Automation meets artificial intelligence
"Strong together through an appreciative partnership, that is the goal"
The use of artificial intelligence offers numerous advantages for companies. Starting with the automated recognition of patterns through to the prediction of future developments. The technology makes it possible to process data in real time and thus make well-founded decisions. We spoke to ControlTech Engineering AG (CTE) and Learning Machines GmbH about this.
The interview with Dr. Boris Lau, Managing Director of Learning Machines GmbH in Freiburg (DE), and Dominic Brunner, Managing Director of ControlTech Engineering AG (CTE) in Liestal, shows the specific advantages of using artificial intelligence in the field of data management and how their partnership enables them to harness these advantages for themselves and their customers. While Dr. Boris Lau completed his doctorate in mobile robotics and artificial intelligence, Dominic Brunner studied mechanical engineering at ETH Zurich. Both entrepreneurs are fascinated by the topic of "big data".
Dr. Boris Lau and his company work with clients in the fields of data science, artificial intelligence and machine learning. Learning Machines develops individual solutions for customers from various industries. CTE has been active in the automation of production plants for 34 years. The focus is primarily on the pharmaceutical, chemical and biotech sectors, as well as food, beverages and flavors. Over the last ten years, the Industrial IT division has emerged as a new area due to the increasing integration of automation with OT operation technology. CTE is currently rounding off its offering with Data Management. In this interview, the two entrepreneurs look for overlaps and comparisons and explain the benefits of their partnership.
In the area of data management, CTE builds data warehouses for operational data storage and long-term archiving of data. In the process, experts develop interfaces between data storage and the various systems that make the data available. Learning Machines, on the other hand, are experts in gaining insights from such data.
Is this where the two companies intersect?
Dr. Boris Lau: The amount of data we need to gain insights from data is the great benefit of working with CTE. They specialize in collecting data, storing it with customers and then making it available, which makes it incredibly easy for us to start a project. Conversely, CTE can use the knowledge we have gained in automation.
Dominic Brunner: Absolutely - we can collect and structure data and help to ensure that it arrives correctly. Learning Machines, on the other hand, can interpret data perfectly. The specialists also add their specialist expertise. To give the data a context, you need someone who knows the business and the process in these systems, which is of course the customer. We have the automation expertise and know how the underlying system that generates the data is structured. Learning Machines helps us to interpret, simplify and provide the data. So it's a three-way relationship. The customer is at the center.
What do I get as a customer when I work with CTE and Learning Machines?
Dr. Boris Lau: An AI dashboard is one possible output. We don't create dashboards that visualize data, but AI-enabled dashboards that are equipped with AI. This makes it possible to generate insights that go beyond simply displaying the data. The aim is for the artificial intelligence to recognize deviations and raise an alarm to draw attention to them.
Dominic Brunner: I would describe it as follows: The customer has a system that is complex in itself, so it has many variables and parameters that influence each other. There are thousands of measuring points and therefore thousands of measurement data. We can collect this data well and Learning Machines can generate a picture from these data points. This allows us to see and understand the process. We can recognize when the process is running correctly and when it deviates. It is comparable to a survey where thousands of people are questioned. With the AI dashboard, Learning Machines is able to structure and categorize these answers in such a way that decisions can be made on this basis.
What makes the AI dashboard so special?
Dominic Brunner: Many experts in the data sector simply want to collect as much data as possible and have an algorithm interpret something from it. In my view, this only works with a very large amount of data if you know exactly what you are looking for and there is an expert who can recognize this from these thousands of data points. It's not so easy to manually compare all the data and understand the feedback and correlations between the data points. Modern technology, such as an AI dashboard from Learning Machines, can help to automate this process so that the artificial intelligence in the dashboard continuously learns for itself when something has been implemented correctly and when not.
This is the link to CTE's core competence. Does this mean that your focus remains on automation and industrial IT?
Dominic Brunner: The vision of an intelligent system that learns what it has done well in order to repeat or change it is the final stage of development. But we are already helping by using large amounts of data to show exactly where there is potential for improvement. This allows us to optimize the system in a targeted manner.
Dr. Boris Lau: Companies are very individual in their own processes. We respond to this. We as experts for data and CTE as experts for data collection and our customers, who understand their processes, form a team that efficiently finds an individual solution for the customer's situation.
That all sounds very exciting. What are the benefits of the partnership?
Dominic Brunner: Learning Machines and CTE speak the same language. A structured work plan, which is implemented step by step, creates a well-functioning interaction. In our partnership with Learning Machines, we focus on mutual expertise, easy communication and mutual understanding. This is how we work with our customers as a team. A team that represents everyone involved: someone who understands the business, someone who understands the system and automation and someone who takes on the role of data scientist.
Dr. Boris Lau: With our partnership, we want to support the local production sites to continue producing locally. A network of production, research and development promotes local jobs, even in times of crisis.
