ISO 17359: Condition monitoring and diagnostics of machines – General guidelines

Summary

ISO 17359 serves as a high-level “umbrella” standard for the entire field of machinery condition monitoring. It provides a structured framework and a strategic overview for setting up and managing a condition monitoring program. Rather than detailing specific measurement techniques, it outlines the essential steps, considerations, and methodologies that should be in place for a program to be successful, from initial planning to routine operation and review. It is the starting point that references other, more specific standards for individual technologies (like vibration, oil analysis, or thermography).

Table of Contents (Conceptual Structure)

The standard is structured as a roadmap for implementing a condition monitoring strategy, centered around a six-step cyclical process:

1. 1. Step 1: Machine Knowledge and Information (Audit):

   This foundational step is the strategic core of the entire condition monitoring program. It mandates a thorough audit to identify which machines are most critical to the operation and therefore warrant monitoring. This involves a risk and criticality analysis. Once critical machines are identified, the standard requires a deep dive to gather all pertinent information, including design specifications, operational parameters, maintenance history, and, most importantly, conducting a detailed Failure Modes and Effects Analysis (FMEA). The FMEA is a systematic process used to identify all potential ways a machine or its components can fail. For each failure mode (e.g., “bearing spalling,” “shaft unbalance”), the goal is to understand its potential causes, its symptoms or effects (e.g., “generates high-frequency impacts,” “causes high 1X vibration”), and the consequences of the failure. The output of this step is a definitive list of failure modes for each critical machine, which directly informs the next step of the process.

2. 2. Step 2: Select Monitoring Strategy:

   This step directly builds upon the findings of the FMEA from Step 1. For each identified failure mode, a strategic decision must be made on the most effective and economical monitoring technology to detect its onset. The standard emphasizes that there is no one-size-fits-all solution. For example, the FMEA might show that a primary failure mode for a gearbox is tooth wear. The strategy here would be to select oil analysis (specifically, wear particle analysis) as the primary monitoring technique, as it can detect wear debris long before a significant vibration change occurs. For a different failure mode, like shaft misalignment, the strategy would be to select vibration analysis, as it is the most direct way to detect the characteristic 2X vibration signature. This step involves a careful review of all available CBM technologies—including vibration, thermography, acoustics, and motor circuit analysis—and mapping them to the specific failure symptoms identified in the FMEA, ensuring a targeted and efficient monitoring program.

3. 3. Step 3: Establish the Monitoring Program:

   This is the tactical planning phase where the high-level strategy from Step 2 is translated into a detailed, documented action plan. This step involves defining all the specific parameters required for a repeatable and effective monitoring program. Key activities in this stage include: defining the precise measurement locations on each machine; specifying the exact parameters to be measured (e.g., RMS velocity, peak acceleration, temperature, wear particle concentration); establishing the data collection frequency (e.g., monthly for non-critical machines, continuously for highly critical assets); and setting the initial alarm or alert limits. The standard provides guidance on setting these initial alarms based on generic industry standards (like ISO 10816), vendor recommendations, or a percentage change from a baseline reading taken when the machine is known to be in good health. The result of this step is a complete, documented monitoring plan for each machine.

4. 4. Step 4: Data Acquisition:

   This step concerns the routine, physical execution of the monitoring plan developed in Step 3. It is the process of dispatching a technician or an automated system to the machine to collect the specified data at the prescribed frequency. The standard places a heavy emphasis on the importance of adhering to standardized procedures during this step to ensure data consistency and repeatability. This means following the exact measurement procedures for the chosen technology, for example, adhering to ISO 13373-1 for vibration data collection. It requires ensuring that the machine is operating under comparable conditions (load, speed) for each measurement and that the data is correctly stored and labeled with all relevant contextual information (date, time, machine ID, measurement point ID) for effective trending and analysis in the subsequent steps.

5. 5. Step 5: Data Analysis and Diagnostics:

   This step is where the collected data is transformed into meaningful information. The process begins with **data analysis**, which involves comparing the newly acquired data against the alarm limits established in Step 3. If no limits are breached, the machine state is confirmed as normal. If an alarm is triggered, the process moves to **diagnostics**. This is a more in-depth investigation performed by a trained analyst to determine the root cause of the problem. It involves a detailed examination of the data, such as analyzing the specific frequencies and patterns in a vibration spectrum or examining the size and shape of particles in an oil sample. The standard recommends a systematic approach to diagnostics, correlating the observed data patterns with the potential failure modes identified in the FMEA (Step 1) to arrive at a specific and confident diagnosis of the fault.

6. 6. Step 6: Maintenance Decision and Action:

   This is the final, decisive step where the results of the condition monitoring program are translated into tangible action. Based on the confident diagnosis from Step 5, this stage involves making a strategic maintenance decision. The standard outlines that this decision is not always to “repair immediately.” Instead, it is a risk-based judgment that considers the severity of the fault, the operational criticality of the machine, and the availability of resources. The possible actions could range from simply increasing the monitoring frequency, to planning a specific corrective action (e.g., an alignment procedure, a bearing replacement) for the next scheduled outage, or, in critical cases, recommending an immediate shutdown of the machine to prevent catastrophic failure. This step closes the loop of the CBM process. The results of the maintenance action, and the verification that the fault has been corrected, are then fed back into the machine’s history (Step 1), creating a cycle of continuous improvement and learning.

Key Concepts

• Strategic Framework: This standard is not about the “what” (e.g., “measure RMS velocity”) but the “how” and “why” of setting up a program. It provides the business and engineering logic for condition monitoring.
• Technology Agnostic: ISO 17359 is not limited to vibration. It provides a framework that is equally applicable to a program based on oil analysis, infrared thermography, acoustic emission, or any other condition monitoring technology.
• The P-F Curve: The philosophy of the standard is closely tied to the concept of the P-F curve, which illustrates that a potential failure (P) can be detected by condition monitoring long before a functional failure (F) occurs, allowing for planned, proactive maintenance.
• Integration: It promotes the idea of an integrated approach, where data from multiple technologies can be combined to provide a more confident and accurate diagnosis of machine health.

Official ISO Standard

For the complete official standard, visit: ISO 17359 on ISO Store

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