Autonomous Machines

Predictive maintenance

We use machine data to identify upcoming machine failures at an early stage in the process and to determine the ideal time for maintenance

Tailor-made measurement concepts

We support customers in the correct selection of additional sensors in order to detect errors as early as possible. These include vibration, ultrasound and sound emission sensors.

Detecting anomalies

Based on historical data, we learn the behaviour of processes, thereby allowing us to identify anomalies and alert machine operators.

Automated planning of maintenance

Our solutions predict how many process steps can be carried out before the machine needs to be serviced. Therefore, we can create the perfect maintenance plan for you.

Autonomous wet storage

A complete solution for the efficient and resource-saving operation of a wet storage facility. The product includes hardware and software and is designed for both greenfield and brownfield systems.

Wireless sensors

Optimal placement of wireless sensors (LoRa) enables us to monitor the condition of the wet store. Data is then sent to the cloud via a gateway.

Efficient control

We include weather data and use intelligent algorithms to efficiently control irrigation saving water and electricity.

Cloud platform

Intuitive software platform for monitoring and controlling the process remotely.

Plug&Play

RetroFit package for existing automation systems (I/O gateway) as a scalable solution, also for self-integration.

Process optimization

Our goal is to increase throughput while ensuring process stability and quality

Training on virtual simulation

We simulate your production process in a virtual environment and can thus easily find and test optimizations without interfering with your process.

Finding optimal process settings

Our solution tries thousands of varying modifications and other process adjustments using the virtual simulation until the optimal settings are found.

Dynamic systems

Our system increases your throughput, ensures stability and quality and reacts dynamically to process changes.

Press time optimization for RF press systems

Radio frequency presses are used in wood processing to harden glue lines in wood-wood connections. Products such as kitchen cabinets, door frames, panels or laminate beams are manufactured using this method.

Challenge

The use of radio frequency is only a means of obtaining heat. To ensure that the adhesive connection holds, the processes are often carried out longer than they actually have to be. Since this process step is very energy intensive, a lot of energy is wasted.

Solution

Using sensor data from the machine along with product information and quality measuring points, an intelligent solution was developed that determines the optimal pressing time. This is characterized by the highest quality with the shortest press time.

Result

By reducing the pressing time, the energy consumption could be reduced by 15-20% and the quality remained the same.

Empower Machines to Operate Autonomously and Efficiently