What is predictive maintenance?

Predictive maintenance (PdM) is a maintenance approach using sensors and software to monitor real-time data on asset condition, preventing failures before they occur.

PdM directly monitors the condition and performance of equipment during normal operation. When a maintenance team knows the condition of every asset in real time, it reduces the chances of failures occurring. Once identified, a predicted failure can be prevented.

Predictive maintenance keeps costs low in several ways. It reduces:

  • The frequency of maintenance tasks
  • The number of unplanned breakdowns
  • The wasted resources of unnecessary preventive maintenance
What is predictive maintenance?

Organizations that use PdM monitor and test specific characteristics to identify conditional changes as they happen. There are numerous testing methods that can be used, including infrared testing, vibration analysis, oil analysis, and more.

There is not one best method—each method has its pros and cons, and each is best for different circumstances. Assets within the same facility may benefit from different maintenance strategies. Critical assets are generally monitored more closely. This can mean using more sensitive testing methods, more frequent monitoring, or both.

Effective asset management is crucial for organizations in today’s competitive environment. And, because planned maintenance is inherently less risky than reactive maintenance is, PdM creates a safer work environment.

Why is predictive maintenance important?

PdM allows for the best possible management of maintenance resources. Organizations invest a substantial amount of money in their assets. Increasing the availability and lifespan of those assets gives organizations the best return on their money.

Monitoring asset condition means that any changes can be identified early on, and problems can be resolved before failure occurs. Predictive maintenance means real-time asset health drives maintenance actions, which increases asset uptime and extends the asset lifecycle.

When the calendar dictates maintenance actions, on the other hand, some components are replaced before they need to be. There is also some risk incurred every time a machine is worked on. Preventive maintenance can be simpler to plan, but it uses more time, money, and parts.

When machines aren’t running optimally, one result can be finished products that don’t meet quality standards. Spotting and fixing issues early, to keep machines running as intended, reduces wasted materials, energy, and time.

What is the difference between predictive maintenance and preventive maintenance?

Preventive maintenance and predictive maintenance are simply different strategies. Preventive maintenance uses the expected life cycle of an asset to determine when to perform maintenance tasks. Changing a car’s oil every three months or every 3,000 miles is one common example of preventive maintenance.

What is predictive maintenance?

Predictive maintenance uses the actual operating condition of an asset to determine what steps to take and when.

Many of the best maintenance programs use a combination of both strategies. A preventive maintenance schedule, based on manufacturer recommendations, is straightforward and sufficient for some assets. Others can even be run to failure. A predictive maintenance strategy can save both time and money, but it is more complex to implement.

While equipment is operating normally, it can be monitored by condition monitoring devices. They can take measurements at regularly intervals or continuously. These devices, paired with predictive maintenance software, can alert maintenance teams when any asset’s condition changes. Automatically generated work orders enable teams to act quickly, preventing equipment failures.

Asset condition data can be trended and analyzed to help maintenance teams spot patterns and make more informed decisions. Ultimately, the goal of predictive maintenance is to maximize asset availability and minimize the time and cost spent repairing each asset.

How do you decide which assets need predictive maintenance?

Predictive maintenance is not necessarily the most effective strategy for every asset. Some assets can be run to failure with little to no impact on production or the bottom line. Others benefit from simple and straightforward preventive maintenance. But for some assets, predictive maintenance is the best strategy.

There are a few questions to keep in mind when considering which approach to use for each asset:

  • If this asset fails, how is production impacted?
  • How much does it cost to repair this asset?
  • How much does it cost to replace this asset?

Answering these questions for each piece of equipment can help teams start to focus their attention and resources.

How do you start a predictive maintenance program?

There are several key steps required to successfully implement predictive maintenance:

  1. Identify which assets should be targeted for predictive maintenance
  2. Choose the tools and methods you will use to monitor asset condition
  3. Select and train an implementation team to learn and carry out predictive maintenance activities
  4. Perform system integrations to get a complete picture of asset health
  5. Coordinate your overall maintenance strategy, identifying which approach will be used where
  6. Determine how asset health data will be shared among team members, stakeholders, and auditors
How do you start a predictive maintenance program?

Implementing a predictive maintenance program requires taking a long-term view of your organization’s goals and needs.

Predictive maintenance FAQs

  1. How does predictive maintenance work?

Condition monitoring sensors are installed directly on assets and capture performance data. A number of factors can be measured, such as vibration or temperature, depending on the asset. The sensors can detect issues such as pressure leaks, vibration abnormalities, or unusual voltage.

Cloud technology enables condition monitoring sensors to share the data they collect. Paired with the right software, alarms and work orders can be triggered when asset conditions surpass defined thresholds.

Data modeling, based on known machine behavior and failure modes, is used to spot issues before they escalate to failure.

  1. Which industries use predictive maintenance?

Predictive maintenance is a useful strategy for a wide range of industries. It leverages technologies and tools—from sensors to software to statistical analysis—to reduce unplanned downtime and wasted resources.

PdM can be deployed in any organization seeking to extend the lifespan of their assets and optimize their maintenance spending.

eMaint predictive maintenance software serves clients in industries such as:

  • Manufacturing
  • Food & beverage
  • Government
  • Healthcare (including pharmaceuticals, medical devices, and more)
  • Energy (including oil & gas, wind, and more)
  • Education
  • Warehousing & distribution
  • Transportation & fleet
  • Facilities
  1. What are the advantages of predictive maintenance?

PdM is a cost-effective maintenance strategy with numerous benefits. Among them:

  • Avoiding unplanned downtime
  • Improving productivity
  • Extending asset life and maximizing time between purchases
  • Reducing the amount of materials and spare parts needed
  • Creating a safer work environment
  • Benefiting the bottom line

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