ISO 13379-1:2025

Overview

ISO 13379-1:2025 - "Condition monitoring and diagnostics of machine systems - Data interpretation and diagnostics techniques - Part 1: General guidelines" defines common concepts, principles and practical guidance for condition monitoring and diagnostic activities. The standard helps simplify communication between users and manufacturers of condition monitoring systems, sets out technical characteristics, and supports the development and selection of appropriate diagnostic approaches for any machine system whose state can be described by measured inputs (operational parameters) and outputs (responses).

Key topics and technical requirements

• Scope and concepts: Establishes terminology and high‑level requirements for condition monitoring and diagnostics (see also ISO 13372 vocabulary).
• Diagnostics workflow (Clause 4): Describes systematic steps for diagnostics:
  • Anomaly validation
  • Data and information collection
  • Analysis
  • Hypothesis formulation
  • Hypothesis testing
  • Diagnosis synthesis
• Requirements to set up diagnostics (Clause 5): Guidance on establishing diagnostic needs, Failure Mode Symptoms Analysis (FMSA), and creating diagnostics requirements reports. New methods include assessment of FMSA results using a Monitoring Priority Number (MPN) and diagram methods.
• Elements used for diagnostics (Clause 6): Defines condition monitoring data, descriptors, symptoms, faults, machine system data, and maintenance records as essential inputs.
• Diagnostic approaches and models (Clause 7): Defines and compares main approaches:
  • Data‑driven (statistical/ML models)
  • Knowledge‑based (fault–symptom diagnostics, causal trees, first‑principles)
  • Guidance on building models and determining a confidence level for diagnoses.
• Informative annexes: Examples and worksheets (diagnostic reports, FMSA worksheet, ratings, methods, model applicability).

Applications and users

ISO 13379-1:2025 is applicable across industries for machine systems where operational parameters and responses can be measured. Typical use cases and beneficiaries:

• Predictive maintenance and reliability programs
• Condition monitoring of rotating machinery, conveyors, pumps, compressors and other industrial equipment
• Diagnostic system developers, condition monitoring solution vendors and integrators
• Maintenance engineers, reliability engineers, asset managers and technical consultants
• OEMs seeking standardized communication about diagnostics and performance

Practical value

• Enables consistent interpretation of monitoring data and transparent diagnostic reporting.
• Helps select appropriate diagnostic approaches (data‑driven vs knowledge‑based) based on applicability and limitations.
• Supports confidence assessment for diagnosis outputs, improving maintenance decision making and asset availability.

Related standards

• ISO 13372 (vocabulary)
• ISO 17359 (data and information collection guidance)
• ISO 13381‑1 (confidence/prognostics concepts)

Keywords: ISO 13379-1:2025, condition monitoring and diagnostics, data interpretation, diagnostic model, FMSA, MPN, data-driven diagnostics, knowledge-based diagnostics, predictive maintenance.