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Playbook · Quality & reliability

Maintenance and asset reliability

Maintenance is a portfolio of decisions about failure consequences. This path starts from asset criticality and failure history, then chooses tasks by consequence rather than habit or vendor fashion.

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6 steps · 4 cited sources · free during beta

The question this path answers

Which assets matter, how do they fail, and which maintenance tasks are actually justified?

The path, step by step

  1. Classify assets by function and criticality

    List the assets that carry operational, safety or environmental consequence. For each, state the function it must perform and what happens when it fails.

    Why it worksAsset management starts from the outcomes the portfolio must deliver, not from a task catalogue. Criticality tells you where maintenance effort can change a business outcome.

    EvidenceStandardization (2024) · Moubray (1997)

    CheckpointA criticality ranking tied to operational and safety consequences, with the top assets named.

    Common failureTreating every asset as equally critical and spreading maintenance thin.

  2. Capture failure history with consistent definitions

    Record failure mode, cause, detection, downtime and repair for critical assets. Use the same definitions across shifts and sites so the history can be compared.

    Why it worksReliability-centred maintenance depends on knowing how assets actually fail. Inconsistent failure categories turn the history into anecdotes and make the next task choice a guess.

    EvidenceMoubray (1997) · Standardization (2024)

    CheckpointA failure log with consistent categories and enough history to rank modes.

    Common failureChoosing maintenance strategy from vendor claims because the failure history is unusable.

  3. Choose tasks by failure consequence

    For each significant failure mode, decide whether a scheduled task, condition-based check, redesign or run-to-failure is justified. Delete tasks that cannot address a credible mode.

    Why it worksRCM's decision logic selects maintenance by consequence: safety, environment, operations and cost. It explicitly permits run-to-failure when no task reduces the consequence enough to justify it.

    EvidenceMoubray (1997) · Shah & Ward (2003)

    CheckpointA task decision per major failure mode, including the explicit run-to-failure decisions.

    Common failureAdding more preventive tasks to every asset and calling it reliability.

  4. Schedule maintenance with operations

    Plan preventive work around production and service windows, with the parts, skills and permits ready before the window opens. Measure schedule adherence, not just completion.

    Why it worksA maintenance plan that ignores operating windows creates either missed maintenance or avoidable downtime. Total productive maintenance treats maintenance as a shared operating responsibility, not a separate function.

    EvidenceShah & Ward (2003) · Moubray (1997)

    CheckpointPlanned work completed within the window, with waiting for parts or permits measured.

    Common failureScheduling maintenance by calendar and discovering the part is unavailable on the day.

  5. Justify condition monitoring with data

    Use condition-based or predictive monitoring only where the failure mode gives a usable warning and the consequence justifies the cost. Pilot on one asset class and compare with the existing task.

    Why it worksCondition monitoring can replace calendar tasks when a measurable precursor exists, but the evidence for predictive programmes is context-dependent and depends on data quality and the failure mode.

    EvidenceMoubray (1997) · Montgomery (2019)

    CheckpointA pilot showing earlier detection or lower cost than the existing task, with false alarms counted.

    Common failureBuying sensors for assets whose failures give no warning or carry little consequence.

  6. Review reliability and update the strategy

    Review downtime, repair time and task yield on a fixed cadence. Move assets between strategies as the failure history changes.

    Why it worksAsset management is a lifecycle discipline: the right task changes as the asset ages, the operating context changes and the failure history accumulates.

    EvidenceStandardization (2024) · Moubray (1997)

    CheckpointA quarterly reliability review that changed at least one task or asset strategy.

    Common failureSetting the maintenance plan once and never revisiting it.

The evidence base

Each step above cites hand-selected research. These are the studies behind the path.

More from the library

Further reading from Portolan's research library, matched by subject. These papers are not proof that any step works; check each checkpoint against your own operation.

  • Ahuja & Khamba (2008) — Total productive maintenance: literature review and directions
  • Kaparthi & Bumblauskas (2020) — Designing predictive maintenance systems using decision tree-based machine learning techniques
  • Abidi et al. (2022) — Predictive Maintenance Planning for Industry 4.0 Using Machine Learning for Sustainable Manufacturing
  • Ljungberg (1998) — Measurement of overall equipment effectiveness as a basis for TPM activities
  • Sharma et al. (2005) — Systematic failure mode effect analysis (FMEA) using fuzzy linguistic modelling
  • McKone et al. (2000) — The impact of total productive maintenance practices on manufacturing performance
  • Cua et al. (2001) — Relationships between implementation of TQM, JIT, and TPM and manufacturing performance
  • Sherwin (2000) — A review of overall models for maintenance management
  • Márquez et al. (2009) — The maintenance management framework
  • Tsang (2002) — Strategic dimensions of maintenance management

Guides for this path

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