This case study demonstrates how vibration and distributed control systems (DCS) process data can extend a soft foot defect to improve operations beyond mechanical reliability. It is divided into two parts. This first part broadly explains the case study, while the second part provides more technical details that went into conducting the case study. The technical details are particularly valuable to those working in the polymer industry.
Vibration as a Mechanical Reliability Tool
Vibration is a useful tool that for decades has proven its effectiveness on mechanical reliability, from detection to analysis to correction. Generally, few bearings spots are selected to collect data, however, when shaking is spread over and impossible, hard, or dangerous to reach, the job scope is beyond a normal route check. To cover thousands of points, using tool like operational deflection shapes (ODS), is not unusual and becomes a very time and labor consuming task.
Vibration analysis is valuable and meaningful for professionals, but for managers without training, complicated data, like spectra and waveform, is overwhelming and not what they are interested in. Fortunately, video taken remotely and safely to amplify invisible defects like soft foot, which is hard to find but easy to fix, surely can improve mechanical reliability. In this case study, both vibration and DCS process data are integrated and cross-referenced to each other. The result provides valuable information to improve either equipment reliability or operational practices in the future.
Case Study Overview
A polymer extruder train has a permanent vibration monitor installed. A weird trending pattern on a motor inboard bearing along a vertical direction is noticed. Using frequency response function (FRF) analysis, possible soft foot is diagnosed, however, it cannot be confirmed visually. Micro movement at the motor foot (0.748 mils), which is 37.5 percent of a strand of hair (~ 2 mils) or 19 percent of paper (~ 4 mils), is confirmed by amplified video. Process loading variations, like polymer capacity or feed rate, viscosity or melt index (MI), start-up or coast down, and their influence on vibration behavior are studied to provide a guideline to improve operational control and vibration troubleshooting.
The Weird Vibration Trending Pattern
A three shafts polypropylene extrusion gearbox had a permanent monitor installed with 16 channels. After a major turnaround (T/A), where the output speed was upgraded from 226 rpm to 265 rpm, a weird vibration trending pattern from the accelerometer mounted on the motor inboard along the vertical (Z) direction began developing since baseline, as shown in Figure 1. This pattern moved across over wide severity range, from smooth and good to fair and rough, which raised attention and curiosity.
An FRF analysis indicated a minor motor 1x rpm peak at 1200 cpm, with out of phase among all four corners. Soft foot was highly suspected, however, the visual inspection by eye could not find any loose bolts or gap under each foot.
Eventually, displacement (0.748 mils) along the vertical (Z) direction, which is 37.5 percent of average hair thickness (~ 2 mils), was verified after taking an amplified video. Imperceptible open and close activities at the motor foot became visible, as shown in Figure 2.
For those without a polymer extrusion background, here’s some basic information. To set up a proper vibration alarm, parameters like rotating speed, along with the capacity or feed rate, if variable and available, always needs to be considered. However, to meet ever-changing customized specifications, frequent viscosity transit, or melt index in the polymer industry, is another factor that can never be neglected because it surely affects loading as well.
Squeezing polymer past a filter to remove impurity and thoroughly mixing to get homogenous resin ready for pelletizing is critical for quality control. The difficulty is best illustrated by trying to insert a thumbtack into the ultrafine screen (just barely hold at position and not drop!), as shown in Figure 3. In a worst-case scenario, the screen crashes if it is overloaded and needs to be replaced.
An extrusion gearbox is surely the core of manufacturing, let alone bearing defects, broken teeth, or any other auxiliary issues, like lubricant pump low pressure, steam ventilation clog, etc. All of these might cause a shutdown, which not only affects extruder reliability, but also may cause a motor rotor bar crack, a consequence of an over electrical current in the armature after frequent start-ups over the long term.
Before the motor soft foot was corrected, vibration was used as an indicator and related its response to DCS data. A more in-depth study was explored, providing insight on both improving operational practice and troubleshooting skills for future reference. After this hairline soft foot deficiency was fixed, there was no longer a weird trending pattern. This 0.748 mils soft foot was subtle, and although it was easy to fix, it was definitely hard to detect.
Conclusion
- Amplified or magnified video definitely saves time and labor, especially when the job scope is bigger and beyond normal route check. Most importantly, the dynamic image can be shared and let the machine speak for itself without explanation. It is a great communication tool for reliability applications.
- Magnified video can help look for defects beyond human vision limit, and its value is proved by numerous documented examples on internet. When photographers proudly present the amazing dynamic images, most stories stop after all the observers give off their surprising “Wow” admiration, whereas it is just the beginning and this study intends to develop further exploration from another viewpoint.
- Reliability common sense tells practitioners that a machine is supposed to be affected by the manner in which it is run by different operational practices or how the vibration is affected by different process factors. However, this intuition is never proven and supported by real data that integrates both online vibration and DCS data, which is the purpose of this case study.
Author’s Acknowledgments
Nick Ma, operation engineer in Formosa Plastics PP-1 Unit for extracting all the DCS plots. Without his contribution, this case study would not be informative.
Andy Lerche, of Mechanical Solutions, Inc. for taking the video that discovered the hairline soft foot and solved my curiosity.
Greg Adams and Seth Rozner, colleagues in the Rotating Department, for reviewing the author’s work before submission.