does your dcs deliver? a tutorial on measuring …standards certification education & training...

Standards

Certification

Education & Training

Publishing

Conferences & Exhibits

Does Your DCS Deliver?

A Tutorial on Measuring

Control Performance

George Buckbee, P.E.

ExperTune, Inc.

2

Presenter

• George Buckbee is V.P. of Product Development at

ExperTune. George holds a B.S. in Chemical

Engineering from Washington University in St. Louis, and

an M.S. in Chemical Engineering from the University of

California at Santa Barbara. His 25 years of industry

experience have been focused in the field of process

control. George is the author of several books, and

dozens of articles. In 2011, George was selected as an

ISA Fellow.

Abstract

Does Your DCS Deliver?

• Industry guru Peter Drucker once said “You can’t control what you don’t measure, and you can’t

manage what you don’t control.” A Distributed Control System (DCS) is an investment that needs

to be managed, controlled, and measured.

• A Distributed Control System (DCS), along with instrumentation and control valves may cost tens

of millions of dollars. Management rightly wants to know about the control system performance,

and especially the return on the investment. Yet many plants do not measure any aspects of

control performance.

• That trend is changing, however, with modern tools and techniques that can be used to document

the specifics of control system performance. This tutorial explains methods to measure and

monitor control performance, and provides useful tips for improving plant results such as quality,

safety, energy costs, and production.

• This presentation will start with the basics of simple statistical performance measurement, then

progress through more sophisticated techniques, including evaluation of controller dynamic

performance and oscillations. The presentation will cover selecting performance metrics that are

measurable, meaningful, and actionable. Finally, the audience will learn how to combine simple

performance measures into powerful diagnostics for instrumentation, valves, and controllers.

• While sophisticated analysis is presented, this presentation does not require an extensive

mathematical background. Operations management, process and control engineers, and

instrument technicians will all benefit from this discussion.

• When controller performance is measured, many process and control improvements become

instantly obvious. Attendees at this presentation will return to their plants armed with techniques

for measuring, controlling, and improving the performance of their control systems.

3

Agenda

Motivations

What is Control System Performance?

Measuring Control System Performance

Diagnostics and Corrective Actions

Conclusions, Q&A

4

Motivations:

The Purpose of Control Systems

• What is the Purpose of a Control System?

5

Reduce Effect of Disturbances

Ensure Stability

Optimize the Process

Ref #1

Motivations

• Isn’t it good enough?

6

7#

Motivations:

Typical Control System Performance

Typical Statistics

• 10% - 90% Control Loops in Manual

• 30% Control Valves with Problems

• 30% Loops-Tuning is completely wrong

• 40% Loops Oscillating

• Improper PID Loop Configuration

– 30% DCS Systems

– 95% PID on PLC’s

• 85% Sub-Optimal Tuning

• 75% Control Loops increase variability

Agenda

Motivations

What is Control System Performance?

Measuring Control System Performance

Diagnostics and Corrective Actions

Conclusions, Q&A

8

The Purpose of Control:

Reducing the Effect of Disturbances

• Variation in Raw

Material

• Weather

• Operations

• Batch Operations

• Process Conditions

9

The Purpose of Control:

Ensure Stability

• Thermal Processes

• Tank Overflows

• Pressure

• Chemical Reactions

• pH

10

The Purpose of Control:

Optimize the Process

• Drive Toward

Optimum

• Hold at Best Setpoint

11

Agenda

Motivations

What is Control System Performance?

Measuring Control System Performance

Diagnostics and Corrective Actions

Conclusions, Q&A

12

Measuring Control Performance

13

How do you know if your control system is

living up to it’s purpose?

“You can’t manage what

you can’t control, and you

can’t control what you don’t

measure.”

Measuring Control Performance

• Criteria for Good Real-Time Performance Measures:

14

• Affects the Bottom Line

• Easily UnderstoodMeaningful

• Can be Measured

• In Real Time, 24 x 7Measurable

• Direct Actions

• Immediate ResultsActionable

15#

Guidance for Tracking & Managing

Control System Performance Data

• Match Business Objectives with Metrics

• Cover Each Unit Fully

– Most Upsets Come from Unexpected Places

• Integrate the Information Into Business Processes

• Follow-Up

• Document the Benefits

16#

Guidance for

Capturing Control System Performance Data

• Capture Data in Real-Time

• Metrics Should be:

– Measurable

– Meaningful

– Actionable

• Diagnostics Built on These Metrics

– Instrument & Valve Failures

– Loss of Control

– Cause of Oscillation

• Historize, Track, Drill Down, etc.

Finding Root Cause

• Process vs. Instrument vs. Valve vs. Control

17

Measure Decide Action

Jin Real Time

Agenda

Motivations

What is Control System Performance?

Measuring Control System Performance

Diagnostics and Corrective Actions

Conclusions, Q&A

18

Equipment Diagnostics :

Instrumentation

• Dead Instrument

PV Max = PV Min

19

Equipment Diagnostics:

Instrumentation

• Spiking

20

Equipment Diagnostics:

Oversized Valves

21

Process & Control Oscillations

• Oscillation Period

– Fourier Transform

• Oscillation Shape

• Focus on Root

Cause

22

What is “Good” Tuning?

• Flat Line?

• Fast SP Change?

• No Overshoot?

• Quarter Amplitude Damping?

• Fast disturbance rejection?

• Don’t move valve too much?

Automated Tuning Methods

• Look for Bumps 24 x 7

• Automatically Model & Tune

• Compare to Existing Tuning

24

Hours

Minutes

Making the Fix!

• Fix the Right Thing

• Follow-Up

• Document the Results

25

Difficult Problems – Interactions

26

27#

Motivations:

Why Does it Matter?

• These Metrics:

– Significant Oscillations

– Variability

– Service Factor

– Opportunity Gap

– Controllability

– Valve Travel

– J

• Directly Impact:

– Energy Cost

– Quality

– Safety/Environmental

– Cost

– Waste, Recycle

– Maintenance Costs

– J

Case Study:

The Challenge

• Distillation Column Swings

• Issues with newly-installed MPC controls when running

at different feed rates rather than design rates

Oscillations When MPC Is Active

Impact of Column Swings

Process Interaction Analysis

(example shown without proprietary data)

Tuning of Pressure Controller

Case Study Results:

Stability, MPC, Steam

Agenda

Motivations

What is Control System Performance?

Measuring Control System Performance

Diagnostics and Corrective Actions

Conclusions, Q&A

34

Conclusions:

Possible Improvements

35

Infrastructure Ensure

Performance

Optimize

Data Historian

OPC Server

Control Performance

Monitoring

Alarm

Management

Process

Modeling

APC /

MPC

KPIs

Conclusions

1. Process Control Systems are not deliveringtheir

full benefit. There is significant business

opportunity in:a. Technical Measures

b. Proven Business Benefit

2. Continuous Improvement Requires:

a. Monitor 24x7

b. Diagnose

c. Prioritize

d. Resolve

36

37Thank You!

References

1. Stephanopoulos, George. Chemical Process Control,

Prentice-Hall, New Jersey, 1984

2. Buckbee, George, and Gordon, Lew. “True Control

System Objectives”, InTech. Sept 2009

3. Buckbee, George. Finding the Source of Cycling In

Process Plants. White Paper, 2010.

4. Buckbee, George. Finding the Root Cause of Process

Upsets. White Paper, 2010

38