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1. (WO2019028020) REFINERY OR PETROCHEMICAL PLANT PROCESS PERFORMANCE IMPROVEMENTS.
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CLAIMS

What is claimed is:

1. A method for enhancing operational efficiency of a chemical plant, the method comprising:

receiving, by a computing device and from one or more thermocouples affixed to one or more tubes inside a furnace of a chemical plant, measured surface temperature data for the one or more tubes inside the furnace;

providing, by the computing device, the measured surface temperature data to a database configured to store the measured surface temperature data;

analyzing, by the computing device, the measured surface temperature data for completeness by identifying gaps in the measured surface temperature data based on a measurement interval;

correcting, by the computing device, the measured surface temperature data for overall mass balance closure;

generating, by the computing device, reconciled surface temperature data; using, by the computing device, the measured surface temperature data to determine whether an upset occurred;

determining, by the computing device, a model fitting parameter for a process model for the chemical plant based on the reconciled surface temperature data;

adjusting, by the computing device, a cut point of the chemical plant or a tray efficiency of the chemical plant to minimize differences between measured performance of the chemical plant and predicted performance of the chemical plant; optimizing, by the computing device, the process model using the model fitting parameter for the process model for the chemical plant;

determining, by the computing device, a maximum capacity of the furnace based on the measured surface temperature data for the one or more tubes inside the furnace;

using, by the computing device, a design of a device of the chemical plant to calculate a fraction of an available capacity of the device of the chemical plant that is currently being used;

generating, by the computing device and for interactive display, one or more detail screens relating the reconciled surface temperature data to operational performance of the one or more tubes inside the furnace;

sending, by the computing device, a report showing actual performance of the chemical plant compared to predicted performance of the chemical plant;

providing, by the computing device, alternatives for improving or modifying future operations of the chemical plant, the alternatives comprising operational changes and revamp modifications to generate improved performance of the chemical plant; and

recommending, by the computing device, target operational parameters of a final product of the chemical plant.

2. The method of claim 1, comprising:

using a partial least squares (PLS) analysis or an orthogonal PLS (OPLS) analysis to generate a trustworthiness score of the process model for the chemical plant based on a comparison between the operational parameters related to the process of the chemical plant.

3. The method of claim 2, comprising:

creating a scoring model that is used for generating the trustworthiness score of the process model.

4. The method of claim 3, comprising:

weighting the trustworthiness score using one or more factors and based on a difference between the operational parameters related to the process of the chemical plant and corresponding one or more threshold values, wherein the one or more factors comprise an accuracy of a primary measuring sensor or an age of a measurement.

5. The method of claim 4, comprising:

updating the scoring model with the weighted trustworthiness score; and

adjusting the process model for the chemical plant based on the scoring model.

6. The method of claim 1, comprising:

creating, by the computing device, a scoring model; and

using the scoring model to generate, by the computing device, a trustworthiness score of the process model for the chemical plant based on a comparison between operational parameters related to a process of the chemical plant.

7. The method of claim 6, comprising:

weighting, by the computing device, the trustworthiness score using one or more factors and based on a difference between the operational parameters related to the process of the chemical plant and corresponding one or more threshold values, the one or more factors comprising an age of a measurement;

updating, by the computing device, the scoring model with the weighted trustworthiness score; and

adjusting, by the computing device, the process model for the chemical plant based on the scoring model.

8. The method of any of claims 1-7, comprising:

performing a heuristic analysis against the measured surface temperature data and performance process model results from the process model.

9. A computer program comprising instructions arranged such that when executed by one or more computers, the instructions cause the one or more computers to perform the method of any of claims 1-8.

10. A computer-readable medium storing the computer program according to claim 9.

11. A system for enhancing operation of a chemical plant, the system comprising:

a furnace comprising one or more tubes inside the furnace;

one or more thermocouples affixed to the one or more tubes inside the furnace;

a fractionation column;

a reboiler associated with the fractionation column;

a receiver associated with the fractionation column;

a feed exchanger associated with the fractionation column;

an interface platform comprising:

one or more processors of the interface platform;

a communication interface of the interface platform and in communication with the one or more thermocouples affixed to the one or more tubes inside the furnace; and

non-transitory computer-readable memory storing executable instructions that, when executed by the one or more processors of the interface platform, cause the interface platform to:

receive, from the one or more thermocouples, measured surface temperature data for the one or more tubes inside the furnace; and

provide the measured surface temperature data to a database configured to store the measured surface temperature data;

an optimization platform comprising:

one or more processors of the optimization platform;

a communication interface of the optimization platform and in communication with the interface platform; and

non-transitory computer-readable memory storing executable instructions that, when executed by the one or more processors of the optimization platform, cause the optimization platform to:

receive, via the interface platform, the measured surface temperature data;

analyze the measured surface temperature data for completeness by identifying gaps in the measured surface temperature data based on a measurement interval;

correct the measured surface temperature data for overall mass balance closure;

generate reconciled surface temperature data;

use the measured surface temperature data to determine whether an upset occurred;

determine a model fitting parameter for a process model for the chemical plant based on the reconciled surface temperature data;

adjust a cut point of the chemical plant or a tray efficiency of the chemical plant to minimize differences between measured performance of the chemical plant and predicted performance of the chemical plant;

optimize the process model using the model fitting parameter for the process model for the chemical plant;

determine a maximum capacity of the furnace based on the measured surface temperature data for the one or more tubes inside the furnace; and use a design of a device of the chemical plant to calculate a fraction of an available capacity of the device of the chemical plant that is currently being used;

an analysis platform comprising:

one or more processors of the analysis platform;

a communication interface of the analysis platform and in communication with the interface platform; and

non-transitory computer-readable memory storing executable instructions that, when executed by the one or more processors of the analysis platform, cause the analysis platform to:

receive historical performance data for the chemical plant; establish relationships between operational parameters related to a process of the chemical plant;

analyze the historical performance data for the chemical plant as trends over time to identify key indicators of process problems for the process of the chemical plant;

determine target operational parameters of a final product of the chemical plant based on the historical performance data for the chemical plant; and

predict a limit of the process of the chemical plant based on the target operational parameters of the final product of the chemical plant; and an interaction platform comprising:

one or more processors of the interaction platform;

a communication interface of the interaction platform and in communication with the interface platform; and

non-transitory computer-readable memory storing executable instructions that, when executed by the one or more processors of the interaction platform, cause the interaction platform to:

generate, for interactive display to a plant operator of the chemical plant, one or more detail screens relating the reconciled surface temperature data to operational performance of the one or more tubes inside the furnace; send a report showing actual performance of the chemical plant compared to predicted performance of the chemical plant;

provide, to the plant operator of the chemical plant, alternatives for improving or modifying future operations of the chemical plant, the alternatives comprising operational changes and revamp modifications to generate improved performance of the chemical plant; and

recommend, to the plant operator of the chemical plant, the target operational parameters of the final product of the chemical plant.

12. The system of claim 11, comprising:

a prediction platform comprising:

one or more processors of the prediction platform;

a communication interface of the prediction platform and in communication with the interface platform; and

non-transitory computer-readable memory storing executable instructions that, when executed by the one or more processors of the prediction platform, cause the prediction platform to:

use a partial least squares (PLS) analysis or an orthogonal PLS (OPLS) analysis to generate a trustworthiness score of the process model for the chemical plant based on a comparison between the operational parameters related to the process of the chemical plant.

13. The system of claim 12, wherein the non-transitory computer-readable memory of the prediction platform stores further executable instructions that, when executed by the one or more processors of the prediction platform, cause the prediction platform to:

create a scoring model that is used for generating the trustworthiness score of the process model; and

weight the trustworthiness score using one or more factors and based on a difference between the operational parameters related to the process of the chemical plant and corresponding one or more threshold values, wherein the one or more factors comprise an accuracy of a primary measuring sensor or an age of a measurement.

14. The system of claim 13, wherein the non-transitory computer-readable memory of the prediction platform stores further executable instructions that, when executed by the one or more processors of the prediction platform, cause the prediction platform to:

update the scoring model with the weighted trustworthiness score; and

adjust the process model for the chemical plant based on the scoring model.

15. The system of claim 11, comprising:

a reconciliation platform comprising:

one or more processors of the reconciliation platform;

a communication interface of the reconciliation platform and in communication with the interface platform; and

non-transitory computer-readable memory storing executable instructions that, when executed by the one or more processors of the reconciliation platform, cause the reconciliation platform to:

receive the measured surface temperature data for the one or more tubes inside the furnace; and

perform a heuristic analysis against the measured surface temperature data and performance process model results from the process model.