Refractory Industries leveraging data to Solve its biggest challenges


Refractory Industries leveraging data to Solve its biggest challenges
Refractory Industries leveraging data to Solve its biggest challenges

For millennia, the refractory industry has existed. Throughout this time, the industry has ensured global safety in high-energy intensive industries, primarily steel production. Almost no process can function in severe temperatures without the use of refractories. The majority of the industry still follows old techniques, and the fact that it deals with raw materials, takes place in harsh environments, and lacks digital connections means it hasn’t been at the forefront of digitalization.

The refractories market, on the other hand, is growing, with a CAGR of 5% projected between 2016 and 2025. As the demand for goods and services grows, there is increasing need to improve efficiencies and embrace technology to do so.

Traditional industry procedures, such as demand management, precisely evaluating manufacturing processes, stock monitoring, and supply chain management, face a number of obstacles in the era of globalization. Because the mining and heavy industries are part of the Fourth Industrial Revolution, the refractory industry now has the chance to use data and technology to address problems and spur innovation, but how can it do so?


Analysis of the Product in the Field

The high-risk component of the heat processes in which refractories function necessitates continual monitoring of product wear. This is necessary in order to ensure the product’s safety and quality, as well as to improve overall process efficiency. Prematurely modifying the product results in higher expenses and unnecessary reactor downtime. However, delaying the replacement of a product for an extended period of time puts the workers’ safety at danger.

In-situ wear analysis is useful in this situation:

Computer vision technology, which can “see” within the reactor by optical or laser vision, can collect data to detect wear and mechanical stress in the refractory layer. This non-destructive method produces relatively precise results and allows organisations to track exactly where repairs in the reactor need to be made before the next cycle or whether the lining has to be completely rebuilt.

With Machine Learning, we can gain a better understanding of the world.

Machine learning (ML) models can be fed photos and other data acquired via in-situ analysis. The models will provide insights over time that will allow companies to make precise estimations on items like the product’s running time as well as which parameters and circumstances (often including temperature) inside the reactor are best for receiving the desired product, be it steel, glass, or cement, while retaining the refractory layer to a minimal level.

RHI Magnesita is a leader in the use of artificial intelligence to learn from industrial data. Its Automated Process Optimization (APO) system collects all available information regarding a specific manufacturing process, including temperature variations, chemical processes, optical measurements, order cycles, and planned maintenance and repair.

The AI-powered APO may provide estimations about refractory material maintenance and replacement based on available information, as well as evidence based values and past measurement results. For instance, a customer who uses APO can schedule maintenance work to occur among production peaks, saving time and resources.


Demand Management via Cloud-based Integration

Network demand planning is one of the refractory industry’s most difficult tasks. Human’s still undertake most of the surveillance in warehouses and along the supply chain, and data is kept in on premise platforms like SAP, which creates silos. The same is true for data from other sections of the value chain, such as mining, raw material production, and replenishment at the customer’s location, as well as product recycling and disposal.


All of this data, although, may produce newly found efficiency for the industry when combined with an end-to-end cloud architecture. Companies can anticipate where demand would therefore emerge by combining data from local warehouse surveillance with movement data, production cycle information, and location tracking data. This allows them to direct their product to the right field at the correct time. Companies can digitize their inventory data and trace it as it moves through the supply chain by adding a single identifier to each unit or pallet using tracking technologies (such as QR codes).

Integrating information from all of the numerous production sites throughout the world is indeed a major obstacle. A centralized, cloud-based solution is required to establish data lakes where almost all necessary data may be securely stored and accessed remotely and securely by any authorized person who appears to require it.


Although the refractory industry is not quite at the top of the list of Industry 4.0, it can close information gaps in the supply chain, solve legacy issues, modernize traditional processes, completely eradicate silos, and build smart, globalized networks that deliver critical insight by producing new data with in-situ process analytics and utilizing existing data in cloud-based networks. Integrating these advancements into the fold and discovering new efficiency is easier than you think, especially with the support of an experienced professional partner like intive.