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Predictive Maintenance

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What is Predictive Maintenance?

Predictive Maintenance is a proactive maintenance technique that uses performance tracking tools to predict possible defects and fix them before they actually occur. This data-driven method is aimed at reducing costs related to repair and decreasing downtime that result from faulty equipment. 

Rather than focusing on daily routine maintenance, or fixing an error as it occurs (Corrective Maintenance), Predictive Maintenance tools utilizes condition-monitoring equipment to analyze the factory’s machines and parts in real-time.  

Types of Predictive Maintenance:

There are numerous Predictive Maintenance softwares and technologies, such as vibration analysis, infrared, oil analysis, and thermal imaging. These are the types of condition-monitoring tools that enable automated data collections and actionable insights. 

What are the benefits of Predictive Maintenance?

Predictive Maintenance, unlike Preventive Maintenance is aimed at reducing downtime of maintenance and decreasing costs relating to repair. Once a business has effectively created a maintenance strategy by following the implementation steps, they’re likely to save costs on the following:

When Predictive Maintenance is working effectively as a maintenance strategy, maintenance is only performed on machines when it is required. That is, just before failure is likely to occur. This brings about several benefits for manufacturing companies, such as: 

  • Reducing downtime related to repairs
  • Decreasing the production hours lost to maintenance 
  • Saving costs related to new equipment and resources
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How to Implement Predictive Maintenance:

In order for Predictive Maintenance to remain sustainable for years, it’s crucial to create this system accurately and effectively. 

Here are the initial steps a business takes once implementing a Predictive Maintenance Workflow. 

  1. Pinpoint essential assets – Begin by evaluating your factory settings, and identifying which equipment, machines, and systems need to be included in the maintenance. Typically, equipment or machines with an extremely high cost repair are selected.
  2. Create your database – Beyond selecting assets for the Predictive Maintenance program, businesses must also review their data and evaluate whether or not it can offer actionable insights into machine behavior. 
  3. Initiate failure modes – In order to establish proper failure modes, businesses need to perform a retroactive analysis of previously identified failures in the factory. And by establishing these failure modes, Predictive Maintenance is equipped with knowledge already obtained. 
  4. Predict failures – Along with establishing proper failure modes, businesses now must create and design the right modeling strategy that will shape the new foundation for failure predictions.
  5. Test pilot – In this final step of implementing Predictive Maintenance, businesses must test the technology on several parts of equipment. Once testing is complete, and the technology seems to be working well, businesses can then begin working with Predictive Maintenance software. And after several weeks, if the implementation of Predictive Maintenance software was completely correctly, the manufacturing process will be significantly improved. 

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