Why is Predictive Maintenance an Important Part of AI-based Hardware Solutions?

In the initial phases of the Industrial Revolution, machines were not too intricate which resulted in fewer breakdowns. As we progressed into the 2nd and 3rd wave of the Industrial Revolution, with swift technologies like the assembly line and other forms rapid automation through Programmable Logic Controllers (PLCs), Human Machine Interfaces (HMIs), and SCADA respectively, the concept of maintenance has grown leaps and bounds.

Nowadays, there is less manual labour and more automation training through the implementation of advanced machinery. To remain competitive, industries have started analysing and closely studying various performance metrics and results, such as production output, overall equipment effectiveness, personnel productivity etc.  in the modern age of today, maintenance, which was once seen as an activity to be carried out only when there was a breakdown, has become exponentially more important. The concept of periodically scheduled maintenance has grown in popularity. This periodic inspection of the machinery helps to identify issues early on itself so that breakdowns could be minimised, or in some cases negated completely and production stoppages can be reduced to a notable extent.

Now as the 4th wave of the Industrial Revolution also known as Industrial Internet of Things (IIoT) or Industry 4.0 has been incepted, there is a larger emphasis on equipment productivity, operational cost, worker productivity etc. Industrial IoT is related to all about linking low-cost sensors to collate machine data and using superior analytics to extract meaningful insights. It is approximated that Industrial IoT will allow manufacturers to enhance their productivity by 30% The maintenance strategy that implements advanced analytics to accurately predict machine defaults is known as Predictive Maintenance.

Using predictive maintenance solutions, businesses will essentially know when to schedule the required replacement of specific parts, be alerted by unproductivity caused due to faulty parts or installations, and lastly,  if any parts are being cluttered and need to be cleaned. An example of the implementation of predictive maintenance can be shown in the prevention of oil spills, by predicting tank overflows in advance. This just shows the importance of predictive maintenance as a part of AI-based hardware solutions and field services in the near future, especially in the case of smart city challenges. 

#SchneiderElectric is one of the prominent global brands exploring the domain of predictive maintenance, to ensure your #LifeIsOn.