Machine Operation App-Solutely Under Control

Machine operation has become a complex challenge for many companies. On the one hand, they are facing a workforce problem: Experienced specialists are often no longer able to properly transfer their extensive knowledge to a sufficient number of junior staff. Instead, more and more lateral entrants are arriving on the shop floor and have to be trained at short notice. At the same time, operating the systems and machines is becoming more and more complicated, even for experienced employees. This is not only because the machines have more and more features, but also because the requirements for efficiency and workpiece quality are increasing. 

Assistance systems can help to defuse this situation: Mobile applications on smartphones or tablets support the training phase and process control. They can be used to provide information on the machine, component or production process in a simplified and situational way.

App-supported process setup

When it comes to guiding the setup process on a milling machine, for example, the correct machine is first identified using a serial number or a QR code. The application then guides the user through the individual tasks step by step: loosening the milling head, chucking the tool, tightening the milling head again. Which tool or stock material is required for each step is displayed on the smartphone screen. Pictures or videos illustrate the explanations, if necessary with translations into various languages. 

But that is not all: Sophisticated sensors within the machines check whether all steps have been carried out correctly. For example, the chuck has sensors that check whether the workpiece has been tightened with the correct clamping force. This means that even beginners can quickly carry out the correct operations. Intelligent sensor technology can also support the determination of optimal process parameters – saving energy and material and achieving machining results of the highest quality.

»We are researching
how the machine can use sensors
to automatically detect
where the problem may be.«

In-situ monitoring saves time and cost

Even while a process is running, sensors in the systems continuously monitor various parameters such as pressures, temperatures and energy consumption. »Deviations from the ideal parameters indicate that something is going wrong in the process,« explains Philipp Lelidis, research scientist in the Production Machines and System Management department. Such indicators also point to where the problem lies. 

One use case is additive manufacturing, for example in metal 3D printing, which is mainly used in the aerospace and medical industries. Such processes often take several hours. If the employees only realize afterwards that there has been an error and the component is unusable, time and raw materials have been wasted.

»We are researching how the machine can use sensors to automatically detect where the problem may be, what impact this has on the component and what countermeasures we can take to still end up with a perfect component,« says Lelidis. This in-situ monitoring can also reduce the extent of required quality assurance in the end.

AI for pattern recognition and process optimization

Another example of the benefits of in-situ monitoring is laser machining. »A laser beam can cut, drill or remove fine layers from the surface of the material,« explains Luiz Guilherme De Souza Schweitzer, who leads the Process Technologies department in the Ultra- and High-Precision Technology division. Particularly precise work is carried out using laser pulses that are only a few femtoseconds long. When they hit a material, it sublimates – i.e. it changes from the solid to the gaseous state. The acoustic spectrum of this vapor can be measured using optical microphones.

There is an ideal acoustic spectrum for every process. Deviations from it indicate that errors have occurred. At present, it is still very difficult to read out these acoustic spectrums. Schweitzer is therefore working on training an artificial intelligence to recognize faulty patterns and carry out optimization procedures on the process. »We only have this expertise in-house at the moment, but testing with customers is already underway,« explains Schweitzer. 

Werk 4.0 increases resilience in production

What works on a small scale now should also function on a large scale in the future. As part of the Werk 4.0 project, Fraunhofer IPK is working on equipping not just individual systems, but an entire plant with digital assistance systems. This should also reduce the workload for employees as well as help to make manufacturing jobs more accessible and fill them despite the shortage of skilled workers.