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Guides Use Cases DeMystifying Cognitive Approaches to Predictive Maintenance

DeMystifying Cognitive Approaches to Predictive Maintenance

Published on 07/06/2017 | Use Cases

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Anita Raj

Head of Growth Hacking . DataRPM

IoT GUIDE

Every 30 minutes in flight, a Boeing 737 engine generates 10 terabytes of data… Almost 640 terabytes of data are created by a four-engine jumbo jet in one Atlantic crossing. 

So much data explosion but such scant value being obtained.

Your Data is as good as the value it gives. True that! Do you know what else is ironically true? A minuscule percentage of Manufacturers are really taking advantage of the wealth of data they behold. As writer Andrew Lang quoted, "He uses statistics as a drunken man uses lampposts—€”for support rather than illumination." Even today, the saga continues as Organizations still use data to support rather than drive decisions.

By 2020, the size of the world’s digital universe will be almost 44 trillion gigabytes. Currently, 7% of the world’s devices are connected which represents only 2% of the world’s total data universe!!

Everybody aims at being data-driven but how many Manufacturers are equipped with the machine intelligence to convert this data into insights? On one hand, CIOs are tired of depending on technology to collect valuable data from devices, and on the other, mountains of data are being created every millisecond, waiting to be explored, analyzed and hypothesized. The imbalance needs to be nipped, and nipped now!

The world today needs a drastic shift from just being just data -driven to insight-driven.

Why?

  1. Value Lead Data Investments: Shallow technology based big data investments which lack meaningful insights are futile.  Superficial data collection with no significant value creation through real-time data insights are meaningless.  Manufacturers need to go the extra mile to cover the gap from data gathering to uncovering deeper data analysis based insights using powerful technologies like machine learning and data science.
  2. Data Complexities Concocted:   Experts predict some companies could hold almost $8 trillion worth data. There exists a clear imbalance between the demand vs. supply, with complex data exploding at one end and a limited number of Data Scientists to decode this on the other. With human limitations of scale, it is unimaginable to wade through this noisy and messy data and create actionable insights without a robust Machine-First approach.
  3. ROI- Game Changer: Today’s competitive market requires insights based decisions at the right time and speed. Agile businesses do not have the luxury of time to wait for months to see results. The data silos need to be cracked, translated into tangible results and quickly operationalized into tactical activities to boost the ROI eventually.

So, let’s Imagine...

Imagine increasing production output tenfold  by leveraging the connected factory

Imagine slashing down global power consumption by using predictive maintenance

Imagine saving billions of dollars in wages with asset intelligence

It is time to make this a reality by letting data drive business critical decisions to start reaping benefits.

“Surge in production by 50%!” did you say? Well, lets see how this happens.

Join me and my colleague, Aditya in our upcoming webinar to learn how cognitive approaches to predictive maintenance is a key driver for strategic decision making.

 

This article was originally posted on LinkedIn.

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