Chemical Processing - October 2007 - (Page 33)

>> Condition management solution architecture Figure 1. Success depends upon properly using wide variety of inputs from all plant levels. bration, temperature, pressure, corrosion and fluid analysis. Now, the advent of intelligent field devices and sensors as well as low-cost wireless units that can be deployed into areas where hard wiring would have been cost-prohibitive is extending these base capabilities and the data they provide. Unfortunately, plants aren’t enjoying the full potential of the data for three reasons: 1. The focus of condition monitoring deployments is too narrow. Sites need to instrument a wider range of assets, so management can look beyond specific equipment to entire process areas or complex asset sets such as heat exchangers, dryers and other plant units. 2. The volume of data available now is huge and will continue to grow exponentially. This creates a significant knowledge management challenge around making sense of the data. Exacerbating the problem, the aging workforce means that plants are losing more and more people with critical operational experience, knowledge and interpretive skills. 3. Many companies still have operational silos. Plant personnel aren’t collaborating to detect, manage and analyze emerging issues. The net result is continued outages, even when the underlying condition or trend had been correctly detected. Condition management defined Addressing this set of challenges requires an enhanced, more holistic approach — condition management. Under this approach, the vast array of condition data is the entry point to a five-step process where the data are: 1. aggregated and rationalized; 2. combined to create context and support proper analysis; 3. clearly presented and communicated; 4. systematically managed to ensure the timely, accurate, consistent and effective resolution of the underlying issues; and 5. used as input to ongoing continuous improvement. www.chemicalprocessing.com The first three elements are aimed at turning the data into information, changing the condition information from “noise” in the eyes of operations personnel into useful decision support intelligence for all personnel. The aggregation and rationalization also need to address the varying types of data, the time element (real-time, neartime and offline) as well as the various access and communication methods utilized by vendors. Once the data are turned into properly contextualized and actionable information, it’s critical to manage the use of the information. It comes back to the fundamental difference between condition monitoring and condition management. Condition management information helps unlock the usefulness of the condition data by: • driving the appropriate workflow/processes to resolve the issue(s), bringing together the key personnel across operational disciplines (engineering, maintenance, control, safety, etc.). • providing input to an ongoing knowledge management process where new situations and their appropriate resolution are systematically captured and documented. Further, condition management supports Six Sigma or Lean Sigma initiatives by supplying input for an ongoing process where the knowledge base is regularly reviewed and refined. A telling example A leading specialty chemicals maker discovered the value of the approach but only after a serious incident. The process uses a significant amount of power, so the company operates a 300-MW captive power plant. The site had deployed condition monitoring tools on assets there — vibration, rpm, and amperage on the pumps in the cooling towers, the manufacturer’s monitoring tools on the turbine, and assorted flow and temperature meters throughout the cooling system. When the primary pump in the cooling tower failed, the control system initiated a cutover to a back-up pump and then cleared the alarm. An operator entered the occurrence in the log, where the required follow-up was to have maintenance staff repair the primary pump. Shortly after this initial incident, the operator started receiving alarms that the temperatures in the cooling system were drifting out of range, coupled with pressure warnings. Assuming that this was a “storm” created by the cutover to the back-up pump, the operator acknowledged and cleared the alarm set. Close on the heels of this second set of indications, the turbine monitoring system flagged a significant temperature variance and recommended an immediate shutdown. Again, on the assumption that this was a blip caused by the cutover, the operator cleared the alarm. After two minutes, which was the defined “re-alarm” time, the turbine monitoring system reported dangerously high temperatures and again recommended a shutdown. This time, October 2007 • 33 http://www.chemicalprocessing.com

Table of Contents Feed for the Digital Edition of Chemical Processing - October 2007

Chemical Processing - October 2007 Contents From the Editor ChemicalProcessing.com Field Notes In Process Energy Saver Compliance Advisor Biofeedstocks See Real Growth Become a Cyber-Security Pacesetter Go Beyond Condition Monitoring Disposable Equipment Earns Lasting Role Improve Control Loop Performance Ethanol Plant Boosts Output and Saves Energy Process Puzzler Plant InSites Equipment & Services Ad Lits Product Spotlight/Classifieds Ad Index End Point

Chemical Processing - October 2007

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