Predictive Maintenance: A Data Science Solution

Predictive Maintenance: A Data Science Solution

Imagine you are lined up for an interview from one of your listed dream companies and you are up late. Adding on to that, there is a geyser issue in the bathroom, last minute ironing is still pending and the coffee machine is upset too! What a start of the day? Frustrating – Isn’t it?  Such technology breakdown situations do randomly happen to some or most of us once in a week, a month or to be on the luckier side in a year. This turns out that we are truly dependent on the machines or gadgets that we use in our daily lives to be productive and stress-free. Therefore, the quality of a machine is not only based on how useful and efficient it is, but also on how reliable it is. And together with reliability comes maintenance. This further dives into an important question – Is there a way to predict the risk of breakdown of equipment? 

The answer to the question is Predictive Maintenance. Predictive Maintenance, is a solution involving Data, Predictive Analytics and Internet of Things (IoT) that helps to monitor machines, predict quality issues and failures even before they occur. This is certainly a win-win strategy for both- consumer electronics companies and users. IoT allows for different assets and systems to connect, work together, and share, analyze and action data. With the IoT driven data from sensors to capture information, predictive maintenance models can make sense and identify any areas that need attention to some parts or a replacement to machines.

For OEMs and consumer goods manufacturer, IoT driven predictive analytics can help them to:

  • Configure a set of ‘rules’  that will identify maintenance issues and send alerts when equipment will need to be repaired or replaced
  • Improve quality standards and deliver better service

For Users, IoT driven predictive analytics can help them to:

  • Get alerts through a mobile app or web-based dashboards about the replacement of parts or equipment
  • Understand and be well informed about their purchase decision and time involved to repair any part of the equipment

To conclude, Maintenance is a serious concern in terms of costs, revenues for companies and enabling consumer satisfaction. Hence, With Predictive Maintenance Solutions, early identification of potential concerns can help organisations increase productivity, improve services, maximize ROI, and create new business models that ensure a bright future.

By: Anupama Rathore

 

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