HPE addresses OT with solutions that help monetize edge data

I recently attended the opening event of HPE’s IoT Innovation Lab in Geneva, Switzerland (which is 1 of 4 global labs), where I had the opportunity to talk to HPE executives and take a closer look at some interesting OT examples showcased in the lab. But, before sharing them with you in this blog post, I would like to present some of my general insights from the event:

Basically, HPE’s view about the enterprise of the future is that it will be edge-centric, cloud-enabled and data-driven. I couldn't agree more with this perspective, given that the amount of data generated at the edge – in the OT world these edge devices are machines, tools, sensors, devices, assets, assembly lines, plants, etc. – will increase exponentially in future. Being able to manage this data, i.e. to capture and analyze it in a way that generates meaningful and actionable insights and eventually helps monetize this data, will be absolutely key for companies to gain a competitive advantage or increase efficiency in the long term.

I liked the way HPE phrased this at the opening event, namely that IoT solutions should help to address the 3 Cs, “connection, compute and control”. HPE’s business activity is clearly to provide infrastructure solutions that allow to securely collect data from the edge and provide high-performance computing power, to analyze this data either at the edge or by connecting the edge to the cloud.

This brings me to two examples that were presented in HPE’s lab and that I consider as highly relevant for manufacturers’ shop floor operations; they demonstrate pretty well how technologies such as IoT, analytics and AI can help manufacturers monetize their edge data while at the same time increasing efficiency on the shop floor:

  • IT/OT convergence: HPE offers its “Edgeline” integrated solutions that allow to converge OT (e.g. CAN bus and OT control systems) with enterprise-grade IT infrastructure on the shop floor. The example showcased in the lab is that of a car manufacturer who has connected a car door and has its behavior (including the window’s) monitored by multiple sensors. Capturing this data using multiple sensors mounted at the door and analyzing it enables more efficient and automated testing of this door and its components. The benefit of implementing this solution for the car producer is a significant increase in the number of cars leaving the assembly line each year, by speeding up factory in-line testing and development procedures. 

  • Digital quality control: Another interesting showcase project at HPE’s lab is the “Edgeline” quality control system implemented at a high-tech assembly line leveraging video sensing, analytics and machine learning to compare images from an assembled component “as is” with the required “to-be” BOM of that component. With this showcase, HPE demonstrates a solution that enables automated and precise defect detection of finished products, which is particularly relevant for high-tech manufacturing. The benefit of this solution, which is already used by Foxconn in the Czech Republic, is that it accelerates the time to train ML algorithms by employing image-analytics methods and by running the analysis right at the edge, which as a result accelerates the quality insurance process for assembled products.

Given HPE’s strong footprint in the manufacturing industry in Europe and its comprehensive portfolio of IT infrastructure solutions, I see HPE very well-positioned to help manufacturers leverage their edge data so as to increase efficiency on the shop floor. However, providers that have a strong position in the OT world in particular (e.g. ABB or Schneider Electric) and who HPE already partners with, will continue to play a major role for HPE to get a foot in the door and to further strengthen its own positioning in the OT world.

And, even though execs from the OT and the IT world have been living in separate worlds for a long time, I have observed that the OT world is increasingly looking at how new technologies such as IoT, cloud and data analytics can help industrial companies gain insights from process and/or machine data from the edge, in order to increase the efficiency of production processes. (To read on, please see our Expert View on this topic). In heavy-asset industries in particular (though not limited to these), which have made long-term investments in production assets, the prospect of increasing the utilization of assets, reducing unplanned downtimes or optimizing energy management is a major driver for modernization and the related investments.

Overall, it can be said that having solutions in place that help manufacturers digitally transform their factory and plant operations, for example by helping the OT domain to monetize the generated edge data, is definitely an opportunity for providers from the IT domain. The investment by HPE in another IoT lab showcasing exactly that can thus be seen as a step in the right direction.