Reliability and Asset Management

Posts Tagged ‘condition monitoring’

12 Essential Elements of Highly Successful Predictive / Condition Based Maintenance Programs

Thursday, April 25th, 2013 | Condition Monitoirng & Predictive Maintenance, Maintenance Programs | No Comments

Have you ever wondered why your predictive /condition based maintenance program is not as effective as you think it should be?  It has been more than 25 years since the wide spread introduction to predictive maintenance tools/instruments and condition based maintenance practices and still many PdM/CBM programs struggle to get full support from management and that is because many of them struggle to be effective in increasing the reliability of their plant operations and showing and effective payback to their management.  Over the year I have seen hundreds of PdM/CBM programs.  All of the effective programs that I have been involved with, basically 12 essential elements.  They are as follow:

  1. Definition of the Process
  2. Leadership and Coordination
  3. Organization with Clear Roles & Responsibilities
  4. Training and Qualifications
  5. Technical Basis
  6. Guidance for Application of Technology
  7. Information Integration and Management
  8. Prioritization and Scheduling of PdM/CBM Work
  9. Work Closeout and Maintenance Feedback
  10. Clear Goals and Performance Measurement
  11. Calculation and Reporting Cost-Benefit and Return on Investment
  12. Continuous Improvement

Does your predictive maintenance / condition based maintenance program have these essential elements?

Tags: , , , , , , ,

Your Predictive/Condition Based Maintenance Program

Tuesday, July 26th, 2011 | Condition Monitoirng & Predictive Maintenance | 8 Comments

The purpose of a predictive/condition based maintenance (PdM/CBM) program is to communicate information about the condition of the machinery under surveillance. The PdM/CBM report should include only information that helps the reader to clearly understand the results of the condition monitoring efforts. The report should include:

  • An equipment status report including operating availability and component availability
  • A priority work list including work pending, work in progress, and work completed
  • Status definitions for satisfactory, marginal, and critical
  • A summary of the operating status of each component to include fully operational, marginal, critical, and inoperable

Individual equipment status reports for equipment that is marginal or worse

The report serves two primary functions:

  1. It provides a valuable source of information for plant maintenance, operations, and engineering.
  2. It continually shows the impact of PdM/CBM on the plant to upper management. This line of communication justifies the program and allows for continued management support.


The reporting period is determined by the needs of the plant but a report should be prepared at least annually. It is important to note that the report should not contain any raw data collected from a diagnostic system. It should be concise and clear.



The following elements should be included in a PdM/CBM periodic report:

  • Management summary – Provides a synopsis that highlights the activities performed during the reporting period. When possible, use photographs of actual plant conditions that illustrate successes.
  • Equipment performance – Provides a list of equipment that predictive maintenance indicates is in an abnormal condition and has been placed on an alert or watch list.
    • Windows® format and supporting documentation can be used to identify equipment condition. Also indicate in this section those pieces of equipment that have been removed from the alert or watch list.
    • Information sharing – Provides a section to be used by predictive maintenance personnel to explain various aspects of the program or to share examples where assistance has been provided to other station departments.
    • Cost-benefit – Provides cost savings that are attributed to predictive maintenance activities. Consider costs that were avoided because equipment replacement, maintenance labor hours, and purchase of replacement power were not needed.
    • Continuous improvement and operating experience – Provides discussions on new technologies and training received by predictive maintenance personnel. This section could also be used to document any internal or external examples of operating experience factored into the predictive maintenance program.


Program Metrics

All nuclear plants have extensive goals and metrics to indicate effectiveness of plant programs and processes and to measure progress toward desired improvements. These metrics do not always relate to the effectiveness and progress of the PdM/CBM program itself. Therefore, it is useful to have a clearly defined set of performance measures that specifically relate to the PdM/CBM process.


A Best practice set of metrics is as follows:

  • Focus on four important cost areas:
    • Equipment reliability and unit availability
    • Operations and maintenance costs
    • Capital expenditures
    • Thermal unit performance
    • Maintenance task balance between unplanned corrective maintenance tasks (which are reactive), planned CM on run-to-failure equipment, repetitive PM tasks, and condition directed tasks, which are planned CM or PM tasks initiated as a result of decisions from the PdM/CBM process. Planned CM is defined as a situation where either the equipment has been predetermined as run-to-failure, or condition monitoring has detected degradation of the equipment and allowed time for proper planning and optimum scheduling of the task.
    • Return on investment for PdM/CBM activities.
    • Effectiveness in implementing the PdM/CBM process

PdM/CBM Key Performance Indicators

Performance Parameter Indicator Target
Data Collection


Number of delinquent data collection PMs 0
Number of surveillance tests repeated due to

errant vibration data

Percentage data collection of total PdM/CBM

components – Motor Analysis Program

Percentage data collection of available PdM/CBM components – Motor Analysis Program 100%
Percentage data collection of total PdM/CBM

components – Thermography Program

Percentage data collection of available PdM/CBM components – Thermography Program 98%
Percentage data collection of total PdM/CBM

components – Vibration Program

Percentage data collection of available PdM/CBM components – Vibration Program 98%
Data Analysis Number of occurrences of unidentified equipment degradation within PdM/CBM scope 0
Lube oil sample backlog 80% ≤ 2 weeks

0% > 4 weeks

Equipment Reliability Percentage of undetected failures of PdM/CBM scope components <1.0%



Tags: , , , ,

Get the Most from Your Predictive/Condition Based Maintenance

Thursday, December 2nd, 2010 | Condition Monitoirng & Predictive Maintenance | 27 Comments

It has been more than two decades since predictive maintenance and condition monitoring were introduced in the electric power industry.  Since then, the industry as a whole has learned a lot about equipment failures, the mechanisms that induce those failures, and how to identify impending failures.  The tools that are available today cover more than just the “big three technologies” (vibration, oil, and infrared analysis).

Yet with all that is available to us as an industry many organizations still struggle to take full advantage of condition monitoring and predictive maintenance.  Or, may because of all the information and technology that is available to us we struggle to get the full value of our programs.

Being successful at implementing Predictive/Condition Based Maintenance requires that an organization be successful in three areas: People – train and educate our plant’s staff (not just the PdM/CBM staff) to understand the importance of PdM/CBM to the success of the organization; Technologies – select the right technology for the right application and understand what the information being provided is telling us about the health of our equipment and plants; and Processes – designing and implementing PdM/CBM processes that are integral to our daily work and provide actionable information to  the work management efforts.

The Electric Power Research Institute (EPRI) identified “14 Key Elements” of successful predictive/condition based maintenance programs.  These “14 Key Elements” include:

1.    Task Technical Basis – should provide a clear understanding of what potential failure mechanisms are being “monitored for”, the impact of those failure mechanisms on the equipment and the plant, and the likely hood of their occurrence.

2.    Technology Application – should include procedures and guidelines for application.  Each technology being applied should be well understood and consistently applied.

3.    Process Flow Definition – should be well defined including all interfaces with engineering groups, work management, maintenance, and operations.

4.    Program Leadership and Coordination – should include good visibility within the organization for the PdM/CBM leadership.  That leadership should promote the use of and the benefits of PdM/CBM.

5.    Organization, Roles, and Responsibilities – should include real accountability and evidence that the responsibilities are being carried out as defined by the process.

6.    Information Management and Communications – personnel should correlate PdM/CBM data with other forms of plant information to provide a clear picture of the health of equipment.  This information should be communicated to other groups efficiently to support timely actions.

7.    Equipment Condition Assessment and Decision Making – condition data should be trended, analyzed, integrated and a report generated on anomalies for equipment owners and management to review.  It should be clear who has the responsibility for making decisions on equipment based upon its health.

8.    Training and Qualifications – the users of the information developed by PdM/CBM should have a basic understanding of the techniques.  The PdM/CBM personnel should be well trained and certified and should be participating with their pier in the industry.

9.    CBM/PdM Work Prioritization and Scheduling – data collection tasks should be well defined, prioritized and scheduled in the work management process.  The plant should ensure that data is collected consistent with the program requirements.

10. Work Closeout and Maintenance Feedback – should include documentation of as found conditions; it should be timely and be provided to the PdM/CBM organization, maintenance and the equipment owners.

11. Goals and Performance Metrics – should be part of the integrated metrics used by the plant.  They should be well developed and consistent with the overall goals of the organization.

12. Calculations of Cost-Benefits and Return on Investment – should include both a probabilistic approach to cost avoidance along with and the real budget associated with running the program.  Management should understand and support the analysis process and the values used in the analysis.

13. Internal Customer Satisfaction – internal customers should be identified and their input as to how the PdM/CBM process could be more useful to them should be solicited.

14. Continuous Improvement – industry and technologies should be reviewed on a regular basis to incorporate lessons learned and new thought process so as to make the PdM/CBM process more effective.

When looking to enhance or revitalize your PdM/CBM process create a clear definition of your ideal organization with respect to the above 14 Key Elements; once this has been complete an assessment of where your organization is performing in each of needs to be performed.  With an understanding of where your organization needs to be and where it is today, an organizational change plan can then be developed to effectively move your organization forward.

Tags: , , , ,

Copyright © 2024 NSGIWebsite design by Slamdot.