Share Email Print
cover

Proceedings Paper

Developing a comprehensive training curriculum for integrated predictive maintenance
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

On-line equipment condition monitoring is a critical component of the world-class production and safety histories of many successful nuclear plant operators. From addressing availability and operability concerns of nuclear safety-related equipment to increasing profitability through support system reliability and reduced maintenance costs, Predictive Maintenance programs have increasingly become a vital contribution to the maintenance and operation decisions of nuclear facilities. In recent years, significant advancements have been made in the quality and portability of many of the instruments being used, and software improvements have been made as well. However, the single most influential component of the success of these programs is the impact of a trained and experienced team of personnel putting this technology to work. Changes in the nature of the power generation industry brought on by competition, mergers, and acquisitions, has taken the historically stable personnel environment of power generation and created a very dynamic situation. As a result, many facilities have seen a significant turnover in personnel in key positions, including predictive maintenance personnel. It has become the challenge for many nuclear operators to maintain the consistent contribution of quality data and information from predictive maintenance that has become important in the overall equipment decision process. These challenges can be met through the implementation of quality training to predictive maintenance personnel and regular updating and re-certification of key technology holders. The use of data management tools and services aid in the sharing of information across sites within an operating company, and with experts who can contribute value-added data management and analysis. The overall effectiveness of predictive maintenance programs can be improved through the incorporation of newly developed comprehensive technology training courses. These courses address the use of key technologies such as vibration analysis, infrared thermography, and oil analysis not as singular entities, but as a toolbox resource from which to address overall equipment and plant reliability in a structured program and decision environment.

Paper Details

Date Published: 15 March 2002
PDF: 12 pages
Proc. SPIE 4710, Thermosense XXIV, (15 March 2002); doi: 10.1117/12.459583
Show Author Affiliations
Richard Norman Wurzbach, Maintenance Reliability Group, LLC (United States)


Published in SPIE Proceedings Vol. 4710:
Thermosense XXIV
Xavier P. Maldague; Andres E. Rozlosnik, Editor(s)

© SPIE. Terms of Use
Back to Top