At this year’s AMPER trade fair, we had the opportunity to present our perspective on manufacturing digitalization, data collection, and modern management of industrial technologies. In the interview, Tomáš Krejčí discussed why it is crucial today to know the real-time status of production equipment and how properly utilized data can help companies increase efficiency, reduce downtime, and better plan production.
The interview also addresses practical experiences from manufacturing companies, the most common problems in digitalization, and how smart manufacturing can be built step by step without the need for extensive investment in new technologies.
Data is the essence of digitalization. One of the key elements of Smart Industry is working with manufacturing data. What types of data do companies track most frequently today? What benefits can better handling of manufacturing data bring to companies? Is this the path you take with your company?
Exactly. That is the foundation our company was built on. I originally come from a manufacturing background, so I perceived the need for missing data. Historically, large MES systems and major solutions have existed for big enterprises, but every manufacturing company deserves digitalization, including small and medium-sized ones. A recent Eurostat report for last year states that only 20% of manufacturing companies in the Czech Republic work more deeply with digitalization. There are still 80% of companies waiting to step into a deeper digitalization of their processes. We want to enable companies to get there.
I’m a bit afraid to ask about statistics regarding digitalization strategy. Can a company start digitalizing even without a strategic plan, just to get started? Or is it necessary to think things through beforehand?
Without a strategy, it makes absolutely no sense. Unfortunately, we encounter this very often—management decides to digitalize, so they just go for it and look for some solution. Especially with MES systems, which are expensive and demanding to implement, a strategy and a dedicated team are essential. Without them, you are unable to build a sensible digitalization system.
You mentioned that working with data is fundamental. But what kind of data are we talking about? What does a company need to track first, and what usually brings results the fastest? After any implementation, everyone wants a quick return on investment. Which type of data enables this?
If we are talking about a manufacturing company, all digitalization stems from the need to “light up the machines.” This means data on the condition of production equipment, their productivity, what they are producing, by what means… That is the basis for building any digitalization framework or advanced application in a company. It is the very thing that brings one of the first impacts. Once you light up your productivity/unproductiveness, you can start working with it in real time and solve daily problems on the shop floor.
As part of the Smart Industry program here at the AMPER trade fair, you are also presenting a specific case study. Can you describe what the project is about? What customer problem did you solve, and what were the main goals of the implementation? And what specific results did the project bring to the customer?
It involves Tenneco, a company operating in the automotive sector that manufactures car valves. In the beginning, they didn’t have a strategy either; they were exactly that type of case: “Let’s get digitalization,” so they bought hardware, but soon found out it didn’t make much sense, didn’t give them what they wanted, and didn’t allow the solution to develop. Gradually, they realized they needed a strategy on which direction to take, so they replaced their solution with ours. As they learned to work with data and digitalization throughout the process, they discovered more things they wanted to optimize or digitalize within their processes. Today, we are at a stage where every paper they historically had to handle, or every Excel sheet they had to fill out, is done as automatically as possible. Data flows directly from the machines into the systems, providing fresh manufacturing data every minute. This allows them to make flexible decisions about what is happening on the shop floor and react to it.
Manufacturing digitalization often means changing processes and the way of working within a company. What do you think is the hardest part of these projects? Is it more the technological aspect, or managing the change inside the company?
It is definitely the process part. The technological side is well-mastered; it’s done in a few days or weeks. But then you struggle for months or even years with changing processes and the mindset of the workers. Those who create a strategy know what they want and why. They are then able to communicate all changes sensibly within the company. Those who don’t have a strategy start looking at numbers and don’t know what to do with them, which is often a process killer—they are unable to move things forward.
Who is your actual partner on the customer’s side who pushes you forward? And how important is collaboration between production, IT, and management in digitalization? Often, individual entities don’t understand each other…
Everything certainly flows down from the owner or management. If they have no interest, the saying goes that a fish rots from the head down. That applies here too. If the top executives of the company are interested, it usually works. It then also depends on the maturity, experience, and mindset of the entire company. When management can properly communicate things to production, projects are more successful. It rarely works the other way around. For us, all the levels you mentioned are essential; IT plays the smallest role for us. But there must be harmony between the owner/management and production. Production must report data and, in return, receive support for development and working with the systems.
Looking ahead a few years, what trends do you think will most influence industrial digitalization? Do you find that companies want to work with things like AI, needing to deploy AI projects, but when you look deeper, you find they actually need something completely different?
We don’t have AI elements in our systems yet; we are thinking more about where AI would fit. However, when we enter into projects, it is still too early for AI in the companies we visit. For us, it is still a bit far off; our projects are the predecessors. Again, we run into strategy – if implementing AI is at the end of it, they have to define everything they need beforehand: data, data logic, data consistency. Everything needs to be set up so that sometime in the future, AI has something to build upon.
And where do you think the greatest competitive advantage will arise for manufacturing companies that decide to go into a project (perhaps with you)?
It is definitely in grasping the data and achieving a greater degree of flexibility in production. If they had no data before us, they lacked crucial real-time information for decision-making. How to make production more efficient on a daily basis or see trends – the improvement comes, and I can prove it with real numbers. Companies gain flexibility in making decisions regarding the continuous improvement process, which then yields the benefits of improvement.
Sometimes it looks like digitalization is the right path for every manufacturing company. Are there any limits that a company should consider before digitalizing? Or is digitalization and your solution truly for everyone?
Personally, I am of the opinion that it is for everyone. The question is perhaps the size of the manufacturing company. But even if I have just one machine running, I need to know its condition, status, and productivity. At the end of the day, there is the product, pricing, efficiency… From a reasonable perspective, there is no limit to thinking about digitalization. However, we might run into cases where a company operates on a single shift with a few employees, where the foreman walks around and asks Joe how things are going… We encounter this all the time, but every machine deserves to have its condition known every minute.
