Imagine you're a maintenance professional enjoying a Saturday barbeque when you get an emergency call. Amid complaints from your family and friends, you have to rush into work and try to diagnose why a critical machine has suddenly failed. Meanwhile, production is down, and all eyes are on you as you work through the weekend to get things running.
Now, imagine that a month ago, you received an alert about that same machine. By analyzing the motor's vibration patterns, you immediately identified a fault, executed a plan, and ensured operations continued without interruptions. This scenario illustrates the power of Condition-Based Monitoring (CbM). In this guide, we'll explore how CbM goes beyond traditional reactive maintenance and how to get started with this essential practice.
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Key Takeaways from This Article✔️ Condition monitoring is a critical practice in industrial environments that helps detect potential machinery issues early, allowing for proactive maintenance and thus preventing significant failures and unplanned downtime. ✔️ Key techniques of condition monitoring include vibration analysis, oil analysis, acoustic analysis, and thermal analysis, each detecting specific types of faults to enhance overall equipment effectiveness and operational efficiency. ✔️ Implementing condition monitoring systems involves a structured approach with data collection, diagnosis, and prognosis, supported by suitable software and IIoT technology to reduce maintenance costs, improve asset lifespan, and ensure employee safety. |
Condition monitoring is a vital practice that helps detect potential machinery issues before they progress into significant failures and costly downtime. The ultimate goal is to spot upcoming equipment failures so maintenance can be proactively scheduled when needed, ensuring that operations run smoothly and efficiently.
Condition monitoring, also known as condition-based monitoring or CbM, involves using various methods of analysis to monitor the condition or performance of machines before issues escalate into major failures. The purpose of condition monitoring is to predict whether an asset will break, how it will break, and the time available for maintenance before functional failure.
In industrial environments, the importance of condition monitoring lies in its ability to:
✔ Detect potential machinery issues before they turn into serious failures
✔ Identify impending equipment failures, thus facilitating the proactive scheduling of maintenance when necessary
✔ Avoid unplanned downtime
Condition monitoring solutions can promptly detect developing faults by identifying changes in machinery conditions, including vibration and temperature. By continuously collecting data, condition monitoring sensors compare readings against normal parameters to identify issues early, facilitating proactive maintenance and significantly reducing the risk of unexpected breakdowns. Online condition monitoring provides an even fuller picture of asset health, and real-time alerts can help prevent unplanned downtime.
As a pivotal tool in predictive maintenance, condition monitoring aids in pinpointing developing faults and inefficiencies in machinery, thereby preventing unplanned downtime. By analyzing condition monitoring data, maintenance teams can determine the optimal timing for maintenance, which enhances machine performance and extends asset life.
Learn more about predictive maintenance in our video: Predictive Maintenance explained.
The benefits of condition monitoring are manifold, making it an indispensable tool in industrial maintenance. The proactive nature of condition monitoring allows for servicing multiple machines during planned downtime, addressing all known problems simultaneously. Ultimately, by implementing condition monitoring, unplanned downtime is reduced, higher overall equipment efficiency (OEE) is achieved, and emergency repairs are avoided.
Reducing maintenance costs on each asset through condition monitoring can have a large impact on plant profitability. Hidden maintenance costs, which can be up to five times higher than direct maintenance costs, are significantly reduced through condition monitoring.
The principles of cost escalation due to asset failure and the benefits of preventive maintenance apply broadly across different sectors where maintaining operational efficiency and minimizing downtime are critical.
To detect faults effectively, it is crucial to choose and implement condition-monitoring techniques specifically tailored to your critical assets. Common areas for continued monitoring include vibration analysis, lubricant analysis, and infrared thermography. These techniques include sensors and connected devices, timed physical inspection by humans, lab testing, and testing using specialized equipment.
Vibration analysis, a type of vibration monitoring, is the most popular form of condition monitoring, involving the detection and assessment of rotational and structural issues. It is most commonly used in machines with rotating pieces, bearings that sustain wear, and those that may leak, including:
✔ Pumps
✔ Motors
✔ Gearboxes
✔ Compressors
Vibration analysis uses sensors to measure vibration patterns in rotating machinery, which have characteristic vibration signatures reflecting parameters like balance and bearing condition.
Thermal analysis in condition monitoring focuses on detecting the presence of developing faults by capturing the heat emitted from assets and analyzing the images to reveal potential failures such as worn parts, excess heat, or thermal anomalies. Thermography is a non-contact method using cameras to detect infrared thermal emissions, providing early warning of emerging problems.
Oil analysis in condition monitoring involves testing lubricants, hydraulic fluids, and other liquids to reveal signs of contamination and wear. It measures constituents and parameters to assess oil conditions and identify wear in machine components. While full contamination testing must be sent to and analyzed by a laboratory, sensors can be installed in lubrication systems for continuous oil level and temperature monitoring. An example of oil analysis results is shown below.
Learn more on how to take an oil sample.
Acoustic analysis in maintenance is broadly categorized into sonic and ultrasonic techniques. Sonic analysis typically applies to lubrication analysis, identifying insufficient or degraded lubrication issues. Ultrasonic monitoring can be used to detect leaks, cavitation, and improperly seated parts by capturing high-frequency sounds emitted from these anomalies. Acoustic analysis captures sound waves generated by machinery, helping to detect abnormalities that indicate potential issues.
Establishing a condition-based monitoring program requires a structured approach. First and foremost, any conditioning monitoring system needs to define baseline limits to warn when equipment starts deteriorating. Another essential task is establishing an equipment register to document all assets within the facility and evaluate their criticality to overall operations. This allows for developing appropriate condition-monitoring techniques, technologies, or strategies.
The four pillars of implementing condition monitoring are:
1. Detection: using sensors and data collection tools to gather information about the equipment’s performance.
2. Diagnosis: analyzing the performance data to determine abnormalities or patterns indicating an impending failure.
3. Prognosis: data analysis to predict the remaining useful life of the equipment.
4. Program: developing and implementing a maintenance program based on the findings of the analysis.
Different systems collect data in various ways, such as:
✔ Installing sensors in motor control cabinets
✔ Using handheld thermal sensors
✔ Electrical monitoring, which provides real-time analysis of electrical parameters like voltage and current
✔ Vibration monitoring tools, which consist of sensors, data acquisition hardware, and condition monitoring software.
Analog to digital converters (ADCs) in data acquisition systems transform analog signals into digital data for analysis. Signal conditioning circuitry in data acquisition units prepares the analog signal from sensors for acquisition by ADC.
Here’s how you can get started with condition monitoring and optimize asset health:
Conduct an initial baseline survey to record essential information about assets, assess asset criticality, and identify warning signs before breakdowns.
✔ Record essential information about assets
✔ Assess asset criticality
✔ Identify warning signs before breakdowns
Establish standards for performance metrics. These can include indicators like temperature, vibration monitoring, and oil analysis results.
Select suitable condition monitoring techniques such as vibration analysis, oil analysis, and acoustic analysis, aligning them with the condition monitoring objectives above.
Make the process easier and more efficient by utilizing technology and data collection to continuously monitor asset health and alert maintenance teams to potential issues in real-time
Certain tasks, such as sending routine hydraulic fluid testing to a lab, cannot be fully automated. For these assets, it's essential to establish a timed preventive maintenance schedule to ensure they are properly managed.
Train staff by providing training in areas such as vibration and oil analysis to help them understand indicators and know when to seek technical assistance. Also train them in how to utilize any connected technologies, managing alerts, etc.
Condition monitoring software ranges from basic tools offering statistical values to advanced systems for raw data analysis and historical trend visualization. An intuitive dashboard can help visualize performance data and requires little training, making it essential for user adoption and efficient operations.
The fusion of AI with IIoT facilitates intelligent decision-making. It analyzes patterns and deviations in data gathered from sensors and connected devices, thereby:
📱 Alerting maintenance teams about any detrimental changes in asset condition
📈 Offering real-time insights into the health and performance of industrial machinery
👍 Allowing for remote monitoring and control
🌍 Enabling manufacturers to oversee operations globally and create a more responsive production environment.
✔ Placing monitoring devices on critical assets to collect data and share it with connected systems for analysis
✔ Ensuring compatibility between monitoring devices and existing infrastructure is crucial
✔ To capture accurate data on equipment performance, devices must be properly installed.
✔ Setting up alert mechanisms and defining baseline performance metrics.
| Interested in these Condition Monitoring Technologies? Learn more here. |
The Asset Monitoring Gateway (AMG) by Banner Engineering provides real-time insights into the operation and performance of assets in your facility. Watch our video of the AMG in action at Airline’s facility and see how easy it is to use.
Condition monitoring is a game-changer in industrial maintenance. By detecting potential issues before they escalate into major failures, it enables proactive maintenance, reduces unplanned downtime, and enhances machine performance and employee safety. Techniques such as vibration analysis, oil analysis, acoustic analysis, and thermal analysis provide valuable insights into machinery health.
Implementing a condition monitoring system requires a structured approach, incorporating data collection methods and choosing the appropriate software to meet business needs. The integration of IIoT further enhances condition monitoring by offering real-time insights and intelligent decision-making capabilities. Embrace condition monitoring to protect your assets and optimize your maintenance processes.