Use of PSA for maintenance optimization

In many countries, level 1 probabilistic safety assessments (PSAs) of NPPs have been completed in recent years, based both on generic data and on data specific to the plant.

Current maintenance programmes have been developed during the operating lives of the NPPs. They were originally based on the recommendations of the plant designers or manufacturers and have been developed following experience of operation of the plant and from the results of plant condition monitoring.

Future developments

Possible future developments in derivation of maintenance programmes include the following:

Condition monitoring will have a greater influence and maintenance based on condition monitoring will replace time based maintenance for some specific plant items.

PSA may be used as part of the case to support proposed changes to maintenance tasks and frequencies but specific studies may be necessary in areas such as in-service

If the PSA is fast enough, it may be used to provide information on how best to respond to changing situations, such as plant failures, which may require changes to planned maintenance activities.

The RCM approach, which may make use of PSA, may be used to optimize maintenance requirements.

Uses of PSA

PSA can be used in maintenance optimization:

to identify and rank key systems, components and failure modes (this is an important part of the RCM method);

to recognize if more frequent maintenance is required in order to achieve risk targets;

to assess the effects of changes to maintenance requirements on system availability and the overall plant risk for all operating and shutdown states;

to assist with outage planning in particular to show that co-incident maintenance outages do not compromise the required level of safety;

to justify existing maintenance requirements;

as part of the case, to support reductions in maintenance frequencies.

Maintenance input to PSA

Maintenance findings can be used to support PSAs by providing plant specific data for the PSA and validation of PSA assumptions and models. Maintenance frequencies can affect component reliability data used in the PSA. Specific studies may be necessary to evaluate the effect on PSA input data of changes to maintenance frequencies and tasks.

Potential difficulties in the use of PSA for maintenance optimization (1) Confidence in the results of the PSA:

validity of reliability data, use of generic data;

validity of the assumptions made and the model used;

possibility of unanticipated failure modes;

treatment of human error, particularly with regard to maintenance induced failures;

models and data for common cause failures.

(2) The need for commitment to the use of the PSA in terms of resources and keeping the PSA up to date. Effort required could be for example 1-2 man-years for each PSA.

(3) Determining acceptance criteria for changes in risk due to changes in maintenance in terms of integrated risk and instantaneous risk.

(4) Difficulty in assessing the effect on PSA input data of a change in maintenance frequency.

(5) PSAs based on conservative assumptions may not be as valid for use in maintenance optimization as a best estimate PS A.

6) PSAs may include simplifying assumptions, for example assessment of only representative parts of the plant, which could affect use of the PSA for maintenance optimization.

Precautions necessary in the use of PSA for maintenance optimization

(1) The PSA must be maintained as a living PSA, taking account of operating feedback and changes to plant and with an adequate commitment of resources.

(2) Feedback data must be collected and assessed to establish its implications on the PSA.

(3) The possibility of maintenance induced failures and common mode failures should be considered, including maintenance induced common mode failures, implying that the PSA should include consideration of human error.

(4) The PSA may have to be adapted or extended for use in maintenance optimization, for example by using best estimate rather than conservative assumptions or by assessing all trains of a system rather than representative trains.

(5) The overall risk criteria and/or technical specification requirements must still be achieved.

(6) Changes to reliability data assumed following changes to maintenance tasks or frequencies may be based on expert judgement but must be followed by validation including use of feedback from operating experience.

(7) Maintenance optimization may not be appropriate for inspection requirements for passive components — specific studies may be necessary for such components.

2.3.2. Conclusions

(1) PSA can be of great value in maintenance optimization but it must be used with care.

(2) Proposals arising from a PSA based approach to maintenance optimization can be considered on a case by case basis by the regulatory body without necessarily implying general approval of the methodology used.

(3) There may be other factors dictating maintenance frequencies, e.g. regulations on inspection of pressure circuit components (but it is possible that PSA based arguments might prompt reconsideration of the regulations, particularly if reductions in radiation doses would be achieved).

(4) PSA can be used to identify key systems, components and failure modes as part of the RCM process but caution is necessary in using PSA in other ways in maintenance optimization studies.

(5) Findings from PSA based RCM studies may be used as an aid to decision making on