As experts in digital transformation, ifm manufactures industrial sensors and solutions for technical processes. Manufacturers’ Monthly finds out from national IoT business manager at ifm, Freddie Coertze, how the company is putting the power back into the engineer’s hands.
The concept of IoT within the manufacturing industry is not a new one, ifm’s Freddie Coertze told Manufacturers’ Monthly, but effecting the implementation of IoT technologies within a business is a different story.
“We’ve moved beyond the stage of ‘Industry 4.0’ and ‘IoT’ as buzzwords that are new to people,” Coertze said. “I think everyone is familiar with those terms now, but the notion of digitising everything – that does still in many cases remain in the realm of ideas. What we haven’t had enough of is proving a tangible return on investment.”
ifm is a manufacturer of industrial sensors and solutions for technical processes specialising in sensors, networking and control systems for a broad range of specialised applications.
While Coertze noted that customers understand the value of IoT technologies at an engineering level, oftentimes engineering business units have struggled to sell the technology internally to the board.
“Such technologies are well and good in theory, but if you don’t have tangible outcomes – ROIs tied to business KPIs – then you’re not going to be able to make the internal business case for them,” he said. “There are always competing pressures over the same finite budget, so if you can’t provide the best business case for an IoT project, then you won’t get funding for it.”
Coertze said that at ifm, they’ve been trying to flip this situation around, helping their customers to make the business case internally such that they can reap the rewards on the operations ground.
And one area where ifm is really pushing to make such business cases is with Moneo, ifm’s powerful IIoT (Industrial Internet of Things) platform.
The Moneo solution
Continuous evaluation of process data provides the basis on which sustainable and successful business decisions can be made. And in order to obtain such data from the manufacturing floor, reliable connection of sensors to IT infrastructure is essential.
Moneo combines the level of operation technology with the level of information technology. Sensor data generated in manufacturing plants can be read and processed easily and used as the basis for sustainable corporate decisions.
With its modular structure, Moneo consists of basic software plus applications – for example, condition monitoring – making it possible to put together a tailor-made software package that suits unique business requirements.
“In the abstract it’s difficult to make the business case,” Coertze said. “Once you tie it to a specific business challenge, it’s a different story. Recently we had a customer for whom we performed some condition monitoring with Moneo, and the results were awesome. But notwithstanding the results – Moneo was still considered a ‘nice-to-have’ technology rather than a ‘need-to-have’ technology’.”
Months later, ifm visited the same customer, and that customer had experienced a big breakdown in one of its power distribution boards, which took down the whole factory.
“One of their bus bars just blew up because of power demand,” Coertze said. “The customer then realised that they needed to start properly monitoring their power – and that it could be done with Moneo. Suddenly, it became relevant to the business because they’d lost production. It was no longer a ‘nice-to- have’ technology, but something they needed.
“Adoption of technologies such as Moneo is not a matter of people not knowing what they’re doing – it’s a matter of managing that internal business case. ifm wants to assist with that journey, and that’s why we’ve invested to help with our Consultancy Services. We help customers build a budget and a scope to help them sell it internally.”
To conclude the explanation of Moneo, Coertze explains the tool acts as ‘middleware.’
“Moneo wants to be sitting in the middle to act as the glue,” he added. “You collect parameters at the bottom, from the factory floor and put it into Moneo. After the data science and analysis, the data is pushed out to other platforms, because the factory may already have an overarching platform like an ERP system that sits on top. Being the link in the digital value chain is crucial.”
The Moneo toolbox
Historically, one of the major hurdles to be overcome when it came to integration of technologies has been the lack of ‘interoperability’, said Coertze.
“It used to be the case that if you’d buy software from a certain vendor, it was proprietary, and you could only use products or services from that one particular vendor,” he said. “IoT has broken down the barriers because of its flexibility. Moneo was designed to push and pull data from any platform, which is essential because oftentimes customers are dealing with legacy systems.”
But in addition to breaking down external barriers between technologies, where Moneo excels is in its modular flexibility internally.
“The thing about Moneo is that you can focus its applications on various things – condition monitoring, process monitoring, energy monitoring. But one of the key applications – and strengths – is its Data Science toolbox.”
It’s often the case that engineers need sophisticated data analytics, but the data analysts within the company are often preoccupied in other domains of the business – for instance with financials or other corporate data beyond the manufacturing process floor.
With Moneo, the power can be put back into the engineer’s hands, by providing sophisticated insights with respect to different sets of variables, without requiring the expertise of a pure data science person. The purpose of the tool is to monitor the critical process value (target variable) with regard to the production quality or the plant condition (e.g. temperature, flow, vibration, current consumption) on an ongoing basis.
AI (assisted predictive maintenance) methods use a mathematical model based on historical data for a permanent target/ actual comparison between measured and predicted target values. This data enables the automatic and early detection of anomalies in a critical process value.
“The data science toolbox makes it easy for the engineer to start identifying problems,” Coertze said. “It’s easy to onboard devices themselves. Whether its temperature, pressure, flow, vibration, whatever the customer wants to monitor about the machines condition – they pull it into a five step wizard that will do all those things in the background, meaning they don’t even need to know anything about databases or data science.”
The soft IoT tool helps engineers optimise manufacturing processes through early warnings and alarms.
“It really resonates with industry because they are used to always having to consult with IT, but now the engineer can take back the power and do what they do best – trying to predict problems and fix things.”
Consulting service
The adoption of IoT products and services has gained serious momentum over the last ten years in Australia. ifm now offers consulting to Australian businesses to help them fully profit from their foray into IoT, which was built out of a need in the market, said Coertze.
“We really saw there are a lot of constraints an engineer will go through on this journey – where to start, what software tools to choose, how to design and understand the whole system,” he said. “ifm understands the common problems across all kinds of industry. This is more a unique service we do on-on-one for the customer.”
The experienced ifm team will assess a particular business to understand its bottlenecks, identify inefficiencies and provide feedback on how they can improve.
“We will then help them with building a proper scope by providing the right soft tools to make them more capable.”
After seeing other IoT technologies fail to solve business problems, ifm is also offering its expertise and working with universities, to help students entering the industry.
“We want to help people with their step into digital transformation,” he added. “Anyone can have the technology, but you always need to translate innovation into return on investment and gains in productivity.”
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