Manufacturing Magazine August 2018 | Page 8

The seven key challenges of data gathering
LEADERSHIP SHOWCASE
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The ability to derive actionable value from IoT-influenced machinery is one of the key challenges for the future of the manufacturing industry . Analysing this data in a meaningful way to drive a desired outcome , such as cost saving or lowering the carbon footprint , is a complex process . This is particularly evident when we consider that the modern factory floor will be deploying numerous different types of equipment from various different manufacturers , with each one perhaps employing alternative data models .

It becomes even more complex again if the data comes from larger corporations whose machinery is distributed across different geographies . Delivering successful solutions that overcome these common obstacles and issues is something that Cisco ’ s Director of IoT strategy , Theresa Bui , is well versed in .

“Catching issues on the edge can help combat unplanned downtime by streamlining equipment maintenance ”

– Theresa Bui , Director of IoT Strategy , Cisco

The seven key challenges of data gathering

In Bui ’ s opinion , the Internet of Things is a ‘ godsend ’, largely because it allows organisations to access data whether it ’ s in the cloud or an app , for example , and connect the necessary devices to pull down whatever your business requires . However , data gathering can produce a number of complexities that need to be addressed at various stages and levels .
Given her 15 years of experience in application security , enterprise SaaS and network communications , there are few people better placed that Bui to identify the key challenges faced by businesses in the manufacturing sector when it comes to data and IoT . Indeed , she has managed to whittle these problems down to seven fundamental
AUGUST 2018