What if the fridge could tell you when the milk was going off, or a city’s parking meters could link up to advise you where there’s a space, or your car could let you know before the exhaust pipe falls off in the middle of the motorway?
Even better: what if instead of just telling you, the fridge orders milk to be delivered, the parking meters tap directly into your sat-nav, and your car sends for the mechanic?
The terms ‘Internet of Things’ and ‘automation’ are not new — the idea of being able to arm machines with not only the ability to monitor themselves through sensors, but also with the means to connect directly to those who need to know (and can take action) has been theoretically possible for quite some time. But making this world a reality comes with many different kinds of problems:
How do you work with old machines that were invented before the internet?
How do you connect hardware from one company to software from another?
How do you make sense of the data gathered by so many different pieces of technology, and communicate it simply, as opposed to thousands of notifications of varying importance bombarding your mobile phone?
And how do you convince people that it’s even worth doing?
Adapting to Industry 4.0
In some instances, this level of technological advancement isn’t required, but in the world of manufacturing, being able to communicate with machines could be the difference between a company thriving and a company going bust.
“If you look at the Forbes 500 list five years ago, 50% of the companies are no longer there, because they struggled to embrace the digital revolution,” explains Vinicius Strey, a Digitalization Consultant for the Motion Control Services team at Siemens, USA. “Some companies don’t acknowledge that by embracing this fourth Industrial Revolution, the bottom line of their business is impacted positively. It’s my job in Siemens to convince them otherwise.”
What you’ve got to understand about the world of manufacturing, is that machines have been powering this industry since well before the world wide web. And the machines that originally replaced the humans, which have been incrementally improved as time has moved on, are still great at building products. They are reliable, and simple to take apart and put together again. As the saying goes: ‘If it ain’t broke don’t fix it.’
But when one machine malfunctions, the whole factory has to shut down. And although the machines get the job done, there are definitely shortcuts and efficiencies that could be made if we knew more about what was going on beneath the hood.
Even if a factory does invest in brand-new, digitally advanced machines, the data that is gathered about the inner workings of the production line is far too much for a human to analyze and take action upon. If the machine starts to show signs that it’s close to a malfunction, these signs could simply be lost in translation
Conversing with computers
Vinicius’ job is to get the machines talking — clearly. As well as to convince factory owners that there’s real value in conversing effectively with their mechanical workforce. A Brazilian, now based in Atlanta, he is in charge of going into factories, assessing their current machines — new or old — and then extracting and analyzing their data to inform the factory how to increase the yield and the lifespan of their machines. And, of course, how to save them precious time and money to keep them on that Forbes 500 list.
“My customers might have machine tools with or without Siemens controls, and they don’t know the potential of the information they can collect out of these machines. So I help them collect all this information generated — every second, every millisecond by those machines — and make this information understandable.”
The information might be around the standard health of the machine — the temperature or the processing speed — or more complicated readings around at what times of the day, and with what amount of energy, the machine is most efficient. Vinicius finds ways to collect all this information and analyze it for the factory.
Saving five seconds might not sound like a lot when you are creating one product, but when you’re creating hundreds, if not thousands, that saving directly impacts the profit of the factory. It’s not difficult to imagine the savings that can be made if you can spot a fault in a machine and fix it, before the whole thing breaks and shuts down the entire production line.
Bridging the gap between machines and humans
For Vinicius though, one of the toughest — but most enjoyable — parts of his job is communicating with both engineers and those without technical backgrounds in order to make the changes in the factories a reality. “My job, first of all, is to stimulate adoption. This is an underdeveloped market, especially here in the US, but across much of the globe too. So, my first task is to go to the customer’s factory, find the technical person responsible and convince them that this can bring them some results in the short and long term. Then I help them convince their senior management — the people who can invest in the solutions — and get them to buy, so we can move on and make it happen.”
Vinicius has to sell in entirely new digital technologies to people who are used to working with analogue mechanical technologies, and essentially ask them to change the way they do their work. “This means 90% of my job is education. I’m saying things like: ‘Hey, perhaps you could operate your machine this way, why don’t you try to do it differently? You know you can get better machine yield, and you can maximize the life-span of your machines, if you try this?’”
Vinicius translates data from machines for humans. He has to work out what information is crucial to what audience, and frame it in a way that makes the most sense at the right time — in terms of selling in the work he does for customers, but also in terms of providing an analysis of the machines.
Many people speak about the dangers of automation in terms of ‘stealing’ human jobs, but this kind of work is not just about cutting down human hours, it’s about making machines even more efficient. Making machines produce more in less time. Enabling companies to save money on wasted factory outages. It’s not about getting rid of everything currently in the factory, it’s about upgrading it, and augmenting it, to make it fit for the 21st century — both for the humans and the machines.
As time and technology move forward, there will always be a need for a translator. Humans, and machines, are all pretty unique — and the one-size-fits-all approach to working with them doesn’t compute. Factories will become ever-more automated and ever-more efficient. The machines will soon all be able to talk, to flag when something might be going wrong, and advise on what can be changed to make them faster, better, stronger.
But we’ll still need those who can talk multiple languages — between different machines and different humans — and those who move with the times and are intent on bringing others along with them. It will always be those who are ahead of the curve, and prompting huge behavioral change, who lead the pack into the future.
It seems like getting machines to talk, therefore, can only ever be the job of a human.
Maybe…
Vinicius Strey has been with Siemens for more than 10 years and is currently a Digitalization Consultant with Siemens Motion Control Services team at Siemens, USA. He supports asset owners to overcome challenges and get the best value from opportunities enabled by industrial digitalization in the machine tool environment. Previously, he worked with industrial security services and Siemens’ cloud-based platform MindSphere. Find out more about working at Siemens.
Photography: Fernando Decillis
Illustration: Vanessa Branchi
