Trying to anticipate the future in some way is without any doubt among the main priorities of the big business realities of today.
Playing in advance not only allows you to always be ready to change, but also to foresee all the criticalities that would inevitably go to turn into damage for the company. For many industries the goal is to use predictive analysis in industry to achieve greater process management efficiency. And therefore obtain a consequent economic advantage.
One of the purposes may be to provide indications on the state of health of the machines, in order to signal any possible failure in advance, giving time to staff qualified to intervene before an actual critical situation occurs, linked for example to the levels of pressure or overheating of machinery.
To get to the algorithms, we analyze the standard working conditions of a machine, together with the anomalies and the subsequent diagnostic analysis: prevent critical issues through predictive analysis therefore makes it possible to intervene on machines at risk of failure with advance, guaranteeing much shorter downtime and maintenance costs. In addition, the algorithm takes into account the efficiency curves of the individual compressors
and proposes room arrangements for maximize performance, suggesting for example the maximum annual number of hours worked per machine and the number of programmable switching on and off.
The development of predictive analysis allows us to increase margins, making operational processes and maintenance-related processes more efficient: for an industrial reality, for example, the savings obtained with these technologies can amount to several hundred thousand euros per year. But the application does not stop at the industry. Take, for example, the sustainable energy production sector. For wind power, the algorithms can be used to study the activity of the blade and understand when it is the most opportune time to replace a rotor. In thermoelectric generation, it is possible to identify the best efficiency curves of the turbines.
Artificial Intelligence also plays a fundamental role in allowing to automate management and control, offering the “human” team the possibility (and time!) to devote in other activities in the company, but it also favored a better and more functional interaction between the brands and its target audience: the companies can support health professionals in medical diagnoses or sorting of specific exams like x-rays, select curriculum vitae through specific filtering criteria and, of course, offer services or products really related to tastes, needs and expectations of their interlocutors.