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 http://hartcomm.org/protocol/realworld/realworld_success_mitsubishi09.html

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

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 levels Tracks changes in PV (i.e. what the operator sees) SPM Turns Process Noise Into Valuable Information PV 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) 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.

12. Japan 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. 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.

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. 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.

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 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.

19. 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.

20. 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.

21. 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.

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 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.

24. 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.

25. 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.

26. 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.

27. 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.

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 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.

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.

32. 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.

33. 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.

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 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.

36. 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.

37. 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.

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

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

43. SIS Safety Certified Process Intelligence 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 Loop Power & Integrity Enhance Transmitter Health and Process Insight with Historical Event Log

44. SIS Process Intelligence Benefits 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 www.Rosemount.com/3051SDiagnostics