Leading local cement manufacturer Republic Cement is thinking out of the box, according to its President and CEO Nabil Francis.

In a recent webinar, Republic Cement told reporters that the company is using data science and artificial intelligence (DSAI) to cut carbon dioxide (CO2) emissions and produce stronger and higher quality cement. According to experts, the strength of cement is typically measured only after a 28-day waiting period, wherein samples cast from one batch of cement are molded into cubes, cured, and tested for its strength using a compressive strength testing machine. Moreover, the compressive strength testing machine applies pressure to the cement cube until the sample breaks, making the load or weight at which the sample breaks the strength of the cement batch.

Data science tool to instantly predict cement strength

To start the ball rolling, Republic Cement established a comprehensive data infrastructure to collect relevant data about the various states and chemical compounds present in cement across the whole manufacturing process and identify its qualities after curing for 28 days. Aside from collecting and digitizing  data,  there was also a need to advance  this data into relevant information. Up until a year ago, the data was simply sitting in a database with little to no role in decisions that affected the 28-day strength testing results, which largely relied on reactive decisions based on these results.

The consequences of not utilizing data to support the cement manufacturing process resulted in the inefficient use of raw materials, which translated to higher costs.