Tata Steel
Assembly Line
Quality Execution System® – two use cases in the European metals industries
Data from various automation levels is consolidated to represent each coil, bridging the gap between the physical and digital realms. This requires data to be transmitted flawlessly, enabling the virtual coil to mirror the physical coil. As the coil progresses through the production route, a digital counterpart is created at each stage of the process. The Quality Execution System (QES®) is designed to gather, combine, and examine all the data pertaining to a coil, thereby establishing the foundation for its digital twin.
Speira, a leading European aluminum rolling and recycling company, is expanding the QES® application ‘Automatic Coil Grading & Release and Genealogy’ to two of its strip coating line routes as part of a long-term digitalization initiative it launched earlier. Speira’s aluminum rolling mill in Grevenbroich, Germany stands for high-quality automotive, beverage can, foil and lithographic products.
TATA Steel, the second largest European steel manufacturer, is also expanding cooperation with SMS as part of a long-term and early-started digitalization initiative. TATA started with their automated coil release at the cold mill in 2012. One of the main goals was to improve the utilization of surface inspection data and conduct post-processing. TATA invested in the automatic coil release for the DSP (direct sheet plant) and Hot Mill shortly after. The Cold Mill now started implementing the PDW part of the DataFactory. Wouter Overgaauw, Manager Quality Assurance Cold Rolling Mill Ijmuiden, states: “The amount of measurement data is steadily increasing, the possibilities for data-driven applications are improving, the PDW gives us the possibility to make better use of both data and applications.”
Databricks Announces Lakehouse for Manufacturing, Empowering the World's Leading Manufacturers to Realize the Full Value of Their Data
Databricks, the lakehouse company, today announced the Databricks Lakehouse for Manufacturing, the first open, enterprise-scale lakehouse platform tailored to manufacturers that unifies data and AI and delivers record-breaking performance for any analytics use case. The sheer volume of tools, systems and architectures required to run a modern manufacturing environment makes secure data sharing and collaboration a challenge at scale, with over 70 percent of data projects stalling at the proof of concept (PoC) stage. Available today, Databricks’ Lakehouse for Manufacturing breaks down these silos and is uniquely designed for manufacturers to access all of their data and make decisions in real-time. Databricks’ Lakehouse for Manufacturing has been adopted by industry-leading organizations like DuPont, Honeywell, Rolls-Royce, Shell and Tata Steel.
The Lakehouse for Manufacturing includes access to packaged use case accelerators that are designed to jumpstart the analytics process and offer a blueprint to help organizations tackle critical, high-value industry challenges.
Advanced analytics of sinter plant operations to minimise particulate emissions
Advanced Analytics of Sinter Plant Operationsto Minimise Particulate Emissions(PM). Use of data analysis techniques to improve understanding of the process and correlate process parameters and raw materialsto PM emissions and to identify areas of opportunity to decrease PM to the local community. Understand the effects of chemistry upon performance, focusing on reduced chlorides by treatment of reverts, effects on sinter quality and design/implementing new sinter process filter system technology on a laboratory scale to capture and measure PM emissions.