Founded in 1908, BRC is the UK’s largest supplier of steel reinforcement and associated products for concrete. With a network of strategically placed manufacturing locations, BRC is able to meet all customer requirements regardless of the size of the project. Moreover, it complies with the highest quality and sustainability standards and can be found in iconic projects such as the second Severn Crossing, the Principality Stadium, Wembley Stadium, Merseylink Gateway, CrossRail, Falkirk Wheel and Aberdeen Western Peripheral Route.
BRC strives to reduce the environmental impact of its operating processes. In that regard, BRC ensures that its reinforcing steel main raw materials have been responsibly sourced. This reinforcing steel is produced via the Electric Arc Furnace (EAF) method, giving a 98% recycled content to the finished product. Producing steel by utilizing this method can reduce its carbon footprint by nearly four times when compared to the Basic Oxygen Steelmaking (BOS) process. BRC couples its production processes with robust supply chain traceability and favorable carbon footprint in order to ensure its customers meet all requirements related with modern construction projects.
With respect to its production facilities, BRC connects to shop floor systems via a rudimentary communications’ system which allows barcodes to be printed on the shop floor detailing customer orders. From there, on the shop floor system there is a continuous laborious process with the steel required for the concrete reinforcement transferred to the required processes using the operator’s knowledge of interpreting the drawings and setting the machines to bend the material to the required specification. Within FACTLOG, BRC wishes to optimize its machinery operational capacity and maintenance processes via predictive machine analytics (interrelating oil levels, greasing requirements, drive wear, temperatures, vibration etc.), also incorporating cognitive characteristics to further capture unresolvable situations, thus leading to predictive fault prevention. In that regard, FACTLOG needs to enable integration with a knowledge-share solution enabling the automation of maintenance alerts to all responsible parties. Moreover, BRC wishes to utilize machine learning and artificial intelligence to support work order handling and to offer dashboards that enable situational-awareness from high level KPIs down to operator/machine/shift/breakdown data; this information must then be used to facilitate resource- aware mid-term production planning.