Berk is the CEO of Fero Labs, an industrial process optimization software company based in New York. He is passionate about helping large industrial companies advance their digital transformation goals using explainable machine learning.
Birand holds a Ph.D. in electrical engineering and computer science from Columbia University. His academic research focused on optimizing wireless and optical networks with efficient cross-layer algorithms. He developed scheduling algorithms for optimizing cellular base stations in 5G networks and has several patents in IoT systems for resilient fibre-optic networks.
Changes to product chemistry boundaries are made only a few times a year. However, during the period between chemistry modifications, there are still opportunities to optimize chemistry limits within the boundaries for cost and product performance measures. This includes accounting for process and raw material cost fluctuations, which have a direct impact on operating margins.
Machine learning software optimizes alloy additions during the refining stage in the melt shop, ensuring that mills maximize cost savings while continuing to meet mechanical property specifications. This presentation will discuss the details of this novel technology and how it's been deployed to five mills in North America in real-time optimization mode. In addition, we'll share the savings achieved as a result of integrating ML into the chemistry optimization process.