Studies have shown that organizations spend approximately 80% of their time reacting to issues rather than proactively preventing them. Predictive maintenance puts predictive maintenance ahead of the game. It helps predict failures and actively monitor performance. As a result, it 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, such as:
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 predictive maintenance programs take time to develop, implement and perfect. The timeline to achieve gains such as these varies, but some clients see positive returns in as little as a year.
Advantages & disadvantages of predictive maintenance
Predictive maintenance 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, predictive maintenance 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.
What to do when predictive maintenance does not make sense
Sometimes predictive maintenance is not the answer to maintenance woes. It might not be the most cost-effective method to manage all assets with predictive maintenance. For example, changing light bulbs 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 predictive maintenance program: Get positive buy in from management and be prepared to discuss and quantify the benefits and goals. Identify which equipment to target for the program by taking 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 predictive maintenance to the average cost of equipment failures. As stated above, sometimes predictive maintenance does not make sense. Depending on the asset, a corrective method of maintenance could be cheaper.
2. Select predictive maintenance technology: Choose which of the above technologies 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 predictive maintenance activities. Carve out time in the schedule for predictive maintenance tasks such as data collection, analysis, reporting and tracking, and allocate funding for predictive maintenance technology investments or, for a predictive maintenance, contractor to assist.
4. Perform system integrations: Leverage the tools within and integrated into a CMMS to help turn condition monitoring data into action. For example, a company offering equipment monitoring services, lubrication engineering and reliability engineering can record negative diagnostic reports and automatically generate corrective work orders.
5. Coordinate preventive maintenance & predictive maintenance 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 reporting and dashboard tools, organizations can consistently document work order history, failures, costs and trends. This helps to track progress for key stakeholders.