Process Profiling: Investigation And Prediction Of Process Upsets With Advanced Diagnostics

Process Profiling: Investigation and Prediction of Process Upsets with Advanced Diagnostics
Bill Zhou – Marketing Engineer
Takayuki Aoyama – Instrument Group Leader

Presenters
Bill Zhou
Takayuki Aoyama

Agenda
Customer Challenges
Process Intelligence
Case Studies at Mitsubishi Chemical
Summary and Future of Diagnostics

Customer Challenges
“
I’m having trouble identifying sources of process variability.
“
I am tired of always reacting to issues and want a proactive plan.
“
I hate dealing with re-work or scrapping of product.

Recap of SPM Case Studies in 2008
SPM helped determined root-cause
Verified issue was fixed with SPM
Inadequate straight pipe length in DP flow measurement
Partial impulse line plugging caused by dirt
Fully plugged manifold
Compressor vibration issues

Agenda
Customer Challenges

See the Process Noise
Higher sampling rate leads to high resolution of process profile
Update Rate: 22 times / second
Update Rate: 1-2 times / second

Statistical Process Monitoring (SPM)
Tracks changing
process noise
levels
Tracks changes
in PV (i.e. what
the operator sees)
SPM Turns Process Noise Into Valuable Information
PV
2nd variable
3rd variable

The SPMTM Model
“Vision without action is a daydream. Action without vision is a nightmare.”
Japanese proverb

Agenda
Customer Challenges

Introduction of Mitsubishi Chemical
Mitsubishi Chemical Corp.
Found in June 1950
New operation started in 1994 by merging Mitsubishi Kasei and
Mitsubishi Petrochemical
Business: Petrochemical, Function Products, Health Care etc
Employees: 4,963 (non-consolidated)
39,305 (MCHC)
Mitsubishi Chemical Holdings Corporation (consolidated)
URL
http://www.mitsubishichem-hd.co.jp
http://www.m-kagaku.co.jp
1 billion Yen = US$ 10.8 million
Our company is the largest Chemical company in Japan
We provide petrochemical, functional chemical, medical, and information electronics products.
Mitsubishi Chemical was founded in 1950 and now we have about 40 thousand employees.
Net sales is approximately 30 billion US dollars.

Japan
Japan
Japan is the small country just next to China.
As you can see, it’s the small-small land on this slide.

Impression of Japan
Some people believe that NINJA or CHONMAGE people are walking around in Japan.
But this is not true.
You would not see the NINJA and the CHONMAGE people in Japan except for sumo wrestlers and comedians.

Petrochemical, Plastic products,
Pharmaceutical, Health care,
Information electronics products
Mitsubishi Chem.
Naoetsu
Mizushima
Kashima
Kurosaki
Tsukuba
Sakaide
Yokkaichi
Matsuyama
Kawasaki
Plant Map
Mitsubishi Chemical has 4 large petrochemical plants in Japan.
I work at the Kashima plant which is indicated with the red box in this slide.
I am responsible for the ethylene process in the plant.

SPM Case Studies for 2009
SPM enabled Predictive Maintenance
Entrained air of pump inlet suction line
Partial plugging in one of two impulse lines
New findings with SPM
SPM as indicator of strong winds
Pressure pulsation of switching feed line
Dryer Switching
Key findings and requests for Emerson
The last section is about requests for the future development SPM function.
I have divided my 5 case studies into 3 sections.
First section is useful for the maintenance practice.
Second section is new findings using SPM.

　
3051S
FC
Pumps
3051S
Transmitter
Control Valve
Case #1: The Problematic Pump
First case study is based on one of our normal pump systems.
We installed the 3051S pressure transmitter for this flow measurement.
There are three pumps and one control valve to maintain the discharge flow.

Flow rate [t/h]
Setpoint [kPa]
Valve position [%]
Stdev [kPa]
Abnormal situation
Trend of stdev, valve position, flow rate
Stdev value jumped when flow measurement decreased.
This trend chart shows the information collected from the pump process.
Light blue line shows the DCS output, green shows setpoint, and red is the standard deviation.
During normal operation, I noticed a sudden drop in flow rate.
When this happened, the standard deviation spiked.
This is when I started my investigation into what happened.

Flow rate [t/h]
Setpoint [kPa]
Valve position [%]
Motor ampere [A]
Stdev [kPa]
Flow rate
stdev
DCS output
Is it the Valve or is it the Pump??
(Flow should↑ when DCS output ↓)
We suspected either improper valve position or insufficient motor performance
This is a detailed view of the previous trend chart.
The drop in flow rate caused the DCS output to decrease because this loop was on auto.
I suspected this was due to valve malfunction so I monitored the actual valve position.

Motor ampere
Valve Position (no issue)
Flow rate
Stdev
No issue found on valve position
What we observed was:
Stdev ↑ when flow rate ↓, pump motor amp ↓
From this data, I determined there is no issue with the valve.
This means that the control valve is not guilty.
This leads us back to the pump.

Is Pump the Culprit?
CASE CLOSED
Entrained air through pump inlet
Stdev ↑ & pump motor amp ↓ prompted investigation on the pumps
Flow direction
Benefit from SPM information
・Future detection of entrained air
・Indicator of when to release air from the lines
When the process operator checked the filter of the pump,
they found that gas existed inside the pipes.
Therefore, we have found that the root cause is entrained air.
In the future, we will use the standard deviation as a future indicator of entrained air.

Motor ampere
Valve Position
Flow rate
Stdev
SPM can be used for future detection
SPM told us that “something was happening” before it affected the process.
SPM can be used for future indication of entrained air
Caused by entrained air
Let’s summarize the case.
When the air went against the pumps, the standard deviation increased quickly.
SPM showed this increment before decreasing the flow rate.
Through this experience, SPM has a possibility to make us know this trouble before the flow rate is affected.

Case #2: The Common Plugged Line
This line often has plugging issues. Thus we installed 3051S with SPM.
DCS output
Flow rate
The second case study is detecting plugged impulse lines.
This measurement has had plugging issues in the past.
Thus we installed the 3051S to detect the abnormal situation.

Trend of Plugged Line Detection
Behavior of this abnormal situation (aka process criminal) was unexpected
Stdev
Expected
Stdev
Valve position
Flow rate
Dropped down
This is the trend chart we collected for this application.
We expected the standard deviation to decrease due to the plugged impulse line.
But what I observed was totally unexpected, the standard deviation increased.

Further Investigation into Behavior of PLD
Expected ↓
Low
Low
Hi
Hi
Delta-P
Delta-P
However, if there are bubbles in the impulse line, the stdev can increase instead of expected decrease.
This is an illustration of what happens when there is a plug.
When there is a plug in one line, the process noise will decrease.
However, if there are bubbles in the line, the process noise will actually increase.
The previous trend chart shows this happening.

Simulation of plugging verified expected behavior – Decrease in stdev
CASE CLOSED
Plugged line detected
Flow rate
Normal Operation
Normal Operation
ok
ok
High side closed
Low side closed
Stdev
In order to confirm this behavior in our application,
we tested plugging by purging the bubbles and closing the lines leading to the transmitter.
This trend is the result of the test.
From this test, we can see that plugging in both low or high side resulted in decreased standard deviation.
Based on this data, we can say that there was bubble trapped inside the impulse line.
Key point here is that SPM detected something wrong in the process
even though standard deviation behaved unexpectedly.

Case #3: The Windy City
Fresh air inlet
Heat exchange
Charge gas
M
To the next
furnace
Heated
air
Feed
PDC
3051S
Air
Heater
Furnace
Emergency Exhaust
The third case study is based on the furnace air heater.
We have many furnaces and each furnace has the air heater system with it.
Fresh air is fed into the heater and heated air is supplied to the furnace.
The pressure inside of the heater is controlled by the pressure controller in DCS.
We installed Rosemount 3051S transmitter to look for any abnormal situations.

Stdev spiked while pressure measurement did not
Stdev [kPa]
Pressure [kPa]
pressure
Spiking of Stdev Prompted Investigation
Stdev spikes
After installing the 3051S, I analyzed the trend data of the furnace operation.
This chart shows that although the operation is normal,
sometimes the standard deviation spikes.

3051S transmitter
Picture of Furnace Heater
Heated air
Sampling nozzle
Emergency exhaust
This is the air heater.
Fresh air comes from the top vent of the heater and heated air is sent into the furnace.
Red circle in the picture here indicates the location of the 3051S transmitter.
Sampling nozzle is connected to the bottom of the heater near the emergency exhaust.

Picture of Furnace Heater
The pod is connected to the other sampling line to be less affected by wind
3051S
We installed the pod to avoid measurement distribution change due to the strong winds.
But it is difficult to remove the influence from the wind completely.

Pressure is also slightly affected
Stdev for furnaces
Pressure inside of furnace
Stdev affected when strong wind blew into the pod
Wind velocity
The Effects of Strong Wind
With the 3051S, we measured standard deviation and compared it to wind velocity.
When the wind became strong, the standard deviation increased.
During this time, the pressure measurement is also slightly affected.

Two adjacent furnaces
Stdev [kPa]
Pressure [kPa]
Affected by wind
Stdev only affected when strong wind blew directly into the pod.
Wind velocity [m/s]
This trend is the other data set.
When the wind velocity increased, the standard deviation changed at the same time.
Strong winds affect the reliability of the PV measurement.
We have found that standard deviation from SPM can detect this phenomenon.
Thus when this happens, we can change the operation from auto to manual to avoid process upset.

CASE CLOSED
Perturbed by wind
Pressure [kPa]
Setpoint [kPa]
Case #3 Summary
Strong winds affect reliable PV
Velocity [m/s]
Direction [-]
Wind velocity
wind direction
Benefit from SPM information
・Indicator of when to change to “Manual” operation due to unreliable dP measurement.
・Prevent unexpected process fluctuation by unstable measurement caused by the wind
When it is typhoon season in Kashima, our operators can predict the strong winds.
However, I believe that SPM is more reliable in prediction than listening to the weather man.

Open either valve
Other plant
User plant
(with Dryer)
3051S
FC
T
(w/o Dryer)
Turbine
Normally manual mode and fully opened
Case #4:Changing Feed Lines
The fourth case study is about switching feed lines.
The operator occasionally has to switch the feed lines manually based on production rate.
This happens about 3 to 4 times a year.

Influence on Stdev by changing the line
Flow rate [km3/h]
Stdev [kPa]
(with Dryer)
Line pressure [MPa]
(w/o Dryer)
Flow rate
Difficult to verify switching of the line by looking at flow rate.
About 0.8
After switching the lines
About 0.1
SPM provides better indication of process profile change.
After switching the feed lines, there is no quick indication that it was successful.
However, when I observed the standard deviation, it was clear the value changed.
The standard deviation changes quickly and provides a nice indication that the switch was successful.

Flow rate was also profiled
CASE CLOSED
Stdev is reliable indicator
Flow rate w/ Dryer
Flow rate
Freq.
Flow rate w/o Dryer
w/Dryer
Flow rate profile can also be observed, but Stdev is a faster indicator of completed switching
w/o Dryer
Distribution
[df/dt t/h]
This chart shows a longer trend of the flow profiles.
Here we can see that there is a clear indication of successful switching of the feed lines.
However, in order to draw this chart, it requires a longer period of time for sampling the data.

FC
Case Study #5 Dryer Switching
3051S
PI
dryer
A
3051S
B
In this process, we switch the dryer operation every 20 days.
We installed 2 units of 3051S to monitor static pressure and flow measurement of this process.

Switching Dryer Operation Affects Stdev
CASE OPEN
Case Open: On-going investigation into WHY Stdev cycles with switching
Stdev of pressure transmitter
Switch over every 20 days
Stdev of flow transmitter
The process profile of the transmitters showed similar pattern before and after switching dryer operation.
I am not sure why there is such a pattern.
Thus, this interesting case is still under investigation.

Summary of Process Profiling
Key findings
SPM enables Predictive Maintenance
SPM is applicable to many applications
we will increase installation to broaden the monitoring coverage
Request to Emerson
Expedite to market diagnostic for loop
Detect capillary plugging
Detect Hydrogen penetration of Diaphragm
Detect Leak of seal fluid in Diaphragm
More sensitive detection for single line plugs
In summary, I found that SPM can enable predictive maintenance
and it’s also useful to detect slight changes in the process.
I am planning to increase SPM usage to broaden the process coverage and discover other applications.
I would like to share with you some requests to Emerson on future diagnostic developments.

Agenda
Customer Challenges

Loop Power & Connectivity
Diagnostic Coverage Beyond the Transmitter
Transmitter Health
Safety Certified

Transmitter Health
SIS
Safety Certified
Benefits
Plugged
Impulse
Line(s)
Flame
Instability
Loop Power & Integrity
25
Applications
Entrained
Air
Agitation
Loss
Looking Beyond the Device to Deliver More Process Intelligence

Transmitter Health
BAD
SIS
Safety Certified
Voice of the
Customer
Benefits
X
+
Failing power supply
_
X
Wiring issues
X
Water &
Corrosion
Looking Beyond the Device Verifying Loop Power and Integrity

SIS
Safety Certified
Benefits
Transmitter Health
Status Event
Time Since Event
Output Saturated
High Variation Alert
Temperature not updating
Output Saturated
LCD Update error
Output Saturated
Mean Change Detected
Temperature not updating
Output Saturated
Cold Start
00:013:11:01:37
00:013:11:31:37
00:013:16:01:33
00:013:23:05:00
00:013:41:11:23
00:015:23:32:47
00:016:58:16:37
00:023:23:54:38
00:123:16:24:67
00:153:57:14:32
Diagnostic Status Log
Enhance Transmitter Health and Process Insight with Historical Event Log

SIS
Benefits
Safety Certified
Safety Certified to single use in SIL2 or multiple use in SIL3
SIL3 Power &
Process Diagnostics
10 Year Proof
Test Interval
Transmitter Health
Advanced Diagnostics Enable the Safest Pressure Installation

Where To Get More Information
Come see a live demonstration at the technology exhibit!
Rosemount 3051S Advanced Diagnostics on the web
www.Rosemount.com/3051SDiagnostics

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Process Profiling: Investigation And Prediction Of Process Upsets With Advanced Diagnostics

by Jim Cahill on Feb 26, 2010

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Process Profiling: Investigation And Prediction Of Process Upsets With Advanced Diagnostics — Presentation Transcript