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Artificial Intelligence: Science applied to industry and decision-making

27 December, 2018

When we talk about artificial intelligence, we all get Hollywood movies, from the evil Terminator Skynet to the no less evil Matrix. It must be said that these kinds of sci-fi films are much closer to fiction than to science.

So what do we mean when we talk about artificial intelligence? We’re talking, basically, about math. Computers are terribly efficient at speeds unimaginable to a human being. Artificial intelligence is only  the application to any area in which it is necessary to perform many calculations very quickly of very complex mathematical formulas (algorithms) made by computers  or, rather, by microprocessors.

A practical example that many of us already carry in our pockets are smartphones with cameras that use artificial intelligence to automatically adjust camera parameters based on lighting, whether people or objects appear, whether they are in movement, etc., to get the best picture from among all possible combinations.

Artificial intelligence comes from the exponential increase in the computing power of microprocessors. Algorithms that only a few years ago could only be executed in supercomputing centers are today available to computers or servers that any company can have.

Applying artificial intelligence to enterprise decision-making

One of the most interesting aspects of artificial intelligence is its predictive capability. Virtually all large financial market operators use this technology to predict market developments in near real time, so that computers control portfolios of securities and, based on the data available to the algorithm, make the decision to buy or sell those securities.

Artificial intelligence is one of the basic pillars of Industry 4.0. Until now, decision-making was mainly based on the “forensic” analysis of what has already happened. We refer to the usual strategic meetings of companies in which the results of the month or quarter are analyzed and from there decisions are made to plan the next period. But the big drawback is that projections are being made to the future of things that have already happened, trusting that the trend will be maintained or will change based on a limited amount of data, but almost never in real time as it is very complex to do so.

However, if we know that computers are better than humans in data analysis and decision-making, why not take advantage of that possibility? Industry 4.0 provides tools, such as robotization and production sensorization, that generate real-time data. The same is true of logistics, orders or many other parameters that are fundamental in the good governance of a company. An artificial intelligence algorithm can simultaneously handle a huge amount of different data, incorporate it into a mathematical model (the “digital twin”) that faithfully reproduces the functioning of the company and make predictions from them, something that a human being, however expert in strategy, is not able to do at the same level.

Does that mean we have to leave the company government in the hands of computers? Absolutely not. The companies that are dedicated to the development of Industry 4.0 do not raise that scenario. What we are raising is the cooperation of human biological neurons with the digital neurons of machines. Strategic planning remains (and will be for a long time) people’s heritage. But artificial intelligence is a valuable tool that allows us, thanks to simulation techniques, to predict different scenarios from a given situation with a high degree of reliability. Questions of the type:

  1. When will I need to increase my production capacity and in what aspects of my company should I?
  2. How far should I increase that capacity (or reduce it, if that were the scenario)?
  3. Is my company properly sized in terms of personnel and equipment to cope with the strategic plan?

… and many similar ones can be answered much more easily and, above all, much more precisely thanks to artificial intelligence. And in a company, in any company, not going short or going too far means an automatic improvement of productivity while a significant savings in costs and investments.

In the same way, there are mathematical models that allow to simulate the forecast of demand that facilitate results to adjust, balance and optimize stocks, guaranteeing incredible levels of service.

Until now, the application of high-tech artificial intelligence was only economically justified in large corporations, given the cost of its implementation. But, as we said at the beginning, the necessary technology is no longer so expensive, so more and more companies would gain in the cost/benefit equation if they implemented the technologies of artificial intelligence,  robotization, sensorization, simulation and digital twin among others) proposed by Industry 4.0. And in the very near future, companies that don’t will be losing the productivity train.

NORLEAN is much more than a simulation company. We are a multidisciplinary team (Engineers – Experts in productive operations, Business Experts, Marketing & Sales, Data Analysts, Technologists, Mathematicians and Financials),we make clear the direction in which the technology applied to the world of the company moves and we have set out as a mission to democratize access to that technology so that not only do large corporations benefit from it. Because the future is already present, here and now.

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