What is Predictive Maintenance (PdM)?
Predictive Maintenance (PdM) is maintenance that directly monitors the condition and performance of equipment during normal operation to reduce the likelihood of failures. Predictive maintenance attempts to keep costs low by reducing the frequency of maintenance tasks, reducing unplanned breakdowns, and eliminating unnecessary preventive maintenance.
With PdM, organizations consistently monitor and test conditions such as lubrication and corrosion. Methods for accomplishing PdM include infrared testing, acoustic (partial discharge and airborne ultrasonic), vibration analysis, sound level measurements and oil analysis. Computerized Maintenance Management Systems (CMMS) can also facilitate success with condition monitoring.
For example, eMaint CMMS empowers companies to define boundaries for acceptable equipment operation, import readings, graph results and automatically trigger an email or generate a work order when boundaries are exceeded.
Predictive vs. Preventive Maintenance
Though the best maintenance programs include a balance of both, preventive maintenance (PM) and predictive maintenance are different strategies. PM is determined using the average or expected life cycle of an asset, where PdM is identified based on the condition of equipment.
While predictive maintenance is more complex to establish than a preventive maintenance schedule based on manufacturer recommendations, it can be more effective for a business to save time and money. For example, taking vibration measurements on an electric engine at recommended intervals more accurately detects bearing wear, and allows organizations to take action such as replacing a bearing before total failure occurs.
How does Predictive Maintenance work?
PdM evaluates the condition of equipment by performing periodic or continuous (online) equipment condition monitoring. Most PdM is performed while equipment is operating normally to minimize disruption of everyday operations. This maintenance strategy leverages the principles of statistical process control to determine when maintenance tasks will be needed in the future.
For example, rather than changing a vehicle’s oil because drives hit 3,000 miles, PdM empowers organizations to collect oil sample data and change the oil based on the results of asset wear. For predictive maintenance to be effective, it requires both hardware to monitor the equipment and software to generate the corrective work order when a potential problem is detected. Specific types of Predictive Maintenance includes:
- Vibration analysis: Vibration sensors can be used to detect degradation in performance for equipment such pumps and motors.
- Infrared: Infrared cameras are often used to identify unusually high temperature conditions.
- Acoustic analysis: Acoustic analysis is performed with sonic or ultrasonic tests to find gas or liquid leaks.
- Oil analysis: Oil analysis determines asset wear by measuring an asset’s number and size of particles.
Additionally, tools such as eMaint CMMS and Fluke Condition Monitoring can help companies act on the analytics collected by these devices and sensors.
PdM Tools in a CMMS
Whether you need to track assets through oil viscosity, temperature or vibration, the tools within CMMS systems can help develop accurate predictions when a piece of equipment will require maintenance or replacement.
Condition Monitoring – Within CMMS systems, condition monitoring tools help empower organizations to execute on predictive maintenance programs. eMaint allows users to define boundaries of acceptable operation for assets, and auto-generate work order or emails when readings fall outside of predefined boundaries.
Fluke Condition Monitoring – Sensors such as Fluke Condition Monitoring (FCM) offer real-time data streams to track events from anywhere and view AC/DC voltage, current, power and temperature data. By wirelessly syncing measurements taken using Fluke Connect handheld tools and comparing them to condition monitoring data, organizations can gain the full picture of equipment efficiency and health.
How much can you benefit from Predictive Maintenance?
Studies have shown that organizations spend about 80% of their time reacting to issues rather than proactively preventing them. PdM puts predictive maintenance ahead of the game, and helps predict failures and activity monitor performance and as a result, saves time and money. Organizations that commit to a predictive maintenance program can expect to see significant improvements in asset reliability and a boost in cost efficiency. Our customers at eMaint have also seen:
- 10x Return on Investment (ROI)
- 25-30% reduction in maintenance costs
- 70-75% elimination of breakdowns
- 35-45% reduction in downtime
- 20-25% increase in production
The best PdM programs take time to develop, implement and perfect. The timeline to achieve gains such as these varies, but eMaint clients, such as Cleveland Tubing, have seen positive returns in as little as a year.
Advantages & Disadvantages of Predictive Maintenance
PdM requires more time and effort to develop then a preventive maintenance schedule. To be truly effective, employees must be trained on how to use the equipment and interpret the analytics they pull. However, once the commitment is made, PdM can revitalize not only a maintenance team, but an organization as a whole. There are condition monitoring contractors who can perform the labor required and analyze the results for your organization.
When Predictive Maintenance Doesn’t Make Sense
However, sometimes PdM is not the answer to maintenance woes. It might not be the most cost-effective method to manage all assets with PdM. Take, for instance, changing lightbulbs on the plant floor. Rather than running diagnostics on the bulb, leveraging a run-to-failure strategy (waiting until the light bulb goes out to change it) makes more sense. There are a few factors to consider when identifying which assets should be considered for predictive maintenance:
- What is the impact on production if the asset failures unexpectedly?
- Can cost-effective tasks be performed proactively to prevent, or to diminish to a satisfactory degree, the consequences of the failure?
- What is the average cost of repairing this asset?
Applications of Predictive Maintenance
There are many applications of Predictive Maintenance in a wide variety of industries such as:
- Finding three-phase power imbalances from harmonic distortion, overloads, or degradation or failure of one or more phases
- Identifying motor amperage spikes or overheating from bad bearings or insulation breakdowns
- Locating potential overloads in electrical panels
- Measuring supply side and demand side power at a common coupling point to monitor power consumption
- Capturing increased temperatures within electrical panels to prevent component failures
- Detecting a drop in temperature in a steam pipeline that could indicate a pressure leak.
How to Implement a Predictive Maintenance Strategy
Implementing a predictive maintenance program should be a methodical process from start to finish. The key is to have a long-term view of what to do in order to put all of the foundational components into place.
1. Design the PdM Program
- Get positive buy in from management – be prepared to discuss and quantify the the benefits and goals of PdM.
- Identify which equipment to target for the program – take a close look at equipment failure histories and the associated root causes. Equipment that is failing the most will provide the most potential for cost reductions and reliability improvements.
- Compare the cost of implementing a PdM to the average cost of equipment failures. As stated above, sometimes PdM does not make sense, and depending on the asset, a corrective method of maintenance could be cheaper.
2. Select PdM Technology
- Choose which of the above technologies that would be most effective to monitor the condition of your equipment. Is your organization more interested in vibration analysis, infrared thermography, ultrasonic inspection, or oil analysis? Select the tools that will provide that information.
3. Allocate Proper Resources
- Develop and train an implementation team to perform PdM activities
- Carve out time in the schedule for PdM tasks such as data collection, analysis, reporting and tracking
- Allocate funding for PdM technology investments, or for a PdM contractor to assist
4. Perform System Integrations
- Leverage the tools within a CMMS to help turn condition monitoring data into action. For example, SEMEQ offers Equipment Monitoring Services, Lubrication Engineering and Reliability Engineering. When a negative diagnostic report is recorded by SEMEQ, eMaint can automatically generate a corrective work order.
5. Coordinate PM & PdM Programs
- Leveraging both Preventive and Predictive Maintenance makes for the best maintenance programs. Use each method where applicable, and decide which strategy to apply based on disruption due to equipment downtime, cost of parts and labor time, and equipment history.
6. Utilize CMMS Reports & Dashboards
- With eMaint’s reporting and dashboard tools, organizations can consistently document work order history, failures, costs and trends. This helps to track progress for key stakeholders.
Additional Resources on Predictive Maintenance
Interested in learning more about eMaint’s approach to Predictive Maintenance?
Visit our Predictive Maintenance Software Page.
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