NEXTGEN® Technology

Tenova’s NextGen^® is innovative hardware that offers a hybrid extractive/laser multipoint off-gas analysis solution with full spectrum analysis (CO, CO₂, H₂, H2O_vapor & N₂ by difference). NextGen^® utilizes highly reliable extraction to first, continuously sample and filter the off-gas prior to analysis.  Extracting and cleaning the off-gas sample ensures no lost signals, a typical problem with in-situ laser systems.  NextGen^® continuously introduces the filtered gas into the laser and other analytical cells to provide a continuous full spectrum off-gas analysis.

Unlike other laser technology options, full spectrum analysis achieved with NextGen^® provides complete process control functionality with absolutely NO compromises, for:

• Dynamic control of burners, lances and fume system suction
• Comprehensive water detection using both H₂ and H₂O_vapor analysis
• Closing a real-time Mass & Energy Balance, which is required for iEAF^® dynamic control of both chemical and electrical energy inputs to the EAF

The importance of having complete off-gas analysis spectrum cannot be stressed enough. A partial analytical spectrum reduces the functionality of in-situ laser systems.

In-situ systems can only provide a series of intermittent, discontinuous off-gas analysis points resulting in long periods of no analysis reading. By comparison, NextGen^® provides continuous off-gas analysis from ALL sample locations simultaneously. Using a high velocity pump to continuously extract off-gas, the system filters and cleans the off-gas prior to introducing it into the sample station laser cells. Therefore, unlike in-situ technology, there is absolutely no risk of interrupted laser beam transmission when using clean gas.

Using clean, filtered gas means the system operates with high reliability at much lower laser power levels than in-situ lasers. NextGen^® splits a laser beam two ways to provide highly reliable, continuous analysis from two typical off-gas sample locations, which are the 4^th hole for melting and refining process control and optimization, and at the downstream location for safety and to close iEAF^®  Mass and Energy balance. Multipoint analysis capability is also imperative when developing a technology roadmap for further technologies such as Tenova’s dynamic iEAF^® and iBOF^® technology.

BENEFITS OF NEXTGEN^®

• Can be configured to provide the most comprehensive off-gas based Water Detection technology by analyzing of H₂ and H₂O_vapor

• Reliability from start-to-end of heat is exceptional, with no interrupted laser transmission

• Analytical response time from probe tip to analysis is approximately 8 seconds or less

• Can be configured for dynamic control of fume system suction

• Reduces installation & maintenance costs

NEXTGEN^® - THE COMPLETE SOLUTION FOR AN INDUSTRY 4.0 PLANT

Tenova’s aim for an Industry 4.0 digitalized environment is a smart factory that utilizes a highly digitalized link between production equipment, sensors, Level 1 and 2 control networks, process control models and cloud computing both within specific process steps and across the entire production facility.

The net result allows for more effective control & optimization of each process step in a way that is dynamically aligned with changing day-to-day factory constraints thereby minimizing total production costs & inefficiencies.

Tenova’s objective for implementing an Industry 4.0 solution is based on:

• Replacing assumptions & related inaccuracies with real-time process measurements in critical areas obtained from robust, reliable sensors;

• Replacing statistical process models which are prone to excessive drift with a new generation of more fundamental thermodynamic & kinetic based process control models that incorporate real-time mass & energy balances;

• Creating a digitalized interface that links process equipment, sensors, Level 1 & 2 networks, and process control models;

• Using cloud computing services to store and analyze large amounts of process data from multiple EAF’s & plants where appropriate;

• Employing a team of highly trained data scientists together with machine learning techniques to develop improved & optimized 2^nd & 3^rd generation process control models;

• Continuously monitoring model performance; and,

• Providing automatic dynamic retuning of the models when necessary to ensure sustained maximum performance over the long-term.