Predictive Maintenance (PdM)

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Maintaining and repairing industrial or commercial equipment can be costly and time-consuming. Predictive maintenance is a preventive maintenance strategy that employs techniques like data analysis and machine learning to identify issues before they cause actual problems. Predictive maintenance can help you reduce downtime, save money on repairs, and extend the life of your equipment.

What is Predictive Maintenance?

Predictive maintenance is an industrial maintenance strategy that uses data analytics and machine learning to forecast when equipment requires servicing or replacement. PdM can improve operational efficiency and reduce downtime by allowing businesses to schedule regular maintenance appointments before faults occur. While predictive maintenance is not a new concept, the recent advancements in big data and artificial intelligence have made it more accessible and cost-effective for businesses of all sizes. By using predictive maintenance, you can avoid unplanned reactive maintenance and minimize costs connected with preventive maintenance.

Predictive Maintenance vs. Preventive Maintenance

The purpose of preventive maintenance is to prevent equipment failures by doing whatever it takes, no matter how expensive or time-consuming it might be. The goal of PdM is to take minimal action while still prolonging the life of the equipment. Preventive maintenance also requires frequent inspections, as these determine when to perform maintenance. This is another difference between predictive and preventive maintenance. Through the use of sensors and other connected devices, predictive maintenance allows your team to monitor equipment conditions remotely.

How Does PdM Work?

You can use data from all parts of your operation to predict problems before they occur using predictive maintenance. The following three areas of your organization contribute to PdM:

  1. Tracking the condition and performance of assets in real-time
  2. Analyzing data from work orders
  3. Utilizing MRO (maintenance, repair, and operations) inventory benchmarks

As part of predictive maintenance, technology and software play a crucial role. Different assets and systems can be connected via the Internet of Things (IoT), artificial intelligence, and integrated systems, which allow them to share, analyze, and act on data shared between them.

All of the tools in your integrated system, from PdM sensors to asset management software, capture information. Then, they analyze the data and identify any areas that need attention. Vibration analysis, oil analysis, thermal imaging, and equipment observation are all examples of preventing unnecessary maintenance by using predictive maintenance sensors. However, if you’re not sure where to begin, you can consult with both equipment manufacturers and condition monitoring experts when selecting the correct technique for performing condition monitoring.

The Benefits of Predictive Maintenance

The benefits of basing your business and maintenance decisions on real data are enormous. Therefore, putting PdM to work as a proactive maintenance strategy is pertinent given the impact of data on business performance. Other types of maintenance, including preventive, corrective, planned, and condition-based, will not become obsolete anytime soon. But, organizations should get ahead of the curve by adopting innovative ideas and technology.

The following are the top 5 benefits of predictive maintenance:

  1. Maximize asset life expectancy
  2. Increased asset uptime
  3. Reduced equipment failure
  4. Improved asset reliability
  5. Minimize maintenance expenses

How to Implement Predictive Maintenance in Your Organization

Predictive maintenance is a newer maintenance strategy. So, it is understandable that maintenance managers may have difficulty understanding how to incorporate a predictive maintenance strategy into their existing maintenance workflow. These are the steps to get you on your way to optimizing your maintenance plan.

1. Choose Assets to Monitor

Despite its numerous benefits, predictive maintenance does not apply to all equipment in operation due to the large amount of data generated by daily equipment monitoring. Maintenance managers should select only a few pieces of equipment to monitor to conserve organizational resources. To choose the right equipment, consider the following:

  • Do they have high maintenance costs?
  • Are they susceptible to equipment failure?
  • Is it possible to monitor conditions leading to or causing failures?

2. Choose Your Prediction Method

In most cases, predictive maintenance requires a predictive algorithm. This means that a maintenance manager must create their own, hire a third party, or purchase predictive analytics software. As a result, predictive maintenance often has a high barrier to entry. However, maintenance managers can also conduct a predictive analysis of their own. The goal of predictive analysis is to evaluate several variables to predict when equipment is likely to fail. This will require a starting idea of the conditions to monitor and any preferences based on your organization’s specific use of the equipment.

3. Integrate Your Sensors with Software

Redlist’s CMMS (Computerized Maintenance Management System) software integrates with many different kinds of sensors. This is an essential step to remove the endless admin hours required to process sensor data and determine actions. An integrated system allows you to configure automatic work order creation from sensor alerts.

4. Install Sensors on Equipment

Maintenance managers can install sensors to the equipment once they have connected the sensors to their database. As soon as maintenance managers verify that sensors are monitoring equipment conditions correctly and sending real-time data to the database, they should set up alerts to notify them when certain conditions are reached.

5. Monitor, Schedule Maintenance, & Revise

No maintenance strategy is complete without monitoring and making adjustments for continuous improvement. If you opt for software that allows sensor alerts to automatically create work orders, then you have more time to monitor and analyze your data.

If you’d like to see how Redlist can support your predictive maintenance goals, schedule a demo with one of our team members.

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