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Using RAM Analysis to reduce turbine-generator maintenance costs
Editor's note: RAM is an acronym for 'reliability, availability and maintainability'. RAM analysis is a technique used in some nuclear generating stations to improve a plant maintenance program (see Maintenance mathematics). Of interest to engineers who maintain any complex electro-mechanical-chemical system, this article takes RAM analysis a step further. Although it applies to turbine-generators, it can be applied to any major installation: oil  refineries, ocean drilling rigs, steel mills, complex production lines, hydro, nuclear and fossil-fuelled thermal generating stations.

The cost of maintenance varies widely from one generating station to another. This holds true even when comparing stations with similar generating output capacities. And cost is the vital factor in maintaining equipment capability or, put in another way, reducing the incapability factor.
RAM techniques were applied to turbine-generator systems at the Bruce nuclear generating station in Ontario, Canada. As a general rule, in any complex system, 20 per cent of the installation take 90 per cent of the maintenance budget to maintain. The aim therefore was to separate those items of equipment that require the lion's share of attention. After this was done, the planners specified those tasks that would improve the effectiveness of the turbine-generation maintenance program.
The North American Electric Reliability Council (NERC) equipment incapability factor (EICbF) standard (see the boxed definition) for turbines over the five-year period 1984-1988 was about 9 per cent. Over the same period, the turbine EICbF for the four 832-MW units at Bruce A Nuclear Generating Station was 8 per cent. The performance for the turbines of the station was therefore only marginally better than the industry standard.
The equipment incapability factor for the station's generators over the same 5-year period was 5 per cent as compared to the NERC standard of 3.5 per cent. Performance of the generators was obviously well below standard and a threat to reliability. To improve the turbine generator maintenance program, analysis of the main components began with a definition of the boundaries and interfaces between the systems and subsystems.
Equipment incapability factor (EICbF) is a measure of the contribution that an item of equipment or system would have made to a unit's gross ICbF if all other system had operation perfectly during a specific period.

Gross incapability factor (ICbF) is the percentage of gross generation that a unit is capable of producing in a specific period.

Poisson distribution theory was developed by Simeon-Denis Poisson (1781-1840), a French mathematician famous for his work on definite integrals and probability analysis.
Dominant failure modes
With the main components and subsystems identified (see Figure 1 and Table 1), the next step was to conduct a failure mode and effect analysis (FMEA). The purpose of a FMEA was to categorize all possible failure modes, and the effects of such failures on the availability of the component or system under review. This is one RAM technique; fault tree analysis is another.
In this study, fault tree analysis was used to assess the most critical of all possible failure modes. The assessments resulted in the truth table shown in Table 1. From this data the probability of the overall system failure was calculated. [The following may look complicated, but  consult Table 1 and the equation will is logically assembled.]

Equation 1 where the symbol | = given that

P (failure) = P[SG] + P[TG|SG] + P[ESV] + P[TG|ESV] + P[ESV|LO] + P[GSV] + P[GSV|LO] + P[TG|GSV] + P[RIV] + P[RIV|LO] + P[TG|RIV] + P[TG] + P[TG|CD] + P[CD] + P[LO] + P[TG|LO] + P[EX] + P[TG|EX] + P[HX] + P[TG HX]
Applying conditional probability rules, Equation 1 is expanded to

Equation 2 where the symbol ∩ = intersection
P (failure) = P[SG] + P[TG ∩ SG]/P[SG] + P[ESV] + P[TG ∩ ESV]/P[ESV] +
P[ESV ∩ LO]/P[LO] + P[GSV] + P[GSV ∩ LO]/P[LO] + P[TG ∩ GSV] /P[GSV] + P[RIV] + P[RIV ∩ LO]/P [LO] + P[TG ∩ RIV]/P[RIV] + P[TG] + P[TG ∩ CD]/P[CD] + P[CD] + P[LO] + P[TG ∩ LO]/P[LO] + P[EX] + P[TG ∩ EX]/P[EX] + P[HX] + P[TG ∩ HX]/P[HX]  

The probability of individual component failure was then calculated using Poisson logic.

Equation 3

Pt (failure) = 1-e-λt where Pt is the time dependent failure probability and the failure rate.

To calculate the failure probabilities of the subsystems, it is necessary to have values of λ for the individual components and the joint failure events. This raises the question of how to get accurate values of λ, which is a problem. Computer simulations may be useful, but the reliability of simulated data is doubtful and may even be misleading. It is better to rely on production and maintenance records, provided they are accurate and well maintained.

Maintenance records should include the following minimum information
  1. Failure mode and diagnosis of the component or system.
  2. Other components that failed as a result of the primary component or system failure.
  3. The effect of the failure on production or plant capability.
  4. Repair and replacement time including work hours and material used.
  5. Annual frequency of failure figures and cumulative figures over the service life of the component.
  6. The cost of repair and the total outage time.
Figure 1 is a simplified goal tree for the turbine-generator. Goal tree analysis provides some measure of the production and maintenance tasks that must be done to achieve the objective. For example, one objective might be to maximize equipment availability. Another could be to improve overall production efficiency. In the case of the turbine-generator studied, the primary objective was to maximize its availability for service.
Maintenance tasks
The final phase of the analysis was to determine the most cost effective maintenance tasks and to incorporate them in the program. As noted, FMEA identifies the dominant failure modes of components or subsystems. Using this information and reviewing the preventive maintenance program leads to program changes that improve cost effectiveness. It also offers a number of options, which are to: do nothing; replace the equipment; make design changes; improve the spare parts program; revise the operating and maintenance procedures; provide additional training; or improve the operating environment.
Subsystem criticality ranking
The next logical step is to rank the system elements in order of diminishing criticality. Ideally, to minimize the incidence of failure, it is necessary to maximize component maintenance. Unlimited maintenance is impractical, for it would increase the work load beyond the capacity of the maintenance staff to say nothing of the exorbitant cost.
If a unit is to operate efficiently, the system components must be ranked to get the maximum benefit from the maintenance effort. Criticality ranking requires reliable data that can only come from accurate production and maintenance records. Table 2 is a list of the Turbine-generator subsystems based on two criteria, which are 'loss-of-production costs' and 'maintenance time spent on the equipment'.

Maintenance planning
Planning a maintenance strategy and applying it is easy once the critical components of the system are known. In sum, the strategy can be expressed in a syllogism:
  • Failure of critical equipment is intolerable.
  • Therefore, minimize breakdown maintenance.
  • Expand preventive maintenance to minimize equipment breakdown.
Bearing failure, for example, is critical. RAM analysis confirmed this. Methods used to detect impending bearing failure are first, on-load vibration monitoring and, secondly,  lubrication condition monitoring. On the basis of these conclusions, the station management decided to replace its 10-year-old vibration monitoring equipment.
RAM analysis led to a number of steps taken to improve equipment availability. One was to refurbish and, where it was considered necessary, to replace the condenser steam discharge valves. Another centered on the quality of the station's maintenance procedures. Those for the Turbine-generators and their subsystems were rewritten in plain English, which made them less complicated to read and follow. As a result, less time was spent in finding spare parts and the actual maintenance was done more efficiently.
The RAM analysis and conclusions reached led to a number of changes in maintenance practice. These included:
  1. Systematic condition monitoring of bearings was begun;
  2. Improved maintenance of the condenser steam discharge valves was instituted;
  3. The station began a program of revised all its maintenance procedures.
  4. Using PC-based planning software, detailed outage plans for the turbine-generators with clear references to the new maintenance procedures were introduced. This made for more efficient manpower planning and shortage outage times.
  5. The station management introduced manufacturer training for maintenance staff. For example, the cost of exciter maintenance was high because the repair crews lacked maintenance expertise. The same applied to fitters and mechanics for maintaining motor-operated valves and like equipment.
  6. Design changes to the exciter cooling system were made with considerable cost savings.
  7. The analysis pointed to the need to investigate other component failures including servo-valves, solenoid valves, limit switches and the electro-hydraulic governor system test panel.

Effective maintenance improves equipment availability and reduces costs. Equipment availability and cost saving was the primary aim of the study.
RAM analysis requires a logical approach to the problem through the use of techniques such as FMEA, FTA and goal trees. To illustrate the steps of this method of analysis use was made of a simplified turbine-generator system. This was ranking critical components in terms of the severity of failure.
On the basis of ranking, it is possible to assign the preventive maintenance tasks in order of priority. The analysis also led to additional options including writing clear procedures, developing detailed outage plans and better management of spare parts. Table 3 lists the projected cost saving for the period for which the analysis was done. These savings lead to an important observation, which is that more than half of savings come from better documentation – new procedures and better outage plans – to a total of $2.01 million.
Finally, equipment availability is increased and maintenance costs decreased by the use of logical analysis using RAM techniques for any complex system of electro-mechanical plant or chemical processing installation.

Co-authored with I. Walker, P. Eng. (First published in Power Engineering July 1990)

Probability and Statistics for Engineers, I. Miller and J. Freeund, 2nd Edition, Prentice-Hall, 1977.

RAM Applications in Power Generation; A tutorial held at the 14th InterRam Conference held in Toronto, Ontario, May 1987.

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