• Case Studies
3min October 25, 2023 3min Oct 25, 2023
October 25, 2023 3 minute read

Building materials company saves $200k with recipe optimization

$200k saved with recipe optimization


saved annually on a single process
to build a digital twin of their production process


As their initial use case, a global building materials manufacturer wanted to address temperature variability on their roofing material production line. Engineers had a sense of where the problem was originating but couldn’t get the level of granularity they needed to make significant cost-saving improvements. 

Optimizing this recipe would enable production teams to continue producing a high-quality product while saving on both cost and energy usage. Real-time data, structured to account for lag and residence times, would enable them to instantly analyze, identify, and resolve variability between batches. 

Identifying a small optimization in temperature control would have a direct and immediate impact on overall productivity, throughput, and cost.


Braincube’s tools enabled SMEs to understand the interrelated impact of different production variables within a digital test environment without wasting resources. Pairing these analyses with real-time production data enabled teams to narrow in on the root cause of the temperature variability—a mechanical malfunction—and quickly implement a change.

“Braincube is bringing data-driven decisions down to the shop floor level and helping people understand the value of data.”

Digital Manufacturing Lead at a global building materials manufacturer

This single discovery resulted in $200,000 in annual savings. Once the mechanical piece was fixed, teams set to work identifying other cost-saving improvements within their production data. 

Making data available to each team has also opened greater collaboration channels between engineers and operators, reinforcing the company’s goal to instill a data-driven culture. The company is excited to scale these cost-saving optimizations across its other roofing material plants.

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