Predictive Analytics In Manufacturing: Why & How For Non-Data Scientists

by Vin Vashishta, Data Science Consultant

A really interesting post on what predictive analytics is and the zero downtime. I recommend it to anyone who is trying to convince a potential client to integrate Internet of Things / Big Data based solutions.Internet of Things

“The problem with older models is they had significant blind spots. The available data didn’t provide a complete picture of the machine in action and that led to frequent failures in the model. The IIoT is aimed at providing a more complete picture of the machine in a variety of environments to eliminate these blind spots. Predictive models rely heavily on compete, high quality data for accuracy. Older models would predict a machine failure based on an average and could me months off. Newer models based on IIoT data can be accurate to the week or even day.”

Is IoT changing the manufacturing?

by Francisco Maroto CEO at OIES Consulting, IOT Advisor for IOTS

Here you will find three interesting case studies about the real usage of industrial IoT.

“While the IoT will allow real-time sharing of data by all who need it, it remains to be seen whether management will move to break down departmental silos to share data on a real-time basis and will choose to give rank-and-file assembly line personnel access to relevant information that would help them work more efficiently.”

IoT Could Be Hobbled By Lack of Consumer Awareness

by Jacob Meister, Real Time Digital Reporter, Design Group

In case you are interested in B2C IoT products, this survey is bringing up some numbers on what people know about IoT.

“Eighty-five percent of those surveyed said they were worried about the possible security/privacy issues that IoT could create. A large number (70 percent) said they felt IoT would hurt daily interactions.”