Robotics will bring about the greatest change. Artificial intelligence is closely linked to it, because in many applications modern robotics only works with machine vision and AI. But it would be too narrow to speak about robotics alone. We must pay equal attention to the core technologies: washing, water extraction, drying and finishing. Productivity, energy efficiency and reliability will continue to improve in all of these areas.

Many people talk about the fully automated laundry. It is an important vision. But, ultimately, what matters to the customer is whether an installation runs reliably, achieves a higher net output with fewer employees, processes textiles to the required quality standard and saves energy at the same time.

For us, performance means much more than machine speed. A machine may have a high peak output on paper. But it is only truly productive, if it runs reliably in day-to-day operation, causes few disruptions, works smoothly with the upstream and downstream processes, and delivers the required quality.

Performance therefore includes several dimensions: productivity, output, quality and availability. Productivity may mean, for example, that a laundry can achieve with two employees what previously required four persons. It also includes careful textile handling and the technical quality of the machine itself. If an installation is frequently at a standstill, even the highest theoretical output is of little value.

I agree with that. Many software solutions are already today ready for use. With our Smart Flow system for example, we control and visualise

processes in laundries, including facilities that are not yet fully automated. Employees can see, for example, what type of laundry is coming out of the dryer, how it needs to be sorted further and which orders are contained in which laundry cart. Tickets, screens and scanners ensure that the relevant information remains available throughout the entire process.

Smart View, in turn, connects the machines and collects operational data. This allows a laundry to identify where disruptions occur, where waiting times arise and where performance is not yet optimal. The aim is to align people and processes more effectively. One employee may be particularly effective when feeding towels, while another may be better deployed with bed linen or in the soil-sort area.

Exactly. Without transparency and a well-organised material flow, even the best automation will not reach its full potential. Data shows where laundry is waiting, which machine is not being supplied optimally or why a line is not achieving its expected net output. That is the basis for making the right investment decisions.

Robotics also requires reliable information about the textile: What is in front of the machine? What size is it? Which customer or order does it belong to? Where must it go next? Software, sensors, machine vision and mechanical systems all have to work together.

Machine vision is particularly important. Sorting is one of the major challenges in every laundry. People can immediately recognise whether an item is a sheet, a duvet cover or a towel; whether it is white, green or blue; and what size it is. Replicating that capability technically is demanding.

That is why we are working with automated soil-sort systems based on optical recognition. This also works without RFID. RFID is very helpful for the precise identification of textiles, but many laundries do not yet use chipped textiles throughout their operations. We therefore need systems that can recognise individual items optically.

AI can learn to assign characteristic features. For example, a coloured identification thread in a hem may indicate that an item is a king-size sheet. The system can then route that textile to the appropriate sorting destination.

No. Recognition is equally important in the clean-laundry area. When laundry leaves the ironer, camera technology can determine what type of item it is. The system can distinguish, for example, between a king-size and a single duvet cover and place them on the appropriate stackers. At the same time, machine vision can contribute to quality control.

AI will therefore not be limited to the start of the process. It will run through the entire laundry operation: from sorting and process control to quality assessment and energy-optimised machine control.

One example is our dryer technology with the “Eco to Power” concept. It is an intelligent control loop that dries laundry close to its saturation limit. The system aims to determine as precisely as possible when a batch of laundry is actually dry. The objective is to achieve short drying times while using as little energy as necessary.

Towards the end of the process, the burner flame is almost switched off. Energy is therefore not supplied as a fixed standard amount, but only to the extent needed. We have been using intelligent control approaches of this kind for many years. In the future, artificial intelligence and self-learning systems will play an even greater role in machine technology as well.

That depends on how you define “fully automated”. If it means that unsorted laundry enters at one end and emerges fully folded at the other without any human intervention anywhere in the process, then there are still challenges to overcome. Today, we can already realise highly automated laundries. However, human input will remain necessary in certain areas for the time being.

We have progressed far with terry goods. Soiled laundry can be sorted automatically, and in hotel laundries the terry-goods area can be automated to a large extent. Flatwork is more difficult: sheets, duvet covers and pillowcases are large, flexible and often difficult to grip reliably. Separating these items from a batch, picking them up correctly, spreading them out and feeding them automatically into a feeding machine is technically very complex.

The two are closely connected. Many things can be developed technically. But a solution must also work reliably and be economically viable. Highly complex robotics for bed linen can become very expensive, so the return on investment must remain justifiable for the operator.

However, labour shortages will change that calculation. In some countries, laundries already struggle to find employees. In those markets, they sometimes have little choice but to invest in automation and robotics. In markets with lower labour costs or sufficient staff, the same investment may pay back much later.

We look at this in three stages. The first is energy-efficient machinery. Before an operation considers photovoltaics, hydrogen or other primary energy sources, it should ensure that its washing, drying and finishing technology is operating as efficiently as possible.

The second stage is the process itself. If an ironer is running for ten hours but laundry is only being fed into it for six hours, then energy is being consumed for four hours without corresponding value creation. The same applies to washing systems, dryers or folding machines running empty. This is why process control is also a sustainability issue.

The third stage is primary energy supply: heat pumps, hydrogen, renewable electricity or other solutions. Much depends on regional conditions. As a machinery manufacturer, we can advise customers and take the necessary interfaces into account. But energy generation and heat supply are specialist fields in their own right.

From our perspective, the sequence should be clear: first make the machinery efficient, then optimise the processes consistently, and only then address the question of which primary energy source should supply the operation. Otherwise, there is a risk of connecting a new energy source to an inefficient process.

First, the basic technology must be right. A productive, energy-efficient machinery park and well-coordinated processes are the foundation. Beyond that, priorities depend strongly on the market in question.

In regions where laundries are still building up or modernising their technical capabilities, modern core equipment, reliable system integration and improved energy efficiency are often the main priorities. This may apply, for example, to parts of South America or Southeast Asia. There, the next major step is often to establish a continuous, productive and stable process in the first place.

The situation is different in established markets. Energy efficiency and sustainability remain important, but the most immediate economic pressure often comes from staffing. Rising labour costs and a shortage of workers mean that automation, robotics and digital process control are becoming even more central.

Absolutely. A laundry installation is not bought for one or two years. The investment decision may be made within a few months, but the customer will live with that decision for 15 years or more. Throughout that period, the installation must operate reliably in one-, two- or three-shift production.

As systems become more complex, long-term support becomes increasingly important. In the past, people often spoke of after-sales service. That is no longer enough. Customers need spare parts, maintenance, competent technicians, digital support and a supplier that accompanies the installation throughout its operating life. Availability is a key economic factor for every laundry. A production machine that is standing still does not generate revenue.

We are continuing to expand our worldwide service organisation. This applies not only to Germany and Europe. In many markets, we work with experienced and well-trained partners, establish regional service hubs and aim to develop new markets with a viable service structure from the outset.

This is particularly important in international expansion. Selling a machine is only the first step. What matters is that it still operates reliably years later and that the customer receives prompt support when needed. Service, local technical expertise and a long-term approach to customer support will therefore become just as important as the next innovation in robotics or artificial intelligence.