Corrective Maintenance Requirements Based on Work Order Counts - Annual Average CM

To compare corrective maintenance activities across breaker families and across utilities, a new metric was developed, Annual Average CM.

It is calculated for each breaker and aggregated for families, as follows:

    Annual Average CM for breaker = (Number of CMs incurred by breaker) / (Number of Years over which the work order histories were observed)
    Annual Average CM for family = Sum [(Annual Average CM for breakers in the family)] / (Number of Breakers in Family)

Annual Average CM is calculated for each breaker using the maintenance history provided by the utility. For older breakers, EPRI has chosen to look back no more than ten years. As the name suggests, Annual Average CM for a breaker is calculated by summing the CM counts for that breaker and averaging it annually by dividing by the number of years over which work order histories were observed. For example, a breaker that had 4 corrective maintenance work orders over the last 5 years of available history has a calculated Annual Average CM of 0.8.

This metric can be used to assess corrective maintenance requirements for different circuit breaker families and draw comparisons across breaker families and different utilities.

In Figure 2-2, using standard box plots, the top row shows annual average CM values for four oil breaker families—two models from Allis/Siemens BZO, GE FK and Westinghouse GM breakers. Within the boxes the horizontal line shows the median and the X shows the mean. The box colors represent different utilities. The middle plot shows the age distribution and the table at the bottom gives the breaker count used to generate the plots.

This visualization is helpful in making comparisons. For example, the Westinghouse breakers have significantly more varied performance at the different utilities. Furthermore, Utility B shows better overall performance across breaker families. These observations raise questions such as:

• Why is there a performance difference?
• What is Utility B doing differently in maintaining its oil circuit breaker fleet?

These questions cannot be answered directly from this analysis, but it is possible to see which breaker family is incurring a higher level of maintenance than other families, which may influence CM requirements in the coming year. It is also possible to identify how a given breaker family is performing at different utilities, and how breaker families differ in their maintenance requirements.

The metric can also be used to look at different families within a single utility, or to make comparisons of gas and oil breakers.

Figure 2-3 is an example of the same metric used in an analysis demonstrating increasing maintenance with age for one family of gas breakers. The plot on the left shows the annual average CM count versus average family age for each utility. There is a clear trend of increasing CM with increasing age. The plot on the right shows the percentage of breakers with one or more CM actions. For example, at utility G (family average age around 12) only a little over 30 % of the breakers have needed corrective maintenance while at utility F (average age around 23), 90 % have. This analysis is only possible because the IDB has a collection of breakers of the same family from different utilities with different average ages for this family.

Such a metric may be useful in providing a quantitative, rather than anecdotal, view of the increasing need for corrective maintenance, and to help asset managers to forecast maintenance requirements as breakers age.