Welcome to Steel 4.0.
Steel 4.0 refers to steel in the 4th industrial revolution. Economic analysts say the first industrial revolution was the Mechanical Revolution in the 18th century. The second was the Electrical Revolution in the 20th century. The third was the Electronic Revolution in the 1970s and the fourth is the Cyber Revolution relying on digitally captured data and autonomous AI execution. This includes real time, historical and predictive data.
In the steel industry, digitalisation aims to improve productivity and facilitate entry to new markets. Operational data is collected from handling raw materials, mobile assets, manufacturing, processing and transportation. Collection methods include sensors, despatch systems, lab systems, GPS, PLC systems, SCADA systems etc.
There are several key areas where digitalisation is being implemented in production operations:
Process Productivity
When operators, managers and engineers in mills and smelters have access to real time operational data and process condition monitoring they should be able to intervene with adjustments, processes and parameters more efficiently. The flow and pacing of materials and supply chain can be visualised and hopefully managed better.
Energy and Water
Energy and water represent some of the highest costs to steelmakers. Cyber monitering of usage is intended to help identify leaks, wastage and inefficient consumption. You can see that in an "energy crisis" governments would have data to inform their decisions about rationing use.
Asset Reliability
Helping to increase the uptime and decrease the downtime of machinery by continuously monitoring its condition of equipment should mean greater asset production. Maintenance becomes less reactive or calendar based and more responsive and conditon based. AI would also predict when maintenance is likely to be needed based on collected data.
Environment, Health & Safety
New regulations aimed at steel manufacturing by government can mean fines or suspension of operations for companies deemed to be non compliant. Continous real time environmental, accident and incident monitoring not only helps to avoid potentially catastophic outcomes through rapid course correction but also provides evidence for audits.
Quality Assurance
Real time monitoring alerts operators to quality deviations in their product before significant quantities of rejected materials are produced. The use of AI enables better prediction of quality issues, too. Certification and the geneology of materials can also be tagged and tracked throughout the production process so the provenance of material is easier to ascertain.
KPI & Reporting
Having an integrated data system across a plant, with uniform definitions and calculations, creates one version of the truth, despite many participants, which simplifies reporting.
This article is a summary excerpt of the video presentation "Beyond Digital Transformation: What AI Means to the Steel Industry" by Petuum. Watch the full video here.