In power generation plants, maintenance directly determines the availability of installations, the safety of teams and compliance with regulatory requirements. Structuring the maintenance organisation therefore becomes an operational lever to improve asset reliability, reduce unplanned downtime and manage performance over time.
Key takeaways
- Structuring maintenance starts with asset prioritisation: criticality analysis focuses efforts on the assets that have the greatest impact on safety, availability and compliance, and adapts maintenance strategies accordingly.
- Reducing unplanned downtime relies on making use of maintenance data: analysing failure histories and tracking simple indicators (MTBF, MTTR, availability) enables a move from reactive maintenance to a more anticipatory approach.
- Performance management must integrate safety and organisation: effective maintenance relies on controlled plans, prepared interventions and standardised practices to limit emergencies and risky situations.
- The CMMS provides an organisational foundation for maintenance managers: by centralising data, plans, indicators and regulatory documentation, it simplifies management, traceability and compliance at power generation plants.
How to identify critical assets and structure a suitable maintenance strategy for power generation plants?
Structuring maintenance for a power generation plant relies first and foremost on a precise knowledge of assets. This step determines the relevance of maintenance plans, resource allocation and the teams’ ability to intervene in an organised way, without being affected by operational contingencies.
Prioritise critical assets
Asset prioritisation aims to identify those whose failure would have a significant impact on safety, production or regulatory compliance.
This approach is based on criteria widely used in the energy sector:
- risks to the safety of people and facilities,
- impact on plant availability and production continuity,
- regulatory obligations associated with certain assets or systems,
- time, resources and skills required for return to service,
- direct and indirect costs related to unavailability.
This criticality analysis can rely on proven methods, such as AMDEC (Failure Modes, Effects and Criticality Analysis).
It makes it possible to identify the most penalising failure scenarios and to prioritise maintenance actions.
A CMMS like DimoMaint enables structuring this analysis by centralising technical data, histories and criticality levels. It provides a shared, long-term reference and makes it easier to reassess priorities as installations evolve or experience feedback is gathered.
Case study – Waga Energy (biomethane) : to monitor about 400 assets per plant and target 95% availability, Waga Energy replaced Excel with a CMMS to obtain “a single source of truth” and a “clear view” of corrective and preventive interventions, with limited production stoppages.
Structure maintenance plans
Building maintenance plans must take into account the specific constraints of power generation plants: continuous operation, limited intervention windows, strict regulatory requirements and close coordination with operations.
Based on asset criticality, different types of maintenance can be combined in a structured way:
- a systematic preventive maintenance for assets subject to periodic checks or known wear cycles,
- condition-based maintenance when asset condition can be monitored using reliable measurements or indicators,
- a predictive maintenance, based on analysis of historical data and operational signals, to anticipate some failures before they cause a shutdown,
- a controlled corrective maintenance for assets with limited impact.
Predictive maintenance does not replace other approaches. It complements existing arrangements, prioritised for critical assets whose failure would have significant consequences. Its implementation requires rigorous structuring of maintenance data and reliable traceability of interventions, indispensable conditions to produce exploitable analyses.
This approach is aligned with reliability-centered maintenance (RCM), which adapts the maintenance strategy to asset functions and the consequences of their failures, rather than applying uniform plans.
The CMMS allows formalising maintenance plans, integrating different strategies (preventive, condition-based, predictive), scheduling interventions and tracking their completion. For maintenance managers, this brings a more controlled organisation, without multiplying tools or parallel follow-ups.
How to reduce unplanned downtime in power generation plants?
Once critical assets are identified and maintenance plans structured, the challenge for maintenance managers is to reduce unplanned downtime. These events remain one of the main sources of production losses, extra costs and organisational strain. Their control relies primarily on better use of maintenance data and on a more proactive approach to reliability.
The main causes of unplanned downtime
Unplanned downtime rarely results from a single factor. They are generally linked to a combination of technical, organisational and human causes.
- On the technical side, some failures are related to asset ageing, severe operating conditions or insufficient monitoring of critical parameters.
- On the organisational side, predominantly reactive maintenance weakens plant reliability.
- Human factors also play an important role: lack of traceability of interventions, loss of information between teams, incomplete or outdated procedures.
Incident analysis can be complemented by root cause analysis (RCA) approaches to prevent recurrence of the same failures and turn feedback into lasting corrective actions.
Use failure history to move from reactive to proactive maintenance
Intervention and incident histories are a lever often underused. Yet this data makes it possible to identify failure patterns and to detect assets showing an abnormal recurrence of failures.
Data analysis from interventions includes notably :
- listing failure types and their recurrent causes,
- analysing intervention and return-to-service times,
- identifying the assets or subsystems generating the most incidents,
This approach makes it possible to distinguish isolated failures from structural defects requiring adaptation of the maintenance strategy, or even modification of preventive plans or operating conditions. The CMMS facilitates this data use. By centralising all histories, it provides a consolidated view of events.
Manage asset reliability using relevant maintenance indicators
Reliability management relies on simple indicators that maintenance teams and industrial management can use directly. These indicators fit the classic triptych reliability, maintainability and availability, widely used to steer the performance of industrial installations.
- MTBF (mean time between failures), to assess asset reliability,
- MTTR (mean time to repair), to measure intervention effectiveness,
- installation availability rate,
- failure rate or rate of unplanned downtime.
Analysing the evolution of these indicators over time makes it possible to identify deviations, measure the impact of maintenance actions implemented and adjust the strategy when results fall short.
The CMMS automates indicator calculation from real field data. Maintenance managers can thus rely on factual data to manage asset reliability, progressively reduce unplanned downtime and strengthen overall operational control.
How to measure and manage maintenance performance at power generation plants?
Maintenance performance management is based on concrete indicators derived directly from the teams’ actual activity. The goal is to adjust priorities and organisation using reliable data.
Data from the CMMS makes it possible to track in particular :
- compliance with maintenance plans and scheduled deadlines,
- the share of planned interventions versus unplanned interventions,
- trends in intervention times and return-to-service delays,
- team workload and the use of internal and external resources.
For maintenance managers, the challenge is to put these data into perspective with production objectives and budgetary constraints.
The DimoMaint CMMS facilitates this approach by consolidating information and providing a shared view between maintenance, operations and industrial management.
Secure maintenance operations in a high-risk environment
Maintenance interventions in power generation plants take place in high-risk environments. Safety is a structuring element of maintenance organisation.
Securing interventions relies mainly on :
- formalised procedures adapted to the assets and intervention situations,
- clear operating methods that include lockouts, checks and verifications before return to service,
- rigorous work preparation, limiting emergency interventions.
Standardising practices reduces discrepancies between teams and limits dependence on individual habits.
The CMMS acts as organisational support here. By integrating procedures and safety requirements into work orders, it helps structure interventions and strengthen risk control without unnecessarily increasing teams’ workload.
Ensure traceability of interventions
Power generation plants are subject to strict regulatory requirements that require complete traceability of interventions and controls performed.
Structuring maintenance implies being able to quickly find :
- intervention histories for regulated assets,
- results of mandatory checks and inspections,
- associated documents (reports, certificates, procedures),
The CMMS centralises this information in a single reference database. It allows planning regulatory checks, tracking them and retaining the required evidence. In audit or inspection situations, maintenance managers thus have a clear, usable view without excessive mobilisation of teams.
Case study – DYNEFF (petroleum distribution, 50 sites)
To manage maintenance of its sites in France and Spain, DYNEFF deployed a CMMS to replace fragmented management (Excel files per asset and per site) and to structure a single database. The project aimed in particular to create a single database of assets, trace interventions and have a global view of activity (recurring failures, stocks, preventive).
Maintenance of power generation plants relies on a structured organisation based on knowledge of assets, anticipating failures and rigorous performance management. Added to these challenges are the safety of interventions and regulatory compliance, which require reliable and durable traceability.
In this context, the CMMS is an essential tool to formalise processes, improve data reliability and give maintenance managers a consolidated view of their activity.
