Condition Monitoring and Predictive Maintenance (PdM) Software Information

Condition monitoring and predictive maintenance software is deployed in predicting equipment maintenance needs. It monitors corrosion, oil condition, bearing wear, overheating, and other settings leading to potential breakdown. The goal of condition monitoring is to identify components for repair before they fail. The software's ability to monitor machinery permits plant personnel to preempt catastrophic failures. It also assists in advance parts ordering, scheduling of manpower, and facilitates the planning of repairs during downtime.


Condition monitoring focuses on numerous parameters to identify substantive changes indicating the development of a fault. This function extends the useful lifespan of equipment by identifying troublesome areas before they cause major issues. It is performed on rotating devices and machinery such as presses, pumps, electric motors, and internal combustion engines.




Condition monitoring and predictive maintenance programs are distinguished by an array of features and purposes, including:


  • Infrared thermography
  • Lubricant analysis
  • Motor health monitoring and analysis
  • Vibration analysis and diagnostics
  • Acoustic emission
  • Material thickness and flaw testing 

Select functions of the program link to sensors supplying input data. These sensors include:


Dynamic accelerometers measure vibrations. This enables the prediction of the lifespan of parts and the detection of machinery faults. An assortment of accelerometer solutions is engaged in situations, including piezoelectric, unbonded strain gage, vibrating element, and Hall effect models. Piezoelectric units are the most commonly used accelerometers for this purpose.


Tachometers quantity a physical device's speed of rotation. Moreover, they measure its phase information, facilitating the matching of frequency components with the speed and position of a shaft.


Proximity probes calculate physical device displacement. They monitor rotating shaft movement. They are found in 90° offset pairs supporting the mapping of shaft movement via an X-Y plot. Doing so allows for the detection of imperfections. The deficiencies include shaft misalignment, faulty bearing, or numerous other circumstances inhibiting proper rotation.




The use of condition monitoring and predictive maintenance software has numerous advantages, including:

 PdM software for desktop and mobile devices

Predicting Equipment Failure


By predicting unplanned equipment failures, the technology reduces the occurrence of incidents. Given the potential for a tremendous cost associated with the breakdown of expensive capital assets, the capability to monitor these assets and predict when maintenance for avoiding catastrophic issues is required renders companies with a valuable service. Constant monitoring of equipment health executed by the system delivers more comprehensive coverage of such situations than traditional visual inspection methods.


Operating Condition


Solutions of this type let companies acquire a big picture view of the overall status of their equipment. If one piece of equipment exhibits signs of strain, other machinery can experience stress as well. In such cases, using plant downtime or shutting down the plant for a time to perform comprehensive equipment assessment and maintenance improves performance. This approach is more effective than a series of plant shutdowns to repair problems one by one.


Failure Prediction Accuracy


By integrating data from multiple sensors and indicators, the platform delivers a more comprehensive representation of equipment health. This integrated approach to data collection and analysis supports accurate evaluation to determine if extra maintenance is necessary. This process takes data from procedures, including vibration analysis, fault detection, and other disparate settings and considers them as a whole to generate a detailed report.


Reduced Condition Monitoring Costs


Traditional monitoring relied on highly trained analysts to determine if extra maintenance was warranted. Advanced applications incorporating "rule-based" analysis can reduce the dependence on constant human oversight of the activity. While human input is still required for high-level decision making, the systems present information related to remediation parameters, thereby reducing the labor costs traditionally associated with the activity.


Improving Equipment Reliability


The software aids in establishing the basis for systematic optimization of monitoring processes and procedures. This results in significant improvement in equipment reliability driven by lengthening mean times between failures for each piece of equipment. This is accomplished by taking steps to enhance the precision of maintenance tasks. The solutions assist in such endeavors by specifying actions allowing equipment to operate at optimal levels over its expected lifespan.




Condition monitoring and predictive maintenance software covers a diverse set of industries, including:


  • Wind energy
  • Hydroelectric power plants
  • Oil and gas
  • Astronomy
  • Computers
  • Semiconductors
  • Manufacturing
  • Utilities
  • Medical
  • Transportation

Selecting Condition Monitoring and Predictive Maintenance Software


Condition monitoring and predictive maintenance software must accomplish the following:


  • Integrate all data relating to machine health into one unified program
  • Support seamless sharing of data across functional lines
  • Minimize lengthy learning curves and software platform compatibility issues
  • Replicate its effects across all facilities


Check manufacturer's specifications to ensure a particular software package contains the functionality necessary to accommodate a planned usage prior to purchase.


Standards and Specifications


Condition monitoring technologies are covered under standards published by ASTM International and International Organization for Standards (ISO).


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eMaint Enterprises