Five papers covering different aspects of steelmaking were selected for presentation by DASTUR at the AISTech conference to be held from May 07-10, 2018. DASTUR’s expertise in the areas ranging from engineering to operations, process improvement to project dynamics, along with its recent success in Machine Learning and AI-based approaches will all be shared with an audience consisting of over 7000 people and 500 companies.
Two papers focus on utilization of machine learning and AI-based techniques for the attainment of better strike-rates during dephosphorisation and desulphurization reactions. The dephos model along with a machine learning approach, can suggest real-time operating recipes to the operators resulting in a substantial 9% increase in the current success rate of the heats complying with the aim phosphorus level.
Developed from DASTUR’s experience of successful implementations, the third paper discusses the design analysis required and the expected benefits from heat size increase in Basic Oxygen Furnaces (BOFs). The fourth paper outlines a methodology for comparative analysis for various Electric Arc Furnaces (EAFs) with different charge mixes based on key techno-economic and environmental factors, for both cost minimization and grade development.
The final paper elucidates DASTUR’s advanced project dynamics model, which takes a systems dynamics approach to simulate real-time changes that are the reality of most large projects. It describes how quantifying risks of delays and having a trade-off zone using sensitivity can result in saving 20% schedule and cost overruns, and is superior to traditional project management techniques when it comes to assessing the domino effect correctly.
DASTUR will also be taking part in the AISTech exposition. The DASTUR team enthusiastically looks forward to customers and industry participants' attendance at the talks as well as at the exhibition at booth #1856.