On-line Performance Monitoring of a Chemical Process

BP Chemicals/CPACT/MDC

Summary

•Will talk about application of multivariate SPC.

•A data visualisation system for overview of plant operation.

•Tried on Hull site plant.

•Will aid operators’ control of plant.

2

Introduction

• Plants have data overload.

• MSPC gives overview of plant operation on just a few graphs.

• PCA is used to compress correlated plant variables to just a few [PC’s].

• Technique was applied to the BP Hull A4 CO plant.

• Plant manufactures CO by steam reforming of nat. gas. CO is feedstock for acetic acid production.

3

Plant Schematic

Steam Natural Gas (desulphurised)

Reformer Heat

Water Removal MEA CO 2 Removal Cold Box Separation H 2 (NH 3 plant) CO (acetic acid plant) 4

MSPC

•Data point on PC scores plots represent plant status at that time.

• Data points due to plant problem appear outside a confidence ellipse.

• Problem points also show up using statistical measures (e.g. SPE and T 2 statistic) - distances from model.

• Problem points interrogated using contribution plots for causal variables.

5

First Model

• An MSPC model was built of “normal” operation for the A4 CO plant.

• The model used 27 main plant variables, including temperatures, pressures, flows and analyser results.

• Model training data was collected at 4 minute snapshots over a 1 week period of stable operation.

• 6 PC’s explains ~70% of variance. • This is effectively then used as a basis to compare future operation.

6

Off-line Analysis

•Using CPACT MultiDAT and PreScreen2 Software

Off-line Analysis of Operator Error

7

On-line with MDC

On-line Model, Feedstock Upset (N 2 )

•PC scores plots, statistics vs time, etc •Zoom in •Click on point to select contribution plot •Plus off-line tools for model building •Plus PLS and adaptive models 8

On-line with MDC

•Normalised •Greatest first •Scrollable •Click for time trend

Process Variable Contribution Plots Time Trend of a Process Variable

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Problems

• But plant operates at different rates.

• What data to use for model?

• What variables to use?

• Dynamic data – influenced by the past.

• Serially correlated (invalid control limits).

• Result – hard to find balance between alerts and false alarms.

• So concentrated on smaller section of plant & tried new techniques.

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Plant Section - MEA Upset in Column Level

3 2 1

Score & Statistics Plots

•Model for MEA (10 tags) •Has oscillation upset at high rates The Oscillation • Clusters 1, 2 and 3 represent different ‘modes’ of operation 11

Live Demo

• Live demo of MDC MSPC+ with the previous data for MEA.

12

Multi Rate Model

• Work by Ewan Mercer et al (CPACT Newcastle University).

• Model for MEA.

• Need models for different plant rates.

• Modes of operation seen as clusters.

• But better to collapse clusters together…

PC1 vs PC2 Scores Plot

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New Technique

• Also by Ewan Mercer et al.

• Based on plant model mismatch (PMM).

• Build state space model for MEA (1m data, I/P’s and O/P’s).

• Build PCA model on differences between predicted and actual plant data (residuals).

• Will effectively collapse clusters.

• Use standard MSPC graphs to monitor plant.

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Plant/Model Mismatch

Schematic of Technique 15

PCA on Residuals

• Model for multiple plant rates.

• Near normal distribution with low serial correlation.

• Picks up upset with fewer false alarms.

16

Parallel Coords

•Each y-axis is a plant variable •Each path is state of plant at one point in time •Another potential technique •Light ‘cluster’ is normal MEA operation •Other [darker] data is upset •Can also use to visualise many PC’s 17

Conclusion/Next Steps

• Model built for overview of the A4 CO plant.

• Tested on-line using

MDC’s MSPC+

software.

• Overview of plant operation with drill down.

• Picks up process problems and helps diagnose cause.

• Will improve running of plants.

• Gain site acceptance for deployment.

• Initially to see plant changes.

• Use alerting later with the new techniques (i.e. PMM).

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Acknowledgements

•

BP Hull Site

: • Steve Batty, Zaid Rawi et al.

•

CPACT/Newcastle University

: • Ewan Mercer, Julian Morris, Elaine Martin et al.

•

MDC

: • Chris Hawkins, Paul Booth et al.

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