Interview with Dr. Roman Hänggi

I recently had the pleasure of interviewing Dr. Roman Hänggi, Professor of Production Management at Hochschule für Technik Rapperswil (HSR), a leading Swiss university of applied science.  Dr. Hänggi lectures extensively on industrial automation and digitization at HSR, and is also a leading voice for collaboration among university, industry, and technology stakeholders. Given his unique blend of professional and academic experiences, I asked Dr. Hänggi if he would share his thoughts on digital industrial transformation. Our interview dialog is provided below.

Please tell readers about your background in industry and academia.

Dr. Hänggi: After my studies at Swiss Federal Institute of Technology (ETH) and University of St. Gallen (HSG), I have worked for nearly 25 years in international industrial companies including Hilti Group, Bosch Packaging Technologies, and Leica Geosystems. I have lead companies and executed digital transformation processes. As an industrial practitioner, my topics of focus included lean management, setting up new factories, service management, and implementation of digital technologies to drive productivity and new business models.

Throughout my professional career, I have worked closely with different universities on research projects as well as educational programs. When I was presented with the opportunity to create a new department of production management with the focus on Industrie 4.0 at HSR, I decided to change my career and give back some of my learning to the students.

Tell us about the program you are helping to create at HSR.  What are your goals and priorities?

Dr. Hänggi: It all starts with standard production methodologies, process management, and lean manufacturing. Based on these fundamentals we have created two specific modules on digitization. One course is focusing on on data management – from design to production – and one on service. The newest add-on module is our Smart Factory course, in which students learn how to connect machines to a data platform, including the relevant programming and interface techniques. In addition, we are deepening the knowledge of specific machine learning methods for the smart factory.

Our research is centered around the latest production technologies in all relevant areas and materials. In recent years, we have had an additional focus on automation and robotics. Therefore, our lectures and research are based on many physical machines and all relevant production processes – from plastic molding, to metal CNC machines, to a wide variety of industrial robots. Right now, we are bringing the machines to a new 5000m2 production facility, which is currently under construction. In this new production environment, our students will experience a smart manufacturing set-up by connecting the different machines together. Learning from data will be a key topic in our new facility.

Discuss the role of data, analytics and AI in the factory of the future.

Dr. Hänggi: The cost pressure while sustaining high quality levels in manufacturing will continue. The volatility in our world today will further increase demand for highest flexibility in any manufacturing processes, but also in our global manufacturing network. Digitalization will be a key requirement for addressing these needs.

Digitalization in manufacturing has many elements. The base for many improvement initiatives in the factory is learning from data. Fact based and fast decisions are crucial for the success of the factory of the future. Predictive maintenance of production machines is a key use case. The benefit of this relevant use case is to minimize downtime. This will drive productivity to a new level.

What benefits can manufacturers achieve by digitizing their operations, and how should they begin the journey?

Dr. Hänggi: First of all, you need to invest and focus on the topic before you achieve gains. This is important to understand. Because of financial limitations you need to prioritize relevant use cases that will bring early, measurable benefits. If you focus digital initiatives on the most important use cases and execute a well-orchestrated plan, you will see major cost improvements as well as flexibility gains from your initial investments. It is fascinating what you can learn if you really understand your processes, manufacturing technologies, and data. A fast payback is given. These learnings will then generate massive improvements.

My best advice is to start the journey today – do not wait for others to blaze the path because every industrial company is different. Find a relevant use case that brings your company forward on two avenues – getting a financial benefit and gaining proficiency in learning from your data. This journey will take years and you do not know everything right now. But you need to start. These projects will challenge your existing infrastructure, IT systems, and organizational set up. Embrace the need to change so you can become a data-driven company.

How can small and medium-sized companies, with limited IT resources, compete in a data-driven future?

Dr. Hänggi: Small and medium-sized companies actually have a great advantage. Fast decision making and limited number of departmental silos are fundamental requisites to drive the digital transformation. To cope with limited IT resources, research shows that partnerships along the value chain will be crucial. This is true for small and medium-sized companies, but also for larger companies. You really do not need to do everything by yourself.

What new data and technology skills must be created in manufacturing companies in the coming decade?

Dr. Hänggi: Before we talk technological skills, you will need to have competence managing your partner network. This is something you need to do yourself. This also requires news skills with many digitalization technologies – not in all depth, but you need to understand what is possible and how to implement the different technologies in your company. Besides these management skills, knowledge of data management, programming, and data analytics will be important for any company. The required depth varies from company to company. Small companies will not have the power to program specific solutions from scratch. So use the latest platforms to gain speed, without needing to master all technical details.

How is HSR collaborating with industrial companies and technology providers to build the competencies needed for digital factories?

Dr. Hänggi: We are a university of applied science. Our Bachelor and Master programs are focused on implementation and getting results. We are currently working on two relevant machine learning research programs with different manufacturing companies in Germany and Switzerland, as well as the University of St. Gallen (HSG).

In our research we are continuously partnering with industrial and technology companies, such as Siemens and Edge2Web. These different research initiatives give lots of feedback and direction in regards to the smart factory, to us as well as the different industrial and technology companies.

How are your students gaining hands-on experience in industrial data collection, analysis, and visualization?

Dr. Hänggi: We believe strongly in three elements in education: theoretical understanding, personal experience through exercise, and implementation in a real context. These beliefs drive our plans. We are designing real practical exercises where the students find a solution and implement it with existing tools and technologies, such as Siemens Mindsphere or Edge2Web low-code software. In addition, our students execute project work, bachelor and master theses together with industrial companies to solve real problems. Right now we have many student projects in companies focusing on the topic of “learning from data in manufacturing”.

You recently chaired a conference of university researchers and industry leaders. Please provide a few highlights of that conference.

Dr. Hänggi: Our strength is the close connection and interaction with many industrial companies. Every year we organize different venues to bring academia and companies together. At our yearly conference on “Digitalization of Industrial Companies” we have been very much focused on getting results through digitalization. Different companies as well as researchers present real implemented use cases. The key insights of the conference can be summarized in two themes. First, “Learning from Data” brings a lot of benefit in regards to gaining efficiency and reducing cost. Second, “Digitization of Manufacturing is a Journey” is a theme you will need to continuously drive as an industrial company. It is not a one-year project. You need to learn and implement step-by-step to drive continuous benefits.