Will machine learning replace technicians?

“The Machine learning Will it replace engineers, doctors, farmers, Data scientists, translators? ” All it takes is a Google search to observe the panic that is sweeping the job market. The triumphant announcement of the technological progress made by such start-ups sounds like a short-term threat to the ears of some professionals.

Industry 4.0: will machine learning replace maintenance technicians?

Perhaps because they were at the forefront of previous waves of automation, maintenance technicians seem to be particularly concerned by the “robot peril”. Industry 4.0 and GMAO (Computer-aided Maintenance Management) have already made their way into factories, but are facing mistrust and reluctance to change.

And that's a shame. Technicians' fears are cutting off their access to business tools that they have been waiting for a long time. What if industrial maintenance experts had everything to gain by becoming players in Machine learning ?

Stop the fantasies around this technology

Of Modern times unto Terminator, the notion of “intelligent machines” or “learning machines” fuels all fantasies. But sticking to science fiction serves as much to artificial intelligence enthusiasts as to all-mechanical nostalgic people.

Without a pragmatic understanding of what the Machine learning or CMMS can bring to the company, progress will remain a dead letter. A survey conducted by Deloitte on Paradoxes of Industry 4.0 highlights that 94% of business leaders consider digital transformation to be one of their first strategic goals; but only 68% of them say they know exactly how to take advantage of it.

So let's start by unraveling the mystery.

The extension of artificial intelligence

Far from the unrestrained scenarios of Black Mirror, artificial intelligence refers to nothing more than a computer program capable of reproducing human behavior. Most of the time, its “intelligence” is similar to that of an Excel formula, such as “IF... THEN... ELSE...”.

The Machine learning (or machine learning) is a form of artificial intelligence, which feeds its algorithms with data drawn from concrete situations. From the formula, we move on to building a model designed to correct the approximation curves of weak artificial intelligence. By “learning” from real situations, the Machine learning Acquire predictive and prescriptive abilities.

The two rules of intelligent use

Associated with Cloud, which provides it with computing power, and at Big Data, which feeds it with information, the Machine learning opens up new horizons for industry 4.0. But only human intelligence can tell him which of these horizons should be explored.

Industrial maintenance, agriculture, transport, energy, automotive... Our blog offers a wide catalog of the multiple applications found, in all sectors, of Machine learning and industry 4.0. With one nuance: these applications are always limited to tasks that are not already optimized by the expertise of technicians.

A tool in the hands of Industry 4.0 technicians

Despite everything, the speeches Corporate are rarely enough to reassure employees worried about their jobs. According to a study by Pew Research Center, 72% of workers say they feel anxious about the idea of a future where robots could perform more and more functions.

Their fears are not entirely unfounded. Digital transformation, of which Industry 4.0 is the culmination, is accompanied by a phenomenon of creative destruction which it would be absurd to deny. Artificial intelligence can improve the performance of the vast majority of jobs currently held by humans.

But it won't make human resources obsolete! Today's society is in the wrong debate when it worries about a “widespread replacement” by robots.

The added value of Machine learning is at the task level, not the job level. CMMS software, for example, relieves technicians of the most time-consuming, monotonous, and automatable aspects of industrial maintenance - and leaves them free to invest in the most interesting missions, to which human intelligence brings real added value.

Experts such as maintenance technicians, among other professions, have everything to gain from the advent of Machine learning.

Digital transformation and Industry 4.0 sometimes seem to be the almost unintended consequence of unbridled technological progress. But the driving force behind innovation is in fact at the level of new requirements for performance, responsibility, and traceability which are putting increasing pressure on industrial maintenance. This technology provides solutions to the pre-existing business needs of industrial technicians.

Putting Big Data at the service of Industry 4.0

Beyond its mechanical challenges, industrial maintenance is first and foremost a job in the collection and analysis of information. To understand and optimize the functioning of their industrial ecosystem, technicians have hitherto used sensors linked by proprietary communication protocols. But the data could only be used in a restricted environment.

Mobility Work goes further, by offering a CMMS software connected to sensors connected by standard Internet protocols (IP), which track a multitude of data on the condition of the machines, such as oil level, temperature, vibrations... Thanks to the Machine learning, technicians monitor the condition of the equipment in real time. LTHE IIOT (Industrial Internet of Things) is the source of information that maintenance professionals have been waiting for.

Switch to prescriptive maintenance

Industrial technicians already mastered the predictive maintenance, based on their own knowledge and experience with the machines they are in charge of. It went beyond reactive and corrective actions, but lacked precision.

Thanks to CMMS software powered by this technology, technicians develop a prescriptive maintenance. It uses the cognitive analysis of data collected by connected objects to impart behaviors to the industrial ecosystem that optimize its performance.

Count on a community of CMMS experts

The power of Machine learning depends on its ability to analyze information from multiple sources connected to the field. It is up to the technicians to take up this method of organization on their own!

Mobility Work offers a community maintenance management platform for industrial players. THEMobility Work app opens a place for the exchange of best practices and information on the business challenges of industrial maintenance. By sharing their know-how and by appropriating the technologies of Machine learning, technicians are becoming the first players in the future of the industry.

Join the maintenance community!