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


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

  1. 1. Process Profiling: Investigation and Prediction of Process Upsets with Advanced Diagnostics<br />Bill Zhou – Marketing Engineer<br />Takayuki Aoyama – Instrument Group Leader<br />
  2. 2. Presenters<br /><ul><li>Bill Zhou
  3. 3. Takayuki Aoyama</li></li></ul><li>Agenda<br />Customer Challenges<br />Process Intelligence<br />Case Studies at Mitsubishi Chemical<br />Summary and Future of Diagnostics<br />
  4. 4. Customer Challenges<br />“<br />I’m having trouble identifying sources of process variability.<br />“<br />I am tired of always reacting to issues and want a proactive plan.<br />“<br />I hate dealing with re-work or scrapping of product.<br />
  5. 5. Recap of SPM Case Studies in 2008<br />SPM helped determined root-cause<br />Verified issue was fixed with SPM<br />Inadequate straight pipe length in DP flow measurement<br />Partial impulse line plugging caused by dirt<br />Fully plugged manifold<br />Compressor vibration issues<br />
  6. 6. Agenda<br />Customer Challenges<br />Process Intelligence<br />Case Studies at Mitsubishi Chemical<br />Summary and Future of Diagnostics<br />
  7. 7. See the Process Noise<br />Higher sampling rate leads to high resolution of process profile<br />Update Rate: 22 times / second<br />Update Rate: 1-2 times / second<br />
  8. 8. Statistical Process Monitoring (SPM)<br />Tracks changing<br />process noise<br />levels<br />Tracks changes<br />in PV (i.e. what<br />the operator sees)<br />SPM Turns Process Noise Into Valuable Information<br />PV<br />2nd variable<br />3rd variable<br />
  9. 9. The SPMTM Model<br />“Vision without action is a daydream. Action without vision is a nightmare.”<br />Japanese proverb<br />
  10. 10. Agenda<br />Customer Challenges<br />Process Intelligence<br />Case Studies at Mitsubishi Chemical<br />Summary and Future of Diagnostics<br />
  11. 11. Introduction of Mitsubishi Chemical<br />Mitsubishi Chemical Corp.<br />Found in June 1950<br />New operation started in 1994 by merging Mitsubishi Kasei and <br /> Mitsubishi Petrochemical<br />Business: Petrochemical, Function Products, Health Care etc<br />Employees: 4,963 (non-consolidated)<br />39,305 (MCHC)<br />Mitsubishi Chemical Holdings Corporation (consolidated)<br />URL<br /><br /><br />1 billion Yen = US$ 10.8 million<br />Our company is the largest Chemical company in Japan<br />We provide petrochemical, functional chemical, medical, and information electronics products. <br />Mitsubishi Chemical was founded in 1950 and now we have about 40 thousand employees. <br />Net sales is approximately 30 billion US dollars. <br />
  12. 12. Japan<br />Japan<br />Japan is the small country just next to China. <br />As you can see, it’s the small-small land on this slide.<br />
  13. 13. Impression of Japan<br />Some people believe that NINJA or CHONMAGE people are walking around in Japan.<br />But this is not true.<br />You would not see the NINJA and the CHONMAGE people in Japan except for sumo wrestlers and comedians.<br />
  14. 14. Petrochemical, Plastic products,<br />Pharmaceutical, Health care,<br />Information electronics products<br />Mitsubishi Chem.<br />Naoetsu<br />Mizushima<br />Kashima<br />Kurosaki<br />Tsukuba<br />Sakaide<br />Yokkaichi<br />Matsuyama<br />Kawasaki<br />Plant Map<br />Mitsubishi Chemical has 4 large petrochemical plants in Japan.<br />I work at the Kashima plant which is indicated with the red box in this slide. <br />I am responsible for the ethylene process in the plant.<br />
  15. 15. SPM Case Studies for 2009<br />SPM enabled Predictive Maintenance<br />Entrained air of pump inlet suction line <br />Partial plugging in one of two impulse lines<br />New findings with SPM <br />SPM as indicator of strong winds<br />Pressure pulsation of switching feed line<br />Dryer Switching<br />Key findings and requests for Emerson<br />The last section is about requests for the future development SPM function.<br />I have divided my 5 case studies into 3 sections.<br />First section is useful for the maintenance practice.<br />Second section is new findings using SPM.<br />
  16. 16.  <br />3051S<br />FC<br />Pumps<br />3051S<br />Transmitter<br />Control Valve<br />Case #1: The Problematic Pump<br />First case study is based on one of our normal pump systems.<br />We installed the 3051S pressure transmitter for this flow measurement.<br />There are three pumps and one control valve to maintain the discharge flow.<br />
  17. 17. Flow rate [t/h]<br />Setpoint [kPa]<br />Valve position [%]<br />Stdev [kPa]<br />Abnormal situation<br />Trend of stdev, valve position, flow rate<br />Stdev value jumped when flow measurement decreased.<br />This trend chart shows the information collected from the pump process.<br />Light blue line shows the DCS output, green shows setpoint, and red is the standard deviation.<br />During normal operation, I noticed a sudden drop in flow rate.<br />When this happened, the standard deviation spiked.<br />This is when I started my investigation into what happened.<br />
  18. 18. Flow rate [t/h]<br />Setpoint [kPa]<br />Valve position [%]<br />Motor ampere [A]<br />Stdev [kPa]<br />Flow rate<br />stdev<br />DCS output<br />Is it the Valve or is it the Pump??<br />(Flow should↑ when DCS output ↓)<br />We suspected either improper valve position or insufficient motor performance<br />This is a detailed view of the previous trend chart.<br />The drop in flow rate caused the DCS output to decrease because this loop was on auto.<br />I suspected this was due to valve malfunction so I monitored the actual valve position.<br />
  19. 19. Motor ampere<br />Valve Position (no issue)<br />Flow rate<br />Stdev<br />No issue found on valve position<br />What we observed was:<br />Stdev ↑ when flow rate ↓, pump motor amp ↓<br />From this data, I determined there is no issue with the valve.<br />This means that the control valve is not guilty.<br />This leads us back to the pump.<br />
  20. 20. Is Pump the Culprit?<br />CASE CLOSED<br />Entrained air through pump inlet<br />Stdev ↑ & pump motor amp ↓ prompted investigation on the pumps<br />Flow direction<br />Benefit from SPM information<br />・Future detection of entrained air<br />・Indicator of when to release air from the lines<br />When the process operator checked the filter of the pump,<br />they found that gas existed inside the pipes. <br />Therefore, we have found that the root cause is entrained air.<br />In the future, we will use the standard deviation as a future indicator of entrained air.<br />
  21. 21. Motor ampere<br />Valve Position<br />Flow rate<br />Stdev<br />SPM can be used for future detection<br />SPM told us that “something was happening” before it affected the process. <br />SPM can be used for future indication of entrained air<br />Caused by entrained air<br />Let’s summarize the case.<br />When the air went against the pumps, the standard deviation increased quickly.<br />SPM showed this increment before decreasing the flow rate.<br />Through this experience, SPM has a possibility to make us know this trouble before the flow rate is affected.<br />
  22. 22. Case #2: The Common Plugged Line<br />This line often has plugging issues. Thus we installed 3051S with SPM. <br />DCS output<br />Flow rate<br />The second case study is detecting plugged impulse lines.<br />This measurement has had plugging issues in the past.<br />Thus we installed the 3051S to detect the abnormal situation.<br />
  23. 23. Trend of Plugged Line Detection<br />Behavior of this abnormal situation (aka process criminal) was unexpected<br />Stdev<br />Expected<br />Stdev<br />Valve position<br />Flow rate<br />Dropped down<br />This is the trend chart we collected for this application. <br />We expected the standard deviation to decrease due to the plugged impulse line.<br />But what I observed was totally unexpected, the standard deviation increased.<br />
  24. 24. Further Investigation into Behavior of PLD<br />Expected ↓<br />Low<br />Low<br />Hi<br />Hi<br />Delta-P<br />Delta-P<br />However, if there are bubbles in the impulse line, the stdev can increase instead of expected decrease.<br />This is an illustration of what happens when there is a plug.<br />When there is a plug in one line, the process noise will decrease. <br />However, if there are bubbles in the line, the process noise will actually increase.<br />The previous trend chart shows this happening.<br />
  25. 25. Simulation of plugging verified expected behavior – Decrease in stdev<br />CASE CLOSED<br />Plugged line detected<br />Flow rate<br />Normal Operation<br />Normal Operation<br />ok<br />ok<br />High side closed<br />Low side closed<br />Stdev<br />In order to confirm this behavior in our application,<br />we tested plugging by purging the bubbles and closing the lines leading to the transmitter.<br />This trend is the result of the test.<br />From this test, we can see that plugging in both low or high side resulted in decreased standard deviation. <br />Based on this data, we can say that there was bubble trapped inside the impulse line.<br />Key point here is that SPM detected something wrong in the process<br />even though standard deviation behaved unexpectedly.<br />
  26. 26. Case #3: The Windy City<br />Fresh air inlet<br />Heat exchange<br />Charge gas<br />M<br />To the next<br /> furnace<br />Heated<br />air<br />Feed<br />PDC<br />3051S<br />Air<br />Heater<br />Furnace<br />Emergency Exhaust<br />The third case study is based on the furnace air heater.<br />We have many furnaces and each furnace has the air heater system with it.<br />Fresh air is fed into the heater and heated air is supplied to the furnace.<br />The pressure inside of the heater is controlled by the pressure controller in DCS.<br />We installed Rosemount 3051S transmitter to look for any abnormal situations.<br />
  27. 27. Stdev spiked while pressure measurement did not<br />Stdev [kPa]<br />Pressure [kPa]<br />pressure<br />Spiking of Stdev Prompted Investigation<br />Stdev spikes<br />After installing the 3051S, I analyzed the trend data of the furnace operation.<br />This chart shows that although the operation is normal,<br />sometimes the standard deviation spikes.<br />
  28. 28. 3051S transmitter<br />Picture of Furnace Heater<br />Heated air<br />Sampling nozzle<br />Emergency exhaust<br />This is the air heater.<br />Fresh air comes from the top vent of the heater and heated air is sent into the furnace.<br />Red circle in the picture here indicates the location of the 3051S transmitter.<br />Sampling nozzle is connected to the bottom of the heater near the emergency exhaust.<br />
  29. 29. Picture of Furnace Heater<br />The pod is connected to the other sampling line to be less affected by wind<br />3051S<br />We installed the pod to avoid measurement distribution change due to the strong winds.<br />But it is difficult to remove the influence from the wind completely.<br />
  30. 30. Pressure is also slightly affected<br />Stdev for furnaces<br />Pressure inside of furnace<br />Stdev affected when strong wind blew into the pod<br />Wind velocity<br />The Effects of Strong Wind<br />With the 3051S, we measured standard deviation and compared it to wind velocity.<br />When the wind became strong, the standard deviation increased.<br />During this time, the pressure measurement is also slightly affected.<br />
  31. 31. Two adjacent furnaces<br />Stdev [kPa]<br />Pressure [kPa]<br />Affected by wind<br />Stdev only affected when strong wind blew directly into the pod.<br />Wind velocity [m/s]<br />This trend is the other data set.<br />When the wind velocity increased, the standard deviation changed at the same time.<br />Strong winds affect the reliability of the PV measurement.<br />We have found that standard deviation from SPM can detect this phenomenon.<br />Thus when this happens, we can change the operation from auto to manual to avoid process upset.<br />
  32. 32. CASE CLOSED<br />Perturbed by wind<br />Pressure [kPa]<br />Setpoint [kPa]<br />Case #3 Summary<br />Strong winds affect reliable PV<br />Velocity [m/s]<br />Direction [-]<br />Wind velocity<br />wind direction<br />Benefit from SPM information<br />・Indicator of when to change to “Manual” operation due to unreliable dP measurement.<br />・Prevent unexpected process fluctuation by unstable measurement caused by the wind<br />When it is typhoon season in Kashima, our operators can predict the strong winds.<br />However, I believe that SPM is more reliable in prediction than listening to the weather man.<br />
  33. 33. Open either valve<br />Other plant<br />User plant<br />(with Dryer)<br />3051S<br />FC<br />T<br />(w/o Dryer)<br />Turbine<br />Normally manual mode and fully opened<br />Case #4:Changing Feed Lines<br />The fourth case study is about switching feed lines.<br />The operator occasionally has to switch the feed lines manually based on production rate.<br />This happens about 3 to 4 times a year.<br />
  34. 34. Influence on Stdev by changing the line<br />Flow rate [km3/h]<br />Stdev [kPa]<br />(with Dryer)<br />Line pressure [MPa]<br />(w/o Dryer)<br />Flow rate<br />Difficult to verify switching of the line by looking at flow rate.<br />About 0.8<br />After switching the lines<br />About 0.1<br />SPM provides better indication of process profile change.<br />After switching the feed lines, there is no quick indication that it was successful.<br />However, when I observed the standard deviation, it was clear the value changed.<br />The standard deviation changes quickly and provides a nice indication that the switch was successful. <br />
  35. 35. Flow rate was also profiled<br />CASE CLOSED<br />Stdev is reliable indicator<br />Flow rate w/ Dryer<br />Flow rate<br />Freq.<br />Flow rate w/o Dryer<br />w/Dryer<br />Flow rate profile can also be observed, but Stdev is a faster indicator of completed switching<br />w/o Dryer<br />Distribution<br />[df/dt t/h]<br />This chart shows a longer trend of the flow profiles.<br />Here we can see that there is a clear indication of successful switching of the feed lines.<br />However, in order to draw this chart, it requires a longer period of time for sampling the data.<br />
  36. 36. FC<br />Case Study #5 Dryer Switching <br />3051S<br />PI<br />dryer<br />A<br />3051S<br />B<br />In this process, we switch the dryer operation every 20 days.<br />We installed 2 units of 3051S to monitor static pressure and flow measurement of this process. <br />
  37. 37. Switching Dryer Operation Affects Stdev<br />CASE OPEN<br />Case Open: On-going investigation into WHY Stdev cycles with switching<br />Stdev of pressure transmitter<br />Switch over every 20 days<br />Stdev of flow transmitter<br />The process profile of the transmitters showed similar pattern before and after switching dryer operation.<br />I am not sure why there is such a pattern.<br />Thus, this interesting case is still under investigation.<br />
  38. 38. Summary of Process Profiling<br />Key findings<br />SPM enables Predictive Maintenance<br />SPM is applicable to many applications<br />we will increase installation to broaden the monitoring coverage<br />Request to Emerson <br />Expedite to market diagnostic for loop<br />Detect capillary plugging<br />Detect Hydrogen penetration of Diaphragm<br />Detect Leak of seal fluid in Diaphragm<br />More sensitive detection for single line plugs<br />In summary, I found that SPM can enable predictive maintenance<br />and it’s also useful to detect slight changes in the process.<br />I am planning to increase SPM usage to broaden the process coverage and discover other applications.<br />I would like to share with you some requests to Emerson on future diagnostic developments.<br />
  39. 39. Agenda<br />Customer Challenges<br />Process Intelligence<br />Case Studies at Mitsubishi Chemical<br />Summary and Future of Diagnostics<br />
  40. 40. Loop Power & Connectivity<br />Diagnostic Coverage Beyond the Transmitter<br />Transmitter Health<br />Safety Certified<br />Process Intelligence<br />
  41. 41. Transmitter Health<br />SIS<br />Safety Certified<br />Benefits<br />Process Intelligence<br />Plugged<br />Impulse<br />Line(s)<br />Flame<br />Instability<br />Loop Power & Integrity<br />25<br />Applications<br />Entrained<br />Air<br />Agitation<br />Loss<br />Looking Beyond the Device to Deliver More Process Intelligence<br />
  42. 42. Transmitter Health<br />BAD<br />SIS<br />Safety Certified<br />Process Intelligence<br />Voice of the<br />Customer<br />Benefits<br />Loop Power & Integrity<br />X<br />+<br />Failing power supply<br />_<br />X<br />Wiring issues<br />X<br />Water &<br />Corrosion<br />Looking Beyond the Device Verifying Loop Power and Integrity<br />
  43. 43. SIS<br />Safety Certified<br />Process Intelligence<br />Benefits<br />Transmitter Health<br />Status Event<br />Time Since Event<br />Output Saturated<br />High Variation Alert<br />Temperature not updating<br />Output Saturated<br />LCD Update error<br />Output Saturated<br />Mean Change Detected<br />Temperature not updating<br />Output Saturated<br />Cold Start<br />00:013:11:01:37<br />00:013:11:31:37<br />00:013:16:01:33<br />00:013:23:05:00<br />00:013:41:11:23<br />00:015:23:32:47<br />00:016:58:16:37<br />00:023:23:54:38<br />00:123:16:24:67<br />00:153:57:14:32<br />Diagnostic Status Log<br />Loop Power & Integrity<br />Enhance Transmitter Health and Process Insight with Historical Event Log<br />
  44. 44. SIS<br />Process Intelligence<br />Benefits<br />Loop Power & Integrity<br />Safety Certified<br />Safety Certified to single use in SIL2 or multiple use in SIL3<br />SIL3 Power &<br />Process Diagnostics<br />10 Year Proof<br />Test Interval<br />Transmitter Health<br />Advanced Diagnostics Enable the Safest Pressure Installation<br />
  45. 45. Where To Get More Information<br />Come see a live demonstration at the technology exhibit!<br />Rosemount 3051S Advanced Diagnostics on the web<br /><br />