Data Science in IIoT is often associated with predictive maintenance – clever algorithms that predict when machine parts wear out, go out of alignment, or otherwise will be in need of repair. This is then used to schedule maintenance to avoid unnecessary downtime, thus keeping machines up and running and earning their keep.
But Data Science is a broad field that can bring more advantages to your operations than this.
As an example, consider a well-known, large European cement producer. For them, energy consumption is a matter of profit or loss, as 30% of the cost of cement is due to the energy consumed during its production. Recognizing this fact, the company went to great lengths to optimize, and standardize, operating procedures.
However, ei3‘s team of Data Scientists noticed that some plants, sometimes, were doing significantly better than the overall average, showing an up to 40% lower energy use compared to their peers for otherwise identical production.
Further analysis showed that these instances could be traced to individual operators: Old-timers, due to their unique skill and experience, applied good judgment and found ways to optimize production beyond what standard procedures would require. Our team could isolate these judgment calls and make them part of the standard operating procedures now applied by all operators. Based on the actions observed from the experienced operators and their positive outcomes, the system pro-actively makes recommendations to novice operators to take the same, or similar actions.
The system acts as a “trusted advisor”, not a “big brother”: the operator can interrogate the system for the reasoning for this action, and take his or her own decision as to its appropriateness under the current circumstances. As a result, overall energy consumption across their European network of manufacturing sites was reduced by 18 million Euro per year.
Any enterprise wishing to optimize resources can benefit from ei3’s data science capabilities, to reduce cost and energy consumption, while helping the environment.