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


2009 HART Plant of the Year Award winner Mitsubishi Chemical Corporation Uses HART Technology to Detect Abnormal Situations and Failures before they Affect the …

2009 HART Plant of the Year Award winner Mitsubishi Chemical Corporation Uses HART Technology to Detect Abnormal Situations and Failures before they Affect the Process

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  • 1. Process Profiling: Investigation and Prediction of Process Upsets with Advanced Diagnostics
    Bill Zhou – Marketing Engineer
    Takayuki Aoyama – Instrument Group Leader
  • 2. Presenters
    • Bill Zhou
    • 3. Takayuki Aoyama
  • Agenda
    Customer Challenges
    Process Intelligence
    Case Studies at Mitsubishi Chemical
    Summary and Future of Diagnostics
  • 4. 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.
  • 5. 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
  • 6. Agenda
    Customer Challenges
    Process Intelligence
    Case Studies at Mitsubishi Chemical
    Summary and Future of Diagnostics
  • 7. 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
  • 8. Statistical Process Monitoring (SPM)
    Tracks changing
    process noise
    Tracks changes
    in PV (i.e. what
    the operator sees)
    SPM Turns Process Noise Into Valuable Information
    2nd variable
    3rd variable
  • 9. The SPMTM Model
    “Vision without action is a daydream. Action without vision is a nightmare.”
    Japanese proverb
  • 10. Agenda
    Customer Challenges
    Process Intelligence
    Case Studies at Mitsubishi Chemical
    Summary and Future of Diagnostics
  • 11. 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)
    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.
  • 12. Japan
    Japan is the small country just next to China.
    As you can see, it’s the small-small land on this slide.
  • 13. 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.
  • 14. Petrochemical, Plastic products,
    Pharmaceutical, Health care,
    Information electronics products
    Mitsubishi Chem.
    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.
  • 15. 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.
  • 16.  
    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.
  • 17. 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.
  • 18. Flow rate [t/h]
    Setpoint [kPa]
    Valve position [%]
    Motor ampere [A]
    Stdev [kPa]
    Flow rate
    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.
  • 19. Motor ampere
    Valve Position (no issue)
    Flow rate
    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.
  • 20. Is Pump the Culprit?
    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.
  • 21. Motor ampere
    Valve Position
    Flow rate
    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.
  • 22. 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.
  • 23. Trend of Plugged Line Detection
    Behavior of this abnormal situation (aka process criminal) was unexpected
    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.
  • 24. Further Investigation into Behavior of PLD
    Expected ↓
    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.
  • 25. Simulation of plugging verified expected behavior – Decrease in stdev
    Plugged line detected
    Flow rate
    Normal Operation
    Normal Operation
    High side closed
    Low side closed
    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.
  • 26. Case #3: The Windy City
    Fresh air inlet
    Heat exchange
    Charge gas
    To the next
    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.
  • 27. Stdev spiked while pressure measurement did not
    Stdev [kPa]
    Pressure [kPa]
    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.
  • 28. 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.
  • 29. Picture of Furnace Heater
    The pod is connected to the other sampling line to be less affected by wind
    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.
  • 30. 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.
  • 31. 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.
    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.
  • 33. Open either valve
    Other plant
    User plant
    (with Dryer)
    (w/o Dryer)
    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.
  • 34. 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.
  • 35. Flow rate was also profiled
    Stdev is reliable indicator
    Flow rate w/ Dryer
    Flow rate
    Flow rate w/o Dryer
    Flow rate profile can also be observed, but Stdev is a faster indicator of completed switching
    w/o Dryer
    [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.
  • 36. FC
    Case Study #5 Dryer Switching
    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.
  • 37. Switching Dryer Operation Affects Stdev
    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.
  • 38. 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.
  • 39. Agenda
    Customer Challenges
    Process Intelligence
    Case Studies at Mitsubishi Chemical
    Summary and Future of Diagnostics
  • 40. Loop Power & Connectivity
    Diagnostic Coverage Beyond the Transmitter
    Transmitter Health
    Safety Certified
    Process Intelligence
  • 41. Transmitter Health
    Safety Certified
    Process Intelligence
    Loop Power & Integrity
    Looking Beyond the Device to Deliver More Process Intelligence
  • 42. Transmitter Health
    Safety Certified
    Process Intelligence
    Voice of the
    Loop Power & Integrity
    Failing power supply
    Wiring issues
    Water &
    Looking Beyond the Device Verifying Loop Power and Integrity
  • 43. SIS
    Safety Certified
    Process Intelligence
    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
    Diagnostic Status Log
    Loop Power & Integrity
    Enhance Transmitter Health and Process Insight with Historical Event Log
  • 44. SIS
    Process Intelligence
    Loop Power & Integrity
    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
  • 45. Where To Get More Information
    Come see a live demonstration at the technology exhibit!
    Rosemount 3051S Advanced Diagnostics on the web