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Achieving Precise Equipment Maintenance through
Condition Monitoring

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Condition Monitoring
Condition Monitoring

In industrial settings, unplanned downtime disrupts production schedules, leads to missed deadlines, and results in increased costs. The traditional "run-to-failure" approach is no longer sufficient to meet the demands of industrial businesses. Predictive maintenance offers a solution for industrial businesses enabling them to shift from costly reactive maintenance to a proactive approach that can significantly reduce costs in the long run. 

Condition monitoring employs a suite of advanced monitoring techniques such as vibration analysis, thermography, oil analysis, and ultrasound testing that have the ability to detect the subtlest indicators of potential equipment failure. Armed with this data, maintenance teams are able to intervene early, prevent breakdowns, optimize maintenance efforts, and elevate the efficiency of their maintenance operations.

What is Condition Monitoring?

Condition monitoring is a systematic process of continuously monitoring the health and performance of critical assets and equipment to detect early signs of faults, deviations, or potential failures. The goal of condition monitoring is to predict and prevent equipment failures, enabling proactive maintenance actions that reduce downtime, optimize resource allocation, and enhance overall operational efficiency.

Manual vs. Automated Condition Monitoring

Manual condition monitoring involves periodic inspections and measurements performed by maintenance personnel. It relies on visual observations, handheld measurement devices, and simple diagnostic tools. While manual monitoring can be effective for some basic assessments, it’s limited in terms of frequency and coverage, and relies heavily on the expertise of the personnel involved.

Automated condition monitoring, on the other hand, involves the use of sensors, monitoring devices, and data analytics to continuously collect and analyze data in real-time. The process is automated, reducing the reliance on human intervention and provides more comprehensive and consistent monitoring. Automated systems detect subtle changes and deviations in equipment behavior, triggering alerts and alarms when abnormalities are detected. This enables maintenance teams to respond swiftly to potential issues, improving equipment reliability and minimizing downtime.

Condition Monitoring and the PF Curve

The P-F Curve is a concept directly related to condition monitoring. It provides insights into the progression of equipment deterioration and helps maintenance teams implement proactive measures to prevent failures. The P-F Curve is a graphical representation, showing the degradation process of equipment from the point in time when a potential failure (P) starts to the point of functional failure (F). The following is a break down the P-F Curve stages and how condition monitoring helps at each stage:


1. P-F Interval

The interval between the potential failure (P) and functional failure (F) is known as the P-F Interval. It represents the window of opportunity during which maintenance teams can take action to prevent the equipment from reaching its functional failure point.

Condition monitoring plays a crucial role in this stage by detecting early signs of degradation, providing maintenance personnel with an early warning that maintenance action is required.

2. Potential Failure (P)

The P-F Curve starts with the potential failure (P) stage, which indicates the beginning of equipment degradation. At this point, the asset shows minor deviations from normal operating conditions, and the changes may not be evident without the aid of condition monitoring. Identifying potential failures is vital as it allows maintenance teams to address the issues before they escalate into major faults causing breakdowns and costly downtime. 

3. Functional Failure (F)

The functional failure (F) stage is the point at which the equipment can no longer perform its intended function. At this stage, the asset is likely to experience a significant breakdown, leading to downtime, production losses, and costly repairs or replacements. 

Understanding the P-F Curve helps maintenance teams plan and execute condition-based or predictive maintenance (PdM) at an optimal time during the P-F Interval. This proactive approach helps extend the useful life of assets, reduce unplanned downtime, and minimize the risk of equipment-related incidents.

Key Components of a Condition Monitoring System

A well-designed condition monitoring system consists of components that work together that monitor and provide data on equipment health. Each component plays a crucial role in the overall functionality of the system. Some of these components are:

1. Sensors and Monitoring Devices

These devices are responsible for collecting data from the equipment being monitored. Various types of sensors are used to measure different parameters, such as:

  • Vibration sensors: Measure the vibrations produced by rotating machinery, helping detect misalignments, imbalance, and defects.
  • Temperature sensors: Monitor the temperature of critical components to identify overheating or abnormal temperature fluctuations.
  • Pressure sensors: Measure fluid pressure in hydraulic and pneumatic systems, detecting potential leaks or pressure variations.
  • Oil analysis sensors: Analyze the quality and condition of lubricating oil to identify contaminants, degradation, and debris.
  • Acoustic sensors: Detect abnormal sounds and noise patterns that indicate potential equipment issues.

2. Data Acquisition System

The data acquired from the sensors needs to be collected and transmitted for further analysis. A data acquisition system ensures that the data is accurately captured, digitized, and sent to the central monitoring unit. It serves as a bridge between the physical sensors and the data analysis software.

3. Data Analysis Software

The collected data from the sensors requires extensive analysis to uncover patterns, trends, and deviations that indicate potential asset health issues. Software like a CMMS processes and interprets the data, using various algorithms and techniques to identify anomalies and potential faults. It provides maintenance teams with actionable insights and diagnostic information.

4. Central Monitoring Unit

The central monitoring unit acts as the central nervous system of the condition monitoring system. It receives and stores the data collected from the sensors and houses the data analysis software. This unit provides a centralized platform for real-time monitoring, data management, and decision-making.

5. Alert and Notification System

The alert and notification system promptly notifies maintenance personnel when abnormal conditions or potential faults are detected. The system sends alerts through various channels, such as email, SMS, or mobile devices, ensuring that relevant personnel are promptly informed to take appropriate actions.

6. Diagnostic and Reporting Tools

To assist maintenance teams in understanding equipment health and making informed decisions, the condition monitoring system provides diagnostic tools and comprehensive reporting features. These tools present data analysis results in graphical reports and dashboards, making data easy to interpret.

7. Integration with CMMS

Integrating the condition monitoring system with a Computerized Maintenance Management System (CMMS) enhances the overall maintenance process. The CMMS incorporates equipment health data from the condition monitoring system, allowing maintenance teams to prioritize and schedule maintenance tasks efficiently. It also helps in managing work orders, spare parts and inventory, and maintenance history.

Condition Monitoring Workflow Coupled with a CMMS

  • sensor installation
    Step 1:

    Sensor Installation

    The first step in implementing condition monitoring is the installation of sensors and monitoring devices on the equipment. These sensors are placed on the assets to capture relevant data, such as vibration, temperature, pressure, oil quality, acoustic emissions, or electrical parameters.

    Role of a CMMS

    A Computerized Maintenance Management System (CMMS) facilitates the management of sensor installations. The CMMS stores information about the sensors' locations, calibration schedules, maintenance requirements and supplier information for ordering.

  • data collection
    Step 2:

    Data Collection

    Sensors collect data from the monitored equipment in the form of vibration patterns, temperature, air pressure or humidity readings, oil analysis results, or other. The frequency of data collection depends on the criticality of the equipment and the monitoring requirements.

    Role of a CMMS

    The CMMS serves as a central repository for all the collected data. It receives, stores, and organizes the information gathered by the sensors, making it easily accessible for further analysis.

  • data analysis
    Step 3:

    Data Analysis

    Once the data is collected, it is processed and analyzed using various techniques and algorithms. The analysis may involve comparing the collected data against established baselines, statistical models, or predefined thresholds to detect any deviations from normal operating conditions.

    Role of a CMMS

    An advanced CMMS comes with built-in analytical capabilities or integrates with specialized condition monitoring software. This integration enables the CMMS to analyze the data, simplifying the process for maintenance teams.

  • failure detection
    Step 4:

    Failure Detection

    The primary objective of condition monitoring is to detect early signs of failure or abnormalities. Through data analysis, the system can identify irregular patterns or changes in the equipment's behavior that may indicate potential issues.

    Role of a CMMS

    The CMMS generates automatic alerts and notifications when it identifies potential faults. Automatica alerts and notifications can be configured with the CMMS through custom workflows. These alerts are sent to designated maintenance personnel, ensuring timely attention to emerging issues.

  • diagnostic insights
    Step 5:

    Diagnostic Insights

    The data analysis provides valuable diagnostic insights into the health of the equipment being monitored. It helps maintenance teams understand the root cause of potential issues and assess the severity of the problem.

    Role of a CMMS

    The CMMS stores historical data and maintenance records, enabling maintenance personnel to compare current performance with past trends. This assists in diagnosing the problem and understanding its development over time.

  • condition assessment
    Step 6:

    Condition Assessment

    Based on the diagnostic insights, the system assesses the condition of the equipment and assigns a health or condition score. This score helps maintenance teams prioritize maintenance actions based on the criticality of the equipment and the severity of detected issues.

    Role of a CMMS

    The CMMS facilitates tracking condition scores and maintenance priorities for each asset. Maintenance teams can access this information through the CMMS dashboard, helping them plan maintenance tasks or assign work orders efficiently. Scores can also be used by maintenance managers for condition assessments which help in determining if equipment should be replaced.

  • alert and reporting
    Step 7:

    Alerts and Reporting

    When the condition monitoring system identifies abnormal conditions or potential faults, it generates alerts and reports. Maintenance personnel receive these notifications in real-time, allowing them to take immediate action to address the emerging problems.

    Role of a CMMS

    The CMMS acts as the communication hub, disseminating alerts and reports to the appropriate personnel, ensuring that the right people are notified promptly.

  • proactive maintenance
    Step 8:

    Proactive Maintenance

    Armed with the information from condition monitoring, maintenance teams can implement proactive maintenance strategies. They can schedule maintenance activities based on the actual condition of the equipment, optimizing the use of resources and reducing unplanned downtime.

    Role of a CMMS

    The CMMS serves as the backbone of proactive maintenance strategies by organizing and optimizing maintenance schedules, streamlining work orders, and managing spare parts inventory needed to complete the maintenance activities.

What Types of Equipment Should Condition Monitoring be Applied to?

Condition monitoring can be applied to a wide range of industrial equipment, helping organizations maintain critical assets in optimal working condition. The suitability of equipment for condition monitoring depends on factors such as the equipment's criticality, complexity, and the potential impact of failures. Here are some common types of equipment that are suitable for condition monitoring:

1. Rotating Machinery

Rotating equipment, such as motors, pumps, compressors, turbines, and fans, are ideal candidates for condition monitoring. Vibration analysis is particularly effective for detecting issues in rotating machinery, as abnormal vibrations often indicate misalignment, imbalance, bearing wear, or other faults.

2. Electrical Systems

Electrical equipment, including transformers, circuit breakers, and switchgears can benefit from condition monitoring. Electrical parameters like current, voltage, and insulation resistance can be monitored to detect anomalies, overheating, or electrical faults.

3. Hydraulic Systems

Hydraulic equipment, like hydraulic pumps and valves are key components in many industrial settings. Condition monitoring techniques monitor parameters like pressure, flow rates, and fluid quality to identify potential issues and avoid failures. 

4. Air Compressor Systems

Air compressor systems are commonplace in various industries. Monitoring air pressure, temperature, and vibration in compressors helps detect faults early on, ensuring the reliable and energy-efficient operation of the system.

5. Cooling Systems

Cooling systems, including chillers and cooling towers, are critical for temperature regulation in industrial processes. Condition monitoring record temperature, flow rates, and refrigerant conditions to ensure optimal cooling performance.

6. Bearings and Gearboxes

Bearings and gearboxes are essential components in machinery. Vibration analysis and oil analysis help detect bearing wear, lubrication issues, and gearbox misalignments, enabling quick action to prevent severe damage.

7. Motors and Generators

Electric motors and generators are ubiquitous in industrial settings. Condition monitoring techniques monitor parameters like temperature, current, and insulation condition to detect motor faults and potential winding failures.

Factors Influencing the Effectiveness of Condition Monitoring

While condition monitoring offers numerous benefits, its effectiveness depends on several key factors that organizations should consider to ensure successful implementation:


Proper Sensor Selection and Installation

Selecting the right PLC (Programmable Logic Controller) or sensor for each piece of equipment is important. Sensors must be suitable for the specific parameters to be monitored. Additionally, proper sensor installation, (correct positioning and calibration), ensures accurate data collection.


Data Quality and Integrity

The effectiveness of condition monitoring relies on the quality and integrity of the data collected. Ensuring data accuracy, consistency, and timely transmission are essential to obtain reliable insights and avoid false alarms.


Frequency of Data Collection

The frequency of data collection should be appropriate for the equipment's criticality and operating conditions. High-criticality equipment may require continuous or frequent data monitoring, while less critical assets may need periodic checks. The frequency would also determine if the organization should rely on manual or automated condition monitoring. And in the case of automated monitoring, determine if PLC or battery operated sensors should be used.


Data Analysis and Expertise

It’s important to have the help of skilled personnel with expertise in data analysis for condition monitoring to be a success. Properly trained analysts can identify early signs of issues, make accurate diagnoses, and recommend appropriate maintenance actions.


Integration with Maintenance Practices

Effective Condition Monitoring requires seamless integration with existing maintenance practices. The data and insights from Condition Monitoring must be integrated into the organization's Computerized Maintenance Management System (CMMS) for streamlined maintenance planning and execution.

Step-by-Step Process to Set up a Condition Monitoring Program

Implementing a robust condition monitoring program is crucial for optimizing equipment reliability, minimizing downtime, and maximizing operational efficiency. Here is a step-by-step guide to help set up an effective condition monitoring program for an organization:

  • conduct a site survey
    Step 1:

    Conduct a Site Survey and Asset Assessment

    The first step is to conduct a comprehensive site survey to assess your facility's critical assets. Identify the equipment and systems that are vital to your operations and have a significant impact on productivity. Use the equipment criticality assessment matrix to prioritize assets based on their criticality and potential consequences of failure.

  • right condition monitoring techniques
    Step 2:

    Select the Right Condition Monitoring Techniques for Your Equipment

    Once you have identified the critical assets, determine the appropriate condition monitoring techniques for each piece of equipment. Consider factors such as the equipment type, operating conditions, failure modes, and maintenance history. Common techniques include vibration analysis, thermography, oil analysis, and ultrasound testing. Tailor your approach to suit the specific needs of your equipment.

  • frequency-of-maintenance
    Step 3:

    Integrate Data Collection and Analysis Tools

    Invest in modern data collection and analysis tools that align with the selected condition monitoring techniques. This may include acquiring vibration analyzers, infrared cameras, oil analysis kits, ultrasound devices, and data management software. Ensure these tools are compatible with your existing CMMS software for streamlined data integration.

  • train maintenance teams
    Step 4:

    Train Maintenance Teams

    Properly trained personnel are essential for the success of the condition monitoring program. Train maintenance teams and personnel responsible for data collection and analysis in the selected techniques. Ensure they understand the principles behind each method and how to interpret and act on the results.

Return on Investment (ROI) Calculation for Condition Monitoring

Calculating the return on investment (ROI) for condition monitoring involves assessing the financial benefits gained from the implementation of the monitoring program against the costs associated with its setup and maintenance. Here's a step-by-step guide on how to calculate the ROI of condition monitoring:

1. Identify the Costs

Start by identifying all the costs associated with setting up and maintaining the condition monitoring program. These costs may include:

  • Equipment and sensor costs: Purchase or lease costs of the monitoring devices, sensors, and data collection tools.
  • Training and education: Expenses related to training personnel in using the monitoring equipment and interpreting the data.
  • Implementation costs: Costs involved in setting up the infrastructure and integrating the monitoring system with existing maintenance processes.
  • Maintenance costs: Ongoing expenses for calibration, maintenance, and regular servicing of the monitoring equipment.

2. Quantify the Benefits

Next, determine the financial benefits derived from the condition monitoring program. These benefits may include:

  • Reduced downtime: Calculate the cost savings from reduced unplanned downtime, avoiding production losses and missed deadlines.
  • Lower maintenance costs: Assess the savings achieved through preventive maintenance, avoiding costly emergency repairs and component replacements.
  • Extended equipment lifespan: Calculate the cost savings resulting from prolonging the useful life of critical assets through proactive maintenance.
  • Energy efficiency improvements: Measure the energy savings achieved by identifying and rectifying inefficiencies through condition monitoring.
  • Safety improvements: Quantify the cost savings from accident prevention and reduced medical expenses or potential legal fees.

3. Assign Monetary Values

Convert both costs and benefits into monetary values to compare and evaluate the financial impact. Use actual data, historical records, and estimates based on industry benchmarks. 

4. Calculate ROI

The ROI is calculated using the following formula:

ROI = (Net Benefits / Total Costs) x 100

Net Benefits = Total Benefits - Total Costs

The ROI is expressed as a percentage, showing the return gained for every dollar invested in the condition monitoring program. A positive ROI indicates that the benefits outweigh the costs, making the investment financially viable.

5. Consider Intangible Benefits

While financial gains are essential, consider intangible benefits as well, such as improved workplace safety, better equipment reliability, and increased employee morale. Though difficult to quantify in monetary terms, these intangible benefits contribute significantly to overall operational excellence.

6. Monitor and Review

Continuously monitor the performance of the condition monitoring program and regularly review the ROI calculation. As the program matures, analyze the actual cost savings and benefits achieved compared to initial projections, making necessary adjustments to optimize the ROI.

Importance of Data Management and Analysis

With the advent of advanced analytics, machine learning, cloud-based solutions, and the ability to interpret data for proactive decision making, organizations can harness the full potential of their condition monitoring data to optimize equipment performance, minimize downtime, and improve operational efficiency.

1. Using Advanced Analytics and Machine Learning

Condition monitoring generates vast amounts of data from various techniques such as vibration analysis, thermography, oil analysis, and ultrasound testing. The sheer volume of data can be overwhelming without the aid of advanced analytics and machine learning.

Benefits of Advanced Analytics and Machine Learning

  • Data Pattern Recognition: Advanced analytics can identify patterns, trends, and anomalies within data that might not be apparent through manual analysis. Machine learning algorithms continuously learn from new data, improving the accuracy of fault detection and diagnosis over time.
  • Predictive Maintenance: Machine learning models can predict equipment failures by analyzing historical data and identifying early warning signs of potential issues. This enables proactive maintenance scheduling and minimizes unexpected breakdowns.
  • Optimal Maintenance Strategies: Advanced analytics can help determine the most cost-effective maintenance strategies based on equipment health, criticality, and historical performance data, optimizing maintenance efforts and resources.

2. Cloud-Based Solutions for Condition Monitoring

Traditional data storage and analysis methods may not be sufficient to handle the large volume and complexity of condition monitoring data. Cloud-based solutions offer scalable and secure platforms for storing, managing, and analyzing data.

Benefits of Cloud-Based Solutions such as CMMS

  • Data Accessibility: Cloud-based platforms enable real-time access to condition monitoring data from anywhere, facilitating remote monitoring and decision-making.
  • Scalability: Cloud solutions can easily accommodate growing data volumes and adapt to changing organizational needs without requiring significant infrastructure investments. 
  • Collaboration and Integration: Cloud-based platforms promote collaboration among maintenance teams, reliability engineers, and data analysts by providing centralized access to data from multiple geographically remote sites and analysis tools.
  • Data Security: Cloud-based solution vendors implement robust security measures, ensuring that sensitive condition monitoring data is protected from unauthorized access and potential data breaches. Read our article on CMMS Data Security to learn how we make this possible.

3. Interpreting Data for Proactive Decision Making

Accurate interpretation of condition monitoring data is important for making informed and proactive maintenance decisions. Trained personnel play a crucial role in extracting valuable insights from the data.

Benefits of Proactive Decision Making

  • Early Fault Detection: Timely data interpretation helps identify early signs of equipment degradation or impending failures, allowing for prompt maintenance actions before issues escalate.
  • Optimized Maintenance Scheduling: Interpreted data facilitates the implementation of condition-based or predictive maintenance strategies, reducing unnecessary maintenance activities and associated costs.
  • Improved Reliability and Performance: Proactive decision making ensures that critical assets operate at their peak performance, leading to enhanced equipment reliability and increased overall operational efficiency.

Implementing a comprehensive condition monitoring program brings a multitude of benefits to an organization that extend far beyond maintenance. From reducing downtime and extending equipment lifespan to optimizing resource allocation and enhancing workplace safety, condition monitoring empowers organizations to elevate their operational efficiency and gain a competitive edge in the market. By harnessing the power of predictive maintenance, businesses can stay one step ahead of equipment failures and costly breakdowns, ensuring seamless production and uninterrupted workflows.

Condition monitoring coupled with a CMMS is a winning combination that drives organizations towards operational excellence. With condition monitoring and a CMMS by their side, organizations can embark on a journey of reliability, cost-effectiveness, and improved productivity, ensuring that maintenance management becomes a strategic advantage that propels them to greater heights.