AI Solutions in Manufacturing – The Real Benefits of Predictive Maintenance

AI or artificial intelligence is all about making machines smarter. Machines have already created a revolution as they reduce human effort. And when you impart intelligence to them it enhances the sensibility of their functions. This is particularly true with the manufacturing sector. The use of AI solutions in manufacturing sector offers plenty of benefits. The potential of predictive maintenance is one of the main perks. 

What is Predictive Maintenance in Manufacturing? 

Depending on the size of the machinery, the applications and the hours of usage the maintenance schedules vary. Regular maintenance is simply to take a look into the internals of the machine and make sure that all the components are functioning as they should. But regular wear and tear or even unprecedented component failures sometimes cause breakdowns to happen despite regular maintenance. This is where predictive maintenance comes into the picture. It is about scheduling maintenance based on the life and performance of the components or the machine on the whole instead of working based on a strict timeline-based approach.

The concept of predictive maintenance isn’t new but the use of an AI platform to enhance it is definitely new and it is a concept that is here to stay. Downtime turns out to be quite expensive and even the most successful businesses might suffer major losses due to them. So, artificial intelligence in predictive maintenance proves to be a beneficial concept.

Combining the Power of Machine Learning to Make Predictive Maintenance Even Better 

The use of artificial intelligence in predictive maintenance involves integration of concepts like Big Data and IoT (internet of things). Big Data is applicable because the amount of data being analyzed and monitored increases with this application. Internet of things is where sensors are integrated in different devices and a suitable algorithm is tuned to allow devices to communicate with each other. Based on predefined rules and the data being communicated, some decisions are made. 

Planning a maintenance or repair before the component breaks down is possible by closely looking for anomalies. This involves training the machine learning model with an exhaustive dataset of the ideal values. The stability of this model is adjusted so as to avoid overfitting and underfitting. In the end you are left with a trained machine learning model that captures deviations from the standard values and automatically triggers the essential response. Alerts are immediately sent regarding a possible breakdown or component failure that is likely and sometimes the model can be trained to automatically schedule machinery inspection as well. 

This is beneficial because –

  • Component failure sometimes leads to bigger dangers and so predictive maintenance enhances safety of operation. 
  • Unexpected downtime means delays in manufacturing. This can sometimes reduce the efficiency of the workflow. AI-based predictive maintenance helps in avoiding the unwanted expenses incurred due to these factors. 

With AI solutions seamlessly integrated into your predictive maintenance strategy, you allow access to historic data and real time data to make a more practical decision and to take timely actions. This is how AI drastically transforms certain sections in the manufacturing sector.

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