Condition based maintenance

What is condition-based maintenance (CBM)?

Condition-based maintenance (CBM) is a strategy that monitors the actual condition of an asset to decide what maintenance needs to be done. CBM dictates that maintenance should only be performed when specific indicators show decreasing performance or upcoming failure. Checking a machine for these indicators may include non-invasive measurements, visual inspection, performance data, and scheduled tests. Condition data can then be gathered at specific intervals or continuously (as is done when a machine has internal sensors). Condition-based maintenance can be applied to mission-critical and non-mission-critical assets.

What is CBM+?

Condition-based maintenance plus (CBM+) is an advanced maintenance strategy that builds upon traditional condition-based maintenance (CBM) principles by integrating real-time data analytics, advanced diagnostics, prognostics, and enterprise-level decision-making tools. While CBM focuses primarily on using sensor data to detect equipment wear or failure, CBM+ aims to predict when maintenance should be performed and optimize operations across the entire lifecycle of assets.

CBM+ transforms maintenance from a reactive or scheduled task into a strategic, intelligence-driven function, increasing asset availability and reducing overall lifecycle costs. It brings together multiple technologies like IoT, machine learning, and digital twins to create a dynamic, responsive maintenance ecosystem.

A brief history: CBM+ and the U.S. Department of Defense

CBM+ was officially introduced by the U.S. Department of Defense (DoD) in the early 2000s as part of a broader initiative to modernize military logistics and sustainment practices. The goal was to enhance the readiness of military equipment while reducing support costs and logistical footprints.

In 2002, the DoD launched its condition-based maintenance plus (CBM+) strategy, which called for the integration of maintenance technologies with information systems to improve weapon system sustainment. This initiative aligned with the DoD’s transformation vision—shifting from a reactive support model to one that is predictive, data-driven, and strategically aligned with mission objectives.

The U.S. Army's DA PAM 750-8 (PDF document opens in new tab), also known as the Department of the Army Pamphlet 750-8, serves as a comprehensive manual for the Army's Maintenance Management System (TAMMS). This pamphlet details the procedures for overseeing maintenance activities, identifying and reporting equipment issues, and recording modifications to equipment, among other essential tasks.

The CBM+ approach has since been widely adopted across the services: Army, Navy, and Air Force, enabling better asset visibility, proactive maintenance planning, and improved decision-making at both tactical and enterprise levels.

What’s the goal of condition-based maintenance?

Condition-based maintenance aims to monitor and spot upcoming equipment failure so maintenance can be proactively scheduled when needed–and not before. Asset conditions need to trigger maintenance within a long enough time before failure, so work can be finished before the asset fails or performance falls below the optimal level.

For condition-based maintenance to succeed, several other elements of your maintenance operation need to be in place. That includes having a scheduled maintenance strategy that allows you to inspect and spot anomalies in equipment and trigger timely follow-up work orders. If you want to take the next step and predict which work orders will lead to asset failure, check out what AI-powered work order reports can do for you. It’s also essential to have the right parts and supplies on hand when problems in performance are identified, and work is created. Read more about forecasting your parts using historical data and artificial intelligence.

Condition-based maintenance workflow

A condition-based maintenance (CBM) workflow outlines the steps to manage CBM activities. It provides a structured approach to effectively monitor equipment conditions, analyze data, and perform maintenance actions based on the equipment's health. Here's an example of a typical workflow for condition-based maintenance for Fiix:

As shown in the example above, Asset A has a series of sensors and tags connected to it. The data from these sensors and tags get aggregated and streamed to an API and the cloud (in this case, a CMMS). At that point, an AI sets up a training period to understand the baselines of the asset. Generally, the training takes some time, and this step takes about one week with Fiix's CMMS. From here, the AI predicts risks and then displays the them on a dashboard for the asset and, lastly, creates a maintenance task and work order for the asset if required.

What is the difference between condition-based and predictive maintenance?

Condition-based maintenance (CBM) and predictive maintenance (PdM) share some similarities but are used in different ways and for different purposes. Below is a table that illustrates some of the differences:

In addition to these differences, it's essential to understand that the predictive maintenance workflow in a CMMS is very different from the condition-based workflow.

Predictive maintenance workflow

A predictive maintenance (PdM) workflow typically involves several stages to implement the strategy effectively. Here's an example of a typical workflow for predictive-based maintenance for Fiix:

As shown in the example above, Asset B has a series of sensors and tags connected to it. The sensor and tag data then gets linked to thresholds that the maintenance manager (or other maintenance personnel) defines. From here, if the meter for a specific sensor or tag is over (or under) the set threshold, the information is sent through the API into the cloud (in this case, a CMMS). When this data is sent into the CMMS, a trigger may (or may not) occur based on the data. If the trigger indicates an issue with Asset B, a maintenance task is created, and a work order is assigned to fix the problem.

CBM vs. CBM+

Although CBM and CBM+ share many of the same traditional values, they differ in several ways. The table below highlights the differences between the two methods:

Key industries where CBM+ is critical

While CBM+ has its roots in defense, its principles and benefits have made it critical across a number of asset-intensive industries:

Types of condition-based maintenance monitoring techniques

There are various types of condition-based monitoring techniques. Here are a few common examples:

• Vibration analysis: Rotating equipment such as compressors, pumps, and motors all exhibit a certain degree of vibration. As they degrade or fall out of alignment, the vibration increases. Vibration sensors can be used to detect when this becomes excessive.
• Infrared: IR cameras can detect high-temperature conditions in energized equipment.
• Ultrasonic: Detection of deep subsurface defects such as boat hull corrosion.
• Acoustic: Used to detect gas, liquid, or vacuum leaks.
• Oil analysis: Measures the number and size of particles in a sample to determine asset wear.
• Electrical: Motor current readings using clamp-on ammeters.
• Operational performance: Sensors measure pressure, temperature, flow, etc.

How is condition-based maintenance data collected?

Two different methods can collect data:

1. Spot readings can be performed at regular intervals using portable instruments
2. Sensors can be retrofitted to equipment or installed during manufacture for continuous data collection

Critical systems that require considerable upfront capital investment or could affect the quality of the product produced need up-to-the-minute data collection. More expensive systems have built-in intelligence to self-monitor in real time. For example, sensors throughout an aircraft monitor numerous systems in flight and on the ground to help identify issues before they become life-threatening. Typically, CBM is not used for non-critical systems, and spot readings will suffice.

Discover how Fiix OT integrations optimizes' your assets based on real-time data (opens in new tab)

How to create a condition-based maintenance program

Creating a condition-based maintenance (CBM) program involves several key steps. Here's a general framework to guide you through the process:

1. Define objectives and scope: Identify the goals and scope of your CBM program. Determine which equipment or assets will be included and the specific objectives you aim to achieve. This could be reducing downtime, optimizing maintenance costs, improving equipment reliability, or maximizing asset lifespan.
2. Identify your critical equipment: Identify the equipment or assets that are critical to your operations and have a significant impact on productivity or safety.
3. Select appropriate condition monitoring techniques: Evaluate and select the most suitable methods based on the equipment and failure modes. Standard practices include vibration analysis, thermal imaging, oil analysis, acoustic, and performance monitoring. Choose techniques that provide meaningful data on the equipment's health and performance.
4. Establish your baseline data and thresholds: Collect initial baseline data to establish each monitored asset's normal operating conditions and performance levels. Determine appropriate thresholds or alarm limits for different parameters to indicate when maintenance actions are required. These thresholds can be based on historical data, equipment specifications, industry standards, or expert knowledge.
5. Implement data collection and analysis: Set up a system to collect, store, and analyze the data from the condition monitoring sensors. This can involve using software like a CMMS or specialized data analysis and visualization tools. Develop algorithms or rules that trigger alerts or work orders when the monitored parameters exceed the defined thresholds or show signs of deterioration.
6. Develop your maintenance strategies: Using the analyzed data and identified asset conditions, determine appropriate maintenance actions. This can range from corrective actions responding to imminent failures to preventive or predictive maintenance tasks. Consider factors such as the criticality of the asset, cost-benefit analysis, and resource availability when developing maintenance strategies.
7. Establish workflow and responsibilities: Define the workflow and responsibilities for executing maintenance tasks based on the CBM findings. Clearly outline the roles and responsibilities of technicians, engineers, and data analysts involved in the CBM program. Develop procedures for documenting and communicating the findings, work orders, and maintenance history.
8. Monitor and refine the CBM program: Continuously monitor the performance and effectiveness of your CBM program. Analyze the data, track key performance indicators, and measure the program's impact on uptime, maintenance costs, and asset reliability.

Use this information to refine and improve the CBM program over time, adjusting the monitoring techniques, thresholds, or maintenance strategies as needed.

Challenges of a condition-based maintenance program

There may be some challenges to effectively running a condition-based maintenance program, and they are important to understand in order to overcome:

• CBM requires an investment in measuring equipment and staff up-skilling, so the initial implementation costs can be high. The way to overcome it is by getting buy-in from your leadership team to push the use case forward.
  

  How to combine data and storytelling to get your maintenance project approved (opens in new tab)

• CBM introduces new maintenance techniques, which can be challenging to implement due to organizational resistance. The way to overcome it is by training the maintenance team and setting up check-in meetings to make sure the new techniques are being done correctly.
• Older equipment can be challenging to retrofit with sensors, and monitoring equipment can be difficult to access during production to spot measure. The way to overcome this is by accepting that some monitoring might not be perfectly done from the get-go. It's okay to update and change monitoring techniques as you go through your CBM process.
• It still requires competence to turn performance information from a system into actionable proactive maintenance items. The way to overcome this is through knowledge acquisition, one of the best ways to learn is from someone who's already done it.
  

  Join the Fiixer community to get insight from experts into CBM (opens in new tab)