Jan 4 2019
Large kitchen appliances and utensils are not easy to clean, a fact that individuals would know very well from their own homes. Intricate components are more the rule than the exception in the industry and pose significant difficulties for the design of cleaning systems.
Positioning full cone nozzles in a CAD environment. (Image credit: Fraunhofer IVV)
In the future, a simulation will be able to assist in such scenarios. At the Fraunhofer Institute for Process Engineering and Packaging IVV in Dresden, the Learning Factory for Industrial Cleaning Technologies will be inaugurated towards the end of 2019. This Learning Factory will allow companies to test the combination of different cleaning technologies.
Components are usually covered with cooling lubricants when they roll off the line. Before these components are subjected to additional processing, the lubricants have to be removed frequently. However, this is not quite easy in the case of complex components. The responsible engineer, depending on his or her experience, should be able to decide the position of the spray cleaning system’s nozzles. Is there an undercut on the component? Is there a drill hole? In complex test systems, the engineers normally check whether the nozzles attain the desired cleaning performance and whether they adapt and rebuild accordingly—a process that is both costly and time-intensive.
Setting up spray cleaning systems
Now, a new simulation software will make this task easier in the future. The software was created by scientists from the Fraunhofer Institute for Process Engineering and Packaging IVV in Dresden along with partners Advitec Informatik GmbH and Innovations- und Simulationsservice Festenberg in the SIMKOR project, sponsored by the German Federal Ministry of Education and Research (BMBF).
The software delivers results for spatially resolved cleaning performance in just a few minutes, even for complex components.
Siegfried Beckmann, Research Fellow, Fraunhofer IVV
Rather than depending on experience alone, the engineer selects and positions the nozzles after loading the CAD data of the object to be cleaned into the software. In a pre-optimization step, the engineer can visualize in real time which parts the cleaning agent is able to reach directly and which parts it does not. After choosing an optimized position for the nozzles in this manner, the engineer begins the simulation. This provides even more comprehensive results, like the time-resolved and spatial distribution of the amount of the cleaning agent used and a simulation of the effectiveness of theoretical cleaning.
“Color coding indicates where the cleaning is more effective and where less. This allows users to realistically appraise problem areas independently of the type of soiling or surface quality,” Beckmann explained.
In order to produce the simulation tool, the investigators at Fraunhofer IVV performed numerous cleaning experiments with typical (that is, average) levels of soiling. They examined the cleaning results for various jet angles and nozzle positions.
We treated the nozzles as the cause and the events on the surface as the effect. We deliberately bracketed out everything in between, as these processes were far too complex for the simulation. So we chose a statistical simulation approach.
Siegfried Beckmann, Research Fellow, Fraunhofer IVV
From this data, the partners subsequently produced the matching mathematical models for the simulation. The initial test version has already been completed; the partners will launch the simulation software into the market in spring 2019. In the coming days, the simulation may also have the potential to specify the optimum positions of nozzles or propose the improved cleaning paths to increase the resource as well as energy efficiency of the cleaning procedure—that is the ultimate vision.
Learning Factory for Industrial Cleaning Technologies
Which cleaning process is optimal for a particular component? Does the chosen cleaning process achieve the required result? It is often difficult to answer these questions for cleaning technology users. This particularly applies to small and medium-sized enterprises, of which there are several in Saxony. In addition, the Fraunhofer IVV team has the right solution for these SMEs: the Learning Factory.
There we combine established water-based techniques—i.e. spraying, immersion cleaning, ultrasound and the cleaning of closed pipeline and tank systems—with newer methods such as atmospheric-pressure plasma, dry steam and CO2 and laser cleaning. Together with the customer, we begin by devising a solution for the particular application and then we test it in the Learning Factory.
Markus Windisch, Team Leader, Industrial Component Cleaning, Fraunhofer IVV
To sum up, the Learning Factory is a platform that allows companies to try out a variety of cleaning methods—and in particular varied combinations thereof—in a protected environment. After the companies locate the optimum cleaning solution, they can retrofit accordingly and provide their workers appropriate training in the Learning Factory much before commissioning.
“We deliberately used commercially available devices and hardware, so that we could offer practical solutions,” stated Windisch.
Moreover, the investigators also consider digitalization and Industrie 4.0 in the Learning Factory. For instance, they incorporated a system solution that is capable of recording the process data—regardless of whether they are entered manually by the operator or come from the machines themselves. In the majority of factories, putting up sticky notes with instructions all over the machine is a common practice. Now, workers can directly enter their comments in the system with the help of a tablet computer and share them with their coworkers in this manner and even with those working at other plants.
Some of the methods have already been implemented, and initial inquiries from customers have also started to come in. Nonetheless, it will take some more time before the combination of different cleaning methods and the cleaning of intricate components are tested—that calls for a second robot system.
However, it should be ready towards the end of 2019. At that phase, the Learning Factory will also cover skills training for employees of customers. The following topics will be addressed: In what way the management of a quality-controlled cleaning process varies from that of a time-controlled cleaning process? On March 14th, 2019, a project workshop will be hosted in association with the Saxony Economic Development Corporation (WFS)—an industry event dedicated to cleaning quality.