Thursday, April 5, 2012

AM Education Course Feature: Condition Monitoring 301

STLE asked the course instructors and chair to provide some detail on the course, and you can read on to get a preview of the course itself. You can register for the meeting and the course, or get some more information on our Annual Meeting page.

First, can you give us an overview of the field and how this course got started?
“Condition Monitoring” is a relatively new term, perhaps 20-25 years old. I founded this course on the observation that CM was going to be a very important concept as equipment and lubricants continued to get more sophisticated. It was also the first practically-oriented STLE course that dealt with in-service lubricants.

How does this course differ from last year or previous courses offered on CM?
This course is significantly more advanced and is targeted to persons who already have experience in oil analysis and CM. Basics are mentioned in passing but the objective is to provide a more technical program.

Are there are any prerequisites for attending this course?

Attendees should have a good basic understanding of oil analysis and the CM concept, generally: the notion of preventive action triggered by CM data, evaluated by knowledgeable people.

What can one expect to learn and be able to bring back to their workplace?

Whether data evaluation and rendering opinions is the goal of the attendee, an appreciation of what an oil analysis or other CM report provides should be gained. If the attendee is a manager of those involved in data evaluation and opinion rendering, then he/she will have a good appreciation of the process so as to facilitate the team in accomplishing CM goals. The theme of this course is "21st Century Condition Monitoring," and this is the crux of what our team is presenting: cutting edge approaches to this valuable, necessary concept.

The short answer is that CM, properly done by competent people in a competent system, saves or earns money by early detection of potential problems and/or increasing component availability, respectively.

Meet the instructors, and see what they're teaching:

Evan Zabawski: Advanced Data Interpretation
A successful condition monitoring program requires the right data coupled with the right interpretation. Obtaining the right data can be relatively simple, but getting a decent interpretation often relies on setting appropriate alarm limits or properly identifying abnormal trends. Leveraging historical data from the same asset and other similar assets is ideal, but the execution often produces sub-par results. This presentation will critique a variety of techniques used for both setting alarm limits and trending data, and then offer a model which uses an amalgamation of the best concepts. Examples will be used to illustrate key concepts. This presentation is aimed at any individual involved in the interpretation of data or decision-making resulting from condition monitoring data (e.g. Reliability Engineers, Maintenance Planners, etc.)

Chad Chichester: Condition Monitoring (CM) Techniques Complementary to Oil Analysis

Many companies elect to employ a multitude of condition monitoring techniques. The nature of failure analysis and prediction is becoming more complex and each technique offers insight to root causation of failures, and impending failures intended to be mitigated. Isolating techniques to confines of their own data, interpretation, and topical experts may prevent reliability and maintenance practitioners from realizing the full potential of using multiple techniques. Integration of data and information from multiple techniques can improve asset owners’ ability to succinctly identify root cause and/or impending failures. This module will focus on CM techniques like, vibration analysis, infrared thermography, and acoustic emissions and how such methods can be aggregated and synergistically complementary to oil analysis.

Allison Toms: Impact of Machinery Configuration and Operations on Monitoring Techniques and Data

Over the past decade, changes in machinery configuration and operational demands have had a profound impact on oil analysis condition monitoring. Machinery and lubricant OEMs and government research have invested in improvements in both the design and materials used in manufacturing and production as well as in lubricant formulation. Many of these improvements have not been adequately reflected in current testing practices. Testing equipment and methodologies have also improved and new monitoring tools have been introduced to address new problems. This presentation will touch on some of the changes to oil analysis over the past decade such as lubricants and additives; component design, configuration and alloy compositions; improved and new testing equipment, technology, techniques; operational and environmental factors; and customer desires. The presentation will include on-line sensors and at-line applications to meet some of these changes as well as the means to achieve improved machinery condition indicators and estimates on remaining useful life through integration of monitoring techniques. Examples and case histories will be presented.

Jack Poley (also Course Chair): Condition Monitoring International and Kittiwake Developments - Changing Paradigms in CM: Online Oil Analysis, Extended Particle Analysis, Software and More

Oil Analysis has changed rather radically in the last decade. The advent of dependable, effective online sensors for metallic wear debris is probably the most obvious such change, leading to a ‘3-tiered’ system of oil analysis: Online, Onsite, Offsite, each having its own advantages. Practitioners can employ one or all avenues. Particulate analysis, especially those near the visible range, is increasingly more advanced. Computerization has provided us with the ability to set limits and plot trends, but nowadays that’s not news. The use of Intelligent Agents in resolving increasingly complex data sets that can include streaming data from online metallic debris or vibration sensors makes it possible, given strong domain expertise, to auto-generate very sophisticated and accurate opinions AND get them to the right stakeholder for timely intervention as may be needed via selective report recipients,. The notion of humans poring over data one sample after the next is on its way out. Information needs to be specific, relevant , consistent and tidy, delivered quickly and effectively to the right parties.

1 comment:

  1. Thank You

    The given information is very effective
    i will keep updated with the same

    industrial automation training