Changing Face of Predictive Maintenance Tools with Artificial Intelligence !

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Every household has a scheduled maintenance drill for their appliances, be it the washing machine or the dishwasher. Similarly, industries too have their own strategies to check their machinery maintenance. Yet, it happens that even with due care and diligence, machines fail to work unexpectedly bringing down production for hours or days, causing losses worth millions of dollars.

Predictive Maintenance Tools
Predictive Maintenance Tools

AI is Enhancing Predictive Maintenance Tools

Such disasters would be a matter of past as Artificial Intelligence is being used for what it is called predictive maintenance. As the phrase suggests, several tools are now available that have the ability to predict if and when the machines would experience failure. The result is that the problem can be fixed before it happens, thus saving time and money.

AI and Predictive Maintenance Tools

Predictive Maintenance tools with ai collect and combine data from different sources which is then applied to machine learning processes. This procedure anticipates any damage or maintenance issues with a machine much earlier than it happens. As it is said, prevention is better than cure, such ability of AI to predict machine failure issues can not only enhance productivity but can also prolong the life of machines.

Today, most companies are utilizing predictive maintenance using it or Internet of Things but AI can take it further. Rather than just monitoring data and their output, it is now possible to leap forward. These advanced algorithms can be used to take swift action in real time.

With such enhanced, modern and best predictive maintenance tools, companies are able to put a foolproof mechanism in place to not just secure their machines but also to ensure the smooth running of their factories, avoiding delay and obstruction. The system is also helping them to optimize their maintenance mechanism.

Dataiku, A data science company has even published a paper on how businesses can use predictive maintenance tools for both long and short-term.

The paper puts forward several steps that companies can use to efficiently integrate AI-enhanced predictive maintenance equipment in their system.

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 Steps for AI-enhanced predictive maintenance system

The first step is, of course, to understand how and where it can be utilized. Data storage with enhanced data processing systems and cheap sensors has made it possible for all types of organizations to access the technology. The wide applications of IoT also are crucial for predictive maintenance.  The good news is that there is also the availability of many different data sources that can be used to collect data for the process.

In addition to collecting the data, it is also necessary to explore and understand it. The data that has been collected is now in parts so what is needed is to enrich it by combining it with the required features so that it is a single and complete unit now.

It is important to know that it is the combination of different types of data that works in making predictive maintenance an accurate system. The system also allows visualization so the output of the tools is visible to all the staff involved in maintenance so that they can take the desired action as early as possible. As maintenance staff can now get visual dashboards in real time, they can work on it without delay. Also, there are systems where feedback can be incorporated as and then into the system which means there may be no need for any human interference at all.

The exciting part is that AI is bringing in new and advanced technology like voice assistants to the fore on a daily basis. This means, there are a number of predictive maintenance tools today which makes the entire process easy and accessible for different businesses.

Conclusion

The primary advantage of predictive maintenance techniques is that it helps business save costs and that too in a major way. It is a boon but in due course, these tools will help companies bring in advanced maintenance strategies which in turn have the capacity to even get extra revenue for businesses.  Another trend to look forward is that in artificial intelligence future, there will be no need for human assistance at all for machine maintenance procedures.

Thus, it isn’t just about maintenance, with businesses making use of applications of artificial intelligence such as predictive maintenance machine learning today, they can be market leaders and show the path for others in future, for sure.

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