Artificial intelligence was long considered the stuff of science fiction. That’s no longer the case, but its potential is still often underestimated.
Although artificial intelligence (AI) is one of the key concepts most discussed in the context of digitalisation at present, the specifics of its application are often hard to grasp. What exactly is artificial intelligence? And what benefits can it offer your company? It therefore comes as little surprise that, according to a survey by market research company Wakefield Research, the vast majority of decision-makers still underestimate the potential and importance of artificial intelligence – in mechanical engineering as in other sectors. Some 30 senior executives and 70 IT managers from companies in Germany with at least 1,000 employees took part in the survey. It revealed that 98 percent of respondents consider artificial intelligence to be a contemporary trend, but some experts see things very differently.
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Artificial intelligence (AI) boosts turnover in mechanical engineering
Early in 2018, management consultancy Accenture estimated that, by using artificial intelligence, the average company could achieve a 38 percent increase in turnover in the period to 2022. A study by Germany’s Federal Ministry for Economic Affairs and Energy (BMWi) provides more specific figures demonstrating the positive impact of artificial intelligence in mechanical engineering. By mid-2023, it predicts the use of artificial intelligence in Germany’s manufacturing industry will generate an additional gross value added of around 31.8 billion euros – roughly a third of the sector’s total growth during this period. The impact the coronavirus crisis will have on the industry remains to be seen, but that in no way changes the potential artificial intelligence offers the sector. The key question is how exactly this can be harnessed in mechanical engineering.
Artificial intelligence allows us to hand over even complex cognitive tasks to machines.
Before we can identify applications for artificial intelligence in mechanical engineering, we first need to understand what exactly “artificial intelligence” means. It is usually defined as the methods which enable a computer to solve problems that humans can only overcome using their intelligence. This means artificial intelligence allows us to hand over even complex cognitive tasks to machines, in addition to physical and/or mechanical ones. A next logical step would be for artificial intelligence to take over monotonous tasks that people often find demotivating in the long term. In mechanical engineering, however, artificial intelligence opens up far greater opportunities, as demonstrated by the example of predictive maintenance.
Predictive maintenance – a prime example of artificial intelligence in mechanical engineering
As the name suggests, predictive maintenance is a type of (machine) maintenance. It offers a number of significant benefits. In the case of traditional, reactive maintenance, faults are only investigated and rectified once they’ve occurred, but predictive maintenance measures take place at the ideal time. This prevents both the failures that are inevitable with reactive maintenance and the waste associated with preventive maintenance. In the latter case, wear parts are regularly replaced – even if they would have continued working for some time. Predictive maintenance is made possible by using artificial intelligence to evaluate big data.
Existing databases are evaluated as a starting point for making reliable predictions.
The form of artificial intelligence used for predictive maintenance – machine learning – in a way provides a glimpse into the future. Existing databases are evaluated as a starting point for making reliable predictions, such as the aforementioned ideal time for replacing wear parts. This makes it apparent, if it wasn’t already, that the countless terms associated with digitalisation can’t be neatly compartmentalised, because they are inextricably interlinked. After all, machine learning is both a form of artificial intelligence and a big data evaluation method. What’s undeniable is that mechanical engineering companies can’t afford to miss out on the new avenues and opportunities artificial intelligence opens up for them.
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