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The role of edge computing in innovation: smart products and smart operations

EIC_IoT_Blog

Olivier_Frank.jpg

Olivier Frank

WW Director Sales & Business development, IoT & Converged Edge Systems

 

 

As the manager of a business that focuses on edge computing, I get to travel the world and see how manufacturers are solving real-world problems on the factory floor. These companies are taking the latest in IoT and other edge technologies to not only make their operations more efficient, but also to fundamentally change the way they do business. 

Oftentimes, however, there is a question of what sorts of digital transformation projects are appropriate to start with. We frequently advise customers to look at two areas of potential innovation: 

  • Smart products
  • Smart operations 

The first category, smart products, requires customers to design products or services with more intelligence. New types of industrial applications and IoT sensors, not to mention powerful edge compute resources, makes such innovation possible. 

 

Bike_AR_demo_sm.jpgFor instance, if you are part of the team designing and building a next-generation bicycle, all kinds of data can be captured by sensors placed on a prototype, from brake pressure to velocity. Live performance data can be processed on the edge and fed into a digital twin, which can inform the team on how to improve features for the next iteration of the bicycle. 

The smart products model can be extended to all kinds of discrete manufacturing scenarios, with the constant feedback loops to engineering, production, and marketing teams leading to more innovative products. Critically, this approach can also accelerate time-to-value, resulting in faster returns on investments and better business outcomes. 

Smart operations, also known as smart manufacturing, involves making existing assets (including legacy equipment) more productive. It’s thinking about quality, reduced downtime, and improved worker safety, among other things. 

Connecting and sensoring these assets is one part of the challenge. The other relates to taking the data from edge systems and deriving useful insights from it. Examples include prescriptive maintenance to identify problems before they shut down the production line, and automated quality control based on video sensors and machine learning. 

A platform for innovation on the edge 

To see how we are approaching the development of smart products and smart operations with customers, a visit to the Electric Mobility Lab (eLAB) at RWTH Aachen University in Germany is in order. There, HPE takes part in a collaboration platform where manufacturers, HPE, and ecosystem partners such as PTC, National Instruments and OSIsoft can work on real-world needs or identify new business opportunities. This is a place to bring together thought leadership and cross-functional knowledge, which allows customers to work on more sophisticated or innovative ideas that would otherwise be impossible to develop on their own. 

The eLAB includes an automotive battery production line, where we can work with customers and ecosystem partners to transform the processes governing the manufacture of this critical vehicle component. The production line includes 12 industrial machines for electrode production, cell assembly, and testing. 

Getting the machines connected was the first step. Doing so revealed the data that is generated by those machines, which opens up the possibility of doing many other things, from analytics to quality control. As this proprietary information is very sensitive, the customer did not want to upload it to the cloud. Instead, we used Edgeline converged systems to enable analytics and other software applications right next to the production line. Working with ecosystem partners and the customer, we reduced quality defects by 30% within 3 months -- a very significant outcome.

Planning a proof of concept 

When it comes to getting started, we advise customers to scope a proof of concept in a sizeable way, which means simple enough as opposed to something that’s overly complex. In the industrial world, it's really about targeting specific assets which they know very well because of their deep operational experience. 

Workshops can help zero in on pain points and define the journey that can quickly get results.

A well-executed proof of concept is a crucial step: Connect a few assets, make the data visible, and then show the quality manager or operations manager the value of the data and the insights that are revealed. 

It’s also possible to get a better understanding of smart products and smart operations by scheduling a visit to HPE IoT Labs in Houston and Singapore (and soon in Geneva and Bangalore). The labs are collaborative environments where HPE, customers, and partners develop advanced IoT technologies intended for the industrial edge. The labs also feature edge experience zones that showcase applications of IoT technologies in manufacturing, smart cities, and other industrial use cases. You can RSVP here to arrange for a visit.

 

Empowering the Digital Enterprise to be more efficient and innovative through data-driven insights from the Internet of Things (IoT)
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