How Data Science & Metallurgy meet on the IIoT

By September 2, 2015 June 20th, 2019 No Comments


A major innovation happening in industrial environments is the application of new technology to old process in order to gain performance and quality improvements, while reducing cost of operations and improving safety. Eigen Innovations has been on the forefront of developing leading edge technologies for the Industrial Internet of Things (IIoT) by leveraging big data analytics and deep learning algorithms to achieve these benefits for companies looking to gain extra competitive advantage.

The process of lead smelting is something that has existed for centuries, ultimately tracing its roots back to ancient times. With each generation, new technology has given greater insight and refinement to what is still considered a “dark art” process. It is with this context that a unique opportunity presented itself to yet again evolve our understanding of this process using the latest combination of technologies provided by Eigen Innovations in partnership with Glencore Xtrata at their lead smelting manufacturing plant in Belledune, NB.


Problem Overview

A lead blast furnace is a highly dynamic and volatile environment, with temperatures ranging well in to 1000 degrees Celsius. Yet, this environment requires a high degree of control and optimization to maintain optimal blast furnace temperature, even distribution of raw material, and real-time corrective measures to produce the desired product output. Operators in this environment have to rely on the combination of expert knowledge accumulated over generations combined with observational data, which can be limited due to the harshness of this environment.

Sub-optimal performance in a blast furnace can contribute to:

  • uneven distribution of the ‘burden layer’ (the top layer of raw material being reduced)
  • hot-spots and flare-ups
  • channelling of gas through the burden layer
  • build-up of accretion on the furnace shaft

All of these results can reduce the campaign life of a smelting run and the overall quality of the end product.

FLIR thermal image from the inside of a blast furnace

FLIR thermal image from the inside of a blast furnace


Solution Overview

Eigen Innovation has developed a connected data analytics platform that is optimized for industrial applications.  The solution uses Eigen’s Intellexon™ software installed and configured on a small industrial gateway device.  The software is programmed to process large amounts of data in real-time in order to provide immediate feedback to operators and other machines in order to optimize a process flow.  Connecting one of FLIR’s fix mounted automation cameras to the platform captures up to 60 frames of high resolution digital thermal data per second enabling a rich real-time view of exactly what is happening within this industrial process.

This solution has enabled Glencore to gain new understandings of the movement of the burden layer within the blast furnace while it’s operating, enabling them to develop proactive strategies to managing the operation of the process in real-time and integrate process control using the Eigen connected platform.  Glencore is now not only able to see what is happening inside the blast furnace and also able to understand the data in real-time using Eigen’s connected data analytics platform.

This past week, Eigen Innovations was honoured to participate at COM 2015 (http://web.cim.org/com2015/) held in Toronto, Ontario, and co-present the findings of this innovative breakthrough on-stage with Glencore Xstrata.


About Eigen Innovations

Bringing Vision to the IIoT: Eigen is certified to work with a range of FLIR thermal cameras that connect to our Intellexon™ platform for advanced analytics and deep learning algorithms for plant-wide optimizations. Contact Greg Picot (greg.picot@ or Justin McKillop (justin.mckillop@ for more information.

Contact Scott Everett, CTO (scott.everett@ for more information about the findings of Eigen’s development of lead smelting process optimization.

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