At Deep.Meta we hold a contrarian view.
This is why we are integrating machine learning software into the metals production industry and are beginning with iron-based alloys, steels.
Today, the steel industry alone is a $ 1 trillion sector and is the most used engineering metal in the world, it is deeply integrated into our societies forming the basic structure of our buildings, transport system, domestic appliances and factories. Put Frankly, steel is the thing that makes things. For a product which is in every part of society globally and is also the most recycled material, we are yet to tap into its true potential.
Today, Deep.Meta’s software monitors production line data, to characterize and flag up defects that would otherwise go undetected or take a long time to investigate. This directly saves time to metallurgists and operators as all the relevant information for that defect is consolidated in one place rather than across multiple sections of the mill. Early identification means defective products are taken out of the production line before these problems compound, saving customers millions of dollars a year in scrap generation which in turn cuts CO2 from avoidable remelting.
Tomorrow, steel will be more than the thing that makes things and we will leverage on its ubiquity in society and it will become a means of monitoring use and hence the lifetime of structures a concept we’ve termed ‘iron-dating. In this scenario, Deep.Meta’s software will determine the life of a steel component in its respective application, home appliances, office buildings, Power stations and indirectly the life of the other constituent components, hence we can gain more information on the materials life cycles of structures or products steels are used in. This will allow us to more accurately predicting supply chain behaviour, materials life cycles and so more effectively plan cities and allocate resources. With this, we will have a view of our World as never before from primary to tertiary sectors to closely monitor the flow of materials through the supply chain.