value determined by the multiplier forms an output quantity of the evaluation entity,

an integrator configured to integrate the output quantity provided by the first multiplier over a time period defined by a reference time and a current time to produce an output value, a second multiplier having at least one input external the at least one evaluation entity that is a percentage factor by which a specific optimization entity exerts influence on the process parameter, the percentage factor is multiplied with the output value from the integrator to produce an apportioned optimization output value; and

a memory device configured to retain a difference between the reference value and the actual value prior to supplying the difference to the multiplier;

wherein the apportioned optimization output value is applied to the process parameter per optimization entity when more than one optimization entity is utilized.

2. The device according to claim 1, 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.

3. The device according to claim 1, 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.

4. The device according to claim 3, 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.

5. The device according to claim 3, 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.

6. The device according to claim 3, 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.

7. The device according to claim 1, 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.

8. The device according to claim 1, wherein at least one time normalization entity is provided for normalizing time quantities.

9. The device according to claim 1, wherein at least one process-quantity normalization entity is provided for normalizing all process quantities which are used by all entities.

10. The device according to claim 9, wherein the process-quantity normalization entity is used for normalizing variables and/or parameters.

11. The device according to claim 1, 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.

12. The device according to claim 11, 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.

13. 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 to determine variables necessary for determining optimization success;

at least one evaluation entity for automatically determining an optimization of the process parameter, each evaluation entity comprises at least one evaluation module, a specific number of evaluation models is determined by a number of optimization entities that influence a particular process parameter, each evaluation module comprising a comparator to compare a reference value of a specific process parameter with an actual value of the process parameter and a first multiplier configured to apportion a difference between the reference value and the actual value using a third input quantity, the value determined by the multiplier forms an output quantity of the evaluation entity, an integrator configured to integrate the output quantity provided by the first multiplier over a time period defined by a reference time and a current time to produce an output value, a second multiplier having at least one input external the at least one evaluation entity that is a percentage factor by which a specific optimization entity exerts influence on the process parameter, the percentage factor is multiplied with the output value from the integrator to produce an apportioned optimization output value; and

a memory device configured to retain a difference between the reference value and the actual value prior to supplying the difference to the multiplier;

wherein the apportioned optimization output value is applied to the process parameter per optimization entity when more than one optimization entity is utilized.

14. The MES device according to claim 13, 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.

15. The MES device according to claim 13, 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.

16. The MES device according to claim 13, 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.

17. The MES device according to claim 13, 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.

18. The MES device according to claim 13, 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.

19. A method for process optimization, comprising:

optimizing one or more process parameters by at least one optimization entity by comparing a reference value of a specific process parameter with an actual value of the process parameter;

determining an exact number of the at least one optimization entities used to optimize a specific process parameter;

apportioning a difference between the reference value and the actual value specific to each optimization entity based on how many are used to optimize the specific process parameter;

integrating a value provided by a multiplier over a time period to produce an output value specific to each optimization entity based on how many optimization entities are used to optimize the specific process parameter;

multiplying at least one input external entity that is a percentage factor by which a specific optimization entity exerts influence on the specific process parameter with the output value to produce an apportioned optimization output value;

retaining a difference between the reference value and the actual value prior to supplying the difference to the multiplier;

applying the apportioned optimization output value to the specific optimization entity when more than one optimization entity is provided to designate a percentage each optimization entity should provide to the specific process parameter;

monitoring the process parameters by at least one monitoring entity that produces a multi-axis spider diagram, each axis is associated with a process parameter;

automatically determining the optimization of the process parameters by at least one evaluation entity with values obtained from the multiplier.

20. The method according to claim 19, 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.

21. The method according to claim 19, wherein the effected optimization of all process parameters is determined online and/or in real time, and as an absolute and/or time-related quantity.

22. The method according to claim 19, wherein when more than the at least one optimization entity is provided, each percentage factor, associated with a cumulative number of optimization entities, may not cumulatively exceed 1.