Andrés Cartagena Ruiz is the Head of MFL X and Servitization, a business of Italy’s MFL Group that leverages exponential technologies such as Industrial IoT, Artificial Intelligence (AI) and Cloud-based applications to create a customer path for Industry 4.0/AI technology.
Below, he discusses the potential and the challenges that are part of the company’s journey
WJI: How has your company’s Industry 4.0 technology evolved, and how big a role has Artificial Intelligence (AI) had in this?
I think that the definition of Industry 4.0 is often either misused or misunderstood. There’s a big hype in the world right now about AI, but it has been around for decades, so regardless of whether we’re talking about generative AI, machine learning algorithms or machine vision, for me Industry 4.0 is about leveraging tools that can have an exponential impact on a company’s operations. For instance, it would be impossible for a person to quickly analyze huge amounts of data and draw conclusions, but with modern AI tools you could do it in a matter of seconds. AI is just one of the technologies that are part of Industry 4.0.
The MFL Group can connect its production lines over its Industrial IoT application (Acumen). We can now pinpoint problems that were impossible to recognize before because the machines were “disconnected products,” hence we didn’t know their behavior under real industrial environments. The data that we now gather through Industrial IoT can be fed to AI algorithms that can help us identify future failures or potential improvements to our designs. In other words, data-driven product development is possible.
WJI: What is the goal of MFL X?
Our objective is to support wire, cable and rope manufacturers by allowing them to make better operational decisions and optimize OEE (Overall Equipment Effectiveness) based on machine data analytics; unlock a modern and data-driven technical customer support experience; deploy apps from industry standard scalable platforms; and all this by complying with the highest standards in cyber-security. Our MFL X apps are the result of our collaboration with 40Factory’s innovative approach within the fields of Industrial IoT, AI, industrial cloud-apps and immersive mixed reality (XR) technologies. With our digital tools, our customers can troubleshoot their lines and quickly find solutions without leaving the platform.
WJI: How does AI translate to improvements in your Industry 4.0 processes for the shop floor?
AI has many potential uses. Consider 50 MFL steel drawing lines operating in different parts of the world that are of the same model and equivalent configuration. We constantly receive data from all those lines and if you run the correct algorithms that analyze that data, you should for example know how a specific motor in a specific part of the machine behaves over time. Based on that information, then you may be able to say, “Ok, we should consider changing this motor type for another model to improve energy efficiency.” That’s an example of data-driven development. Another example is the potential to implement machine vision systems to analyze quality parameters, such as the lay length of a cable. You want to know if there are discrepancies in your production, especially if you are running at full speed. Lay length is normally measured by cutting a cable sample, bringing it to the laboratory and then measuring it manually. Well, why not do it in-line, with a machine vision system that is powered by machine learning algorithms?
These are just two examples of new AI-powered technologies that allow us to exponentially improve our methods of analyzing in-line quality and efficiency. Emma will play a big role here in interpreting the results of the algorithms through plain human language interaction.
WJI: Who exactly is Emma and why do you think she is going to be very important to MFL customers?
Emma is our new generative AI assistant that we launched a year ago and continue to improve. She will be able to serve our customers on a level that does not exist elsewhere. She is a daily companion to us at MFL and for customers.
Let’s start with the customers. If customer X owns an MFL copper rod breakdown line, they will receive an instance of Emma with access to the knowledge base for that specific machine. When she responds to a tech support question, the user can verify the source of the information Emma used to generate the response. The source can be based on one or several documents. If the user asks Emma something about a line that the customer does not own, she will not answer. Also, a customer cannot “train” Emma. They can only interact with her, but she excels at that. She can interact in more than 100 languages via text, speech-to-text and vice versa.
Since Emma is embedded in Acumen (Industrial IoT App) as well, you can ask her to analyze data for a specific cable you produced three months ago. What alarms went off during that production? How many reels were manufactured on June 3rd? She can go into the data and generate a response based on it. We have released it publicly but only for internal MFL use at the moment and we are very happy with the results.
WJI: How will Emma be of value to MFL staff?
Emma’s knowledge and capabilities will be of value to all MFL staff as she can be trained with anything. Some of the early stage uses include the onboarding process of new employees. Emma can lead them through the first days to make sure they learn the basic rules, procedures or digital tools that are useful daily. If they forget, they just need to ask Emma again. Another early use of Emma is for interpreting European regulations for machinery manufacturing with regards to industrial safety. These documents can be very hectic to read but once loaded onto Emma, she can point you to the correct norm related to specific issue you might have on a production line.
Lastly, a new MFL assembly floor worker, who is going through the internal testing procedures of a new rod breakdown machine, might have to flip through many pages of static documentation. Emma can show that employee the specific steps with images and videos for each specific test procedure. We expect Emma to be available for customers by mid-2025.
WJI: How does your partnership with 40Factory work?
40Factory supplies MFL with digital white-label apps that are configurable and customizable for MFL’s machines. They are not just a vital technology partner, but also one of our portfolio companies. MFL Group opportunistically invests in high tech companies through its Venture Capital vehicle (Bit Atlas).
40Factory is a developer of two solutions. The first one is MAT, a white-label industrial IoT application with a variety of modules that fit different industrial needs. MFL X’s IIoT app is called Acumen and is 100% based on MAT.
The second solution is Wilson.ai, a generative AI assistant that can be trained with specific knowledge, it has open APIs to connect to other cloud-based applications including, of course, Acumen. Like MAT, Wilson.ai is also a white label, so our Emma is 100% based on Wilson.ai technology.
WJI: Aside from Emma, can you list the other tools you offer?
- MFL X Scout. This is our cloud-based application that allows customers to order spare parts by seamlessly navigating the 3D model of your line. You can also access interactive operation manuals and intuitive maintenance video clips that can help you with the upskilling of your operators.
- MFL X Acumen. This is an Industrial IoT application that harvests valuable insights from industrial machines data. It is based on MAT (Machine Analytics Tool), a scalable, secure, highly configurable and multi-platform app designed and developed by Italy’s 40Factory.
- MFL X Wizard. This is a cloud-based engineering tool designed for you (the end user), for our engineering team and for our technical sales team. It allows users to run wire drawing line simulations to calculate line performance for specific wire diameters and materials, and to select the correct set of dies.
At an operational level, the applications are designed to support users in making informed strategic decisions, extracting value from the data generated by the production lines, as well as transforming customer service into an efficient and pleasant experience. These digital tools also unlock “Servitization” business model that benefit both our customers and MFL’s revenue model.
WJI: Are you pleased where your company’s technology now? What’s your biggest concern?
We are definitely excited about how things are developing from the technological point of view. What I consider the biggest challenge and the biggest reason why we can’t go faster, the answer is culture, and that includes internal company culture. The adoption of modern digital applications cannot be forced onto employees. Adoption must be accompanied by internal campaigning efforts. Management’s responsibility is to clearly convey the message to the whole company of why it is important for MFL to stay ahead of the curve when it comes to adopting digital exponential solutions. Once everyone is aligned, things start moving with inertia.
The whole human nature of a group change is not simple. Some colleagues may think, “Why do we have to learn this new tool if I’m going to retire in five years and this is so different?” The goal of our internal workshops is to invite everyone to adopt a life-long learning mindset. If someone properly uses all the tools that we can now provide, they could accomplish work faster and free up time to think about more strategic issues.
WJI: So, you have to sell the concept of what MFL can do not just to customers but to all MFL staff?
At MFL, we are now employing around 500 people, and you need them all to understand where the company wants to go. That’s why we hold internal events on a regular basis where we share what is possible with technology. The internal culture of both our customers as well as our staff must evolve. I believe that will happen naturally as we are in the middle of a generational change of decision makers inside the organizations. As more people who are tech savvy enter the field, there should be greater acceptance. We notice that with our new young engineers. When they go through the onboarding process, they are not surprised. They expect from day one to have the opportunity to work with modern tools, and they often ask about it during interviews. They want to know what we are doing with the industrial IIoT or what we are doing with AI. As an incumbent machine manufacturer, if we are not prepared to discuss such things, it’s just a matter of time before we find out that we no longer attract and retain young talent. We must keep up with technology. There’s no turning back, so we must learn how to leverage it.
WJI: Could AI ultimately result in jobs lost?
The goal of AI is not necessarily to substitute an employee, it is to help them. So, if for example, you are a machinery mechanical designer, AI should be seen as your copilot. If people have access to AI tools that allow them to work faster and better, then you should demand more quality and precise outcomes.
Sources
MFL X: Its Industry 4.0/AI Story Evolves, ‘hosted’ by Emma,” a Q&A in the November 2024 issue of Wire Journal International, featuring Andrés Cartagena Ruiz*, Head of MFL X and Servitization, a business of the MFL Group, and WJI Editor in Chief Mark Marselli.