eWorkOrders Predictive Maintenance Program empowers organizations with additional tools to create more accurate predictions on when a piece of equipment will require maintenance or replacement. Predictive Maintenance is a condition-based maintenance program where assets are monitored with sensor devices that supply data about the asset’s operation and possible defects. The data is used to predict when the asset will require maintenance or replacement.
eWorkOrders CMMS software solution will automatically create a work order when it detects that an asset has fallen outside of the defined parameters. Alerts will be sent to the maintenance team to assess and repair the issue. With the alerts being identified and sent directly to the technicians in real-time, the elimination of extensive downtime is minimized.
What is Predictive Maintenance
Predictive maintenance (PdM) is a proactive maintenance strategy that tracks and monitors the performance and condition of equipment during normal operation. These monitoring tools detect various deterioration signs, anomalies, and equipment performance issues. Based on these measurements, maintenance work can be done just before a failure happens.
Predictive vs. Preventive Maintenance
Predictive Maintenance monitors the performance and condition of equipment during normal production operations. Predictive Maintenance estimates the exact moment of a failure, and repairs can be scheduled when necessary. This is a cost-effective approach with minimal impact on production.
Preventive Maintenance tasks are completed based on a recurring time schedule or a given amount of usage or cycles. A planned and scheduled maintenance routine is put in place to extend the life of assets and reduce downtime. The maintenance is performed on predetermined assumptions, based on manufacturers’ recommendations or history.
Predictive Maintenance Objective
The main objective of Predictive Maintenance is to first predict when equipment failure might occur (based on certain factors), and be able to prevent the failure with regularly scheduled and corrective maintenance.
How Predictive Maintenance Works
Predictive Maintenance depends on condition monitoring, which collects and analyzes data from the machine during operations, to ensure the optimal use of equipment.
There are three main elements that allow PdM to track asset conditions and alert technicians about projected equipment failures:
- With real-time tracking, each piece of equipment is monitored through installed and fitted sensors that capture data about equipment deterioration and performance.
- Internet of Things (IoT) technology collects and shares the data enabling the assets to communicate, work together, analyze data, and recommend appropriate action to be taken directly based on how the system is set up.
- Predictive Data collected is analyzed using predictive algorithms that identify trends when an asset will require repair, servicing, or replacement.
Predictive Maintenance/Condition Monitoring Techniques
There are numerous condition-monitoring devices and techniques that can be used for effectively predicting failure, as well as providing advanced warnings for maintenance teams. Some of them include:
Infrared Thermography / Temperature Measurement
Infrared thermography is used to detect heat variations in machines and equipment. By capturing thermal images, infrared cameras help identify overheating components, allowing technicians to address potential failures before they escalate.
Ultrasonic Monitoring / Acoustic Analysis
This method uses high-frequency sound waves to assess the condition of bearings, rotating parts, and other machinery. It helps detect leaks, gear faults, and lubrication issues that could lead to equipment failure.
Vibration Analysis / Dynamic Monitoring
Vibration analysis is essential for high-speed rotating equipment, as it measures vibration patterns to assess a machine’s health. By analyzing these signals, technicians can detect imbalances, misalignments, or worn components before they cause major breakdowns.
Oil Analysis / Tribology
By examining oil samples, technicians can determine the presence of contaminants, metal particles, or signs of wear. This helps ensure proper lubrication and prolongs the life of mechanical components.
Laser Interferometry
A precision measurement technique that uses laser-generated wavelengths to detect even the smallest changes in wave displacement. This method is valuable for ensuring structural integrity and component alignment.
Motor Circuit Analysis
This process involves computerized testing of electric motors to evaluate their overall condition. It helps identify faults, insulation breakdowns, and early signs of electrical failure, ensuring reliability.
Radiography / Neutron Imaging
This technique uses radiation to inspect internal structures and detect hidden defects in machinery. It provides a non-destructive way to assess material integrity and prevent failures due to unseen damage.
What Circumstances Call For Predictive Maintenance?
Predictive maintenance (PdM) applications include those that: possess a crucial operational role and possess failure modes that are reasonably predictable with routine monitoring.
Some applications that predictive maintenance is not appropriate for include those that don’t perform a critical task and do not have a cost-effective predictable failure mode.
Who Uses Predictive Maintenance?
Predictive maintenance is widely used by maintenance managers, technicians, and asset management teams across various industries. Manufacturing, transportation, energy, and facilities management sectors rely on predictive maintenance technologies and asset management systems to monitor impending equipment failures and plan maintenance tasks effectively. By leveraging data-driven insights, these industries can optimize asset performance, reduce downtime, and improve operational efficiency.”
A Few Examples of Predictive Maintenance
Prevention of Power Outages
Power outages can be extremely inconvenient for those affected, and they can even be fatal in places like hospitals or assisted care facilities. They can be prevented by using predictive maintenance technology, which allows for early detection. Using cloud-based computers and artificial intelligence, sensors offer information about assets. Companies in the energy sector are informed by this knowledge when equipment failure is most likely to occur.
Building Management
With the aid of environmental monitoring and software for ventilation and energy management, buildings can be managed and controlled remotely. By using sensors tailored to the desired result, owners and managers can also control the temperature of the building environment and monitor humidity or moisture. The sensors provide the data to cloud-based data analysis tools, which enable you to spot anomalies or changes over time and schedule maintenance as necessary. This kind of monitoring can reduce the building’s overall energy costs. Building Management Since a manufacturing plant tends to have many costly assets and valuable equipment, they might invest in infrared imagers to monitor aspects of assets, such as temperature, to prevent overheating. This predictive maintenance system helps plants avoid overusing essential equipment, pushing machinery to the point of disruptive breakdowns.
Benefits
- Fewer asset failures result in reduced downtime.
- Reduced total labor time and cost spent on equipment maintenance.
- Automatic insights into your data.
- Control of spare parts inventory
- Improves worker and environmental safety.
- Increases employee efficiency.
- Increases production and ROI with properly maintained equipment.
Remote Monitoring
Automatically taking readings and entering them into eWorkOrders is possible by connecting an IoT sensor device to your equipment. When conditions fall outside the set parameters, a work order is generated and sent to a technician for an inspection or repair.
Reporting
Sensor readings can be used to display graphs or exported into a spreadsheet for a specific date range. Reports for detailing predictive maintenance work orders and asset history are easily generated.
Additional Expense
Depending on your needs, implementing a Predictive Maintenance Program requires some additional purchase of hardware, such as equipment for monitoring assets: Vibration, Thermography, Oil Analysis, or Ultrasonic.
Implementing a Predictive Maintenance Program in your facility requires additional employee training on the use of the equipment and interpreting the analysis.
Predictive Maintenance and CMMS
As businesses move from reactive to proactive to predictive maintenance, computerized maintenance management software (CMMS) plays a critical part to help facilitate predictive maintenance.
To be successful PdM requires the right balance of technology and human interaction. CMMS makes the process easier and here is why:
- CMMS is the engine that drives the PdM functionality. All of the information on asset performance that has been gathered and stored throughout the years in your CMMS is a starting point and the initial dataset before PdM implementation.
- CMMS integrates with PdM technology to generate alerts and work orders. With condition-monitoring sensor integration, some CMMS can automatically create an alert or generate a work order whenever sensors detect that an asset is operating outside predefined parameters. These alerts prompt the maintenance team to take preventive actions before the machine fails and causes unexpected downtime.
- CMMS is a centralized system that gathers and stores all of the information into one centralized platform that is accessible at any time from anywhere.
Predictive Maintenance and Return on Investment (ROI)
Implementing a predictive maintenance program requires a significant investment in money, resources, and training. In taking these things into consideration the initial investment into predictive maintenance’s return on investment (ROI) far outweighs any of these costs.
The reasons why:
- Reactive maintenance costs, resource time, loss of productivity, inventory backlog, delays in production, equipment downtime, and more are all hitting your bottom line.
- Having access to more accurate data gives you the ability to extend equipment life and improve the efficiency of maintenance operations.
eWorkOrders CMMS Predictive Maintenance
Predictive Maintenance (PdM) gives you the ability to predict failures and monitor performance on your most important assets. While the costs of investing in PdM technology may seem to be very high, over time this solution can provide significant ROI cost savings and better machine performance.
Linking the condition monitoring data to your CMMS allows for quicker dispatching of technicians, making it easier for repairs to get done faster. With eWorkOrders CMMS Predictive Maintenance you can define equipment operation boundaries, import the readings, graph results and automatically trigger an email to generate a work order when the readings go outside of the set boundaries. Having all of your data stored within a CMMS can help improve asset reliability, reduce costs and increase the efficiency of your maintenance operations.
If you are interested in learning about Predictive Maintenance or any of the other CMMS features, please feel free to contact one of our account executives, who will answer your questions and provide you with a free demo
