Will Machine Learning Replace Technicians?

"Will machine learning replace engineers, doctors, farmers, data scientists, translators?" All it takes is a Google search to observe the panic that is spreading to the labor market. The triumphant announcement of the technological progress made by one or another start-up sounds like a short-term threat to 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 feel particularly concerned about the "robot threat". Industry 4.0 and CMMS (Computerized Maintenance Management Systems) have already entered the factories, but face mistrust and reluctance to change.

And that's a pity. Technicians' fears are cutting off their access to long-awaited business tools. What if industrial maintenance experts had everything to gain by becoming machine learning actors?

Stop fantasizing about this technology

From Modern Times to Terminator, the notion of "intelligent” or “learning machines" fuels all fantasies. But sticking to science fiction harms both artificial intelligence enthusiasts and all-mechanical nostalgia. 

Without a pragmatic understanding of what machine learning or CMMS can bring to the company, progress will go unheeded. A Deloitte survey on 4.0 industry paradoxes points out that 94% of business leaders consider digital transformation as one of their primary strategic objectives, but only 68% of them say they know exactly how to take advantage of it.

So let's start by solving the mystery.

The extension of artificial intelligence

Far from the unbridled 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...".

Machine learning is a form of artificial intelligence, which feeds its algorithms with data from concrete situations. From the formula, we move on to the construction of a model designed to correct the approximation curves of a weak artificial intelligence. By "learning" from real situations, the machine learning acquires predictive and prescriptive skills.

The two rules for a smart use

Combined with the Cloud, which provides it with computing power, and Big Data, which provides it with information, machine learning opens up new horizons for Industry 4.0. But only human intelligence remains essential to determine which of these horizons should be explored. 

Industrial maintenance, agriculture, transport, energy, automotive... Our blog offers a wide catalog of the many 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 the technicians. 

A tool in the hands of Industry 4.0 technicians

Nevertheless, corporate speeches are rarely enough to reassure employees who are worried about their jobs. According to a study by the Pew Research Center, 72% of employees say they feel anxious about 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 result, is accompanied by a creative destruction phenomenon that it would be absurd to deny. Artificial intelligence can improve the performance of the vast majority of jobs currently held by humans.

But it will not make human resources obsolete! Our society is having the wrong debate when it worries about a "generalized 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, 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, the new requirements for performance, responsibility, and traceability that 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 business of collecting and analyzing information. To understand and optimize the functioning of their industrial ecosystem, technicians have traditionally used sensors linked by proprietary communication protocols. But the data could only be used in a limited environment.

machine learning cmms

Mobility Work CMMS is provided with an analytic tool to help you analyze all your maintenance data and adapt your strategy

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

Switching to prescriptive maintenance  

Industrial technicians already mastered predictive maintenance, based on their own knowledge and experience of 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 prescriptive maintenance. This plays on the cognitive analysis of the data collected by the connected objects to impart behaviors to the industrial ecosystem that optimize its performance.

Rely on a community of CMMS experts

The power of machine learning lies in its ability to analyze information from multiple sources and connected to the field. It is up to the technicians to take over this mode of organization!

Mobility Work offers a community-based maintenance management platform for industrial players. The Mobility Work application provides a forum for the exchange of best practices and information on the business challenges of industrial maintenance. By pooling their know-how and appropriating machine learning technologies, technicians become the first actors of the industry's future.

Join the maintenance community!