Multi-sensor system for environmental detection

RESEARCH PROJECT

LocSens

Challenges

  • Cleaning of production areas hitherto carried out manually
  • Quality criteria assessed subjectively by personnel
  • Reproducible cleaning processes not possible
  • No inline data acquisition of the degree of contamination
  • Adverse working conditions

 

Research results

  • Innovative service robots for automated cleaning
  • Multi-sensor system for environmental detection
  • Customized cleaning of objects and surfaces with complex geometry
  • Individual planning of travel paths and cleaning times depending on the degree of contamination

 

Benefits

  • Reproducibility and product safety due to automated cleaning
  • Support for cleaning personnel
  • Efficiency increase due to automated and parallel cleaning when using several cleaning robots
  • Continuous logging and documenting of the cleaning

Manual cleaning - time-consuming and not reproducible

 

The cleaning of production plants and their surroundings is often still performed manually in the food industry. Open production lines in particular, for example those used for meat processing which require almost all surfaces to be cleaned, need a lot of daily cleaning work in order to maintain the plants and production areas in a hygienic state. Besides the often adverse working conditions, the work of the cleaning personnel is also a potential source of error and represents a risk to hygiene and consumer protection. Up until now there has been a lack of suitable technologies for the automated and customized cleaning of complex production areas. One main reason for this has been the lack of sensor systems to at least partially replace human senses.

 

Intelligent, autonomous robots for effective cleaning processes

 

The objective of the LocSens project is to use automation to enhance product safety. Innovative cleaning technology and location sensor concepts are being combined in a service robot.

The contamination sensor developed by the Fraunhofer IVV Dresden uses fluorescence technology to detect contamination on plant surfaces and adapts the cleaning program to the degree of contamination. The robot is equipped with a telescopic arm and motorized jet cleaner to facilitate customized cleaning. The telescopic arm can be moved around all three rotational axes and can accurately access all contaminated surfaces.

For position detection the robot uses radar sensors combined with ultrawide band probes that even function under adverse cleaning conditions. In addition, the contamination sensor helps detect its own position using visual odometry. All data are brought together in a software cockpit and linked to a digital twin of the whole production plant, enabling the entire cleaning process to be simulated.


The self-propelled robot platform can be employed for mobile use throughout production areas. The only physical interface to the robot is the feed hose for the cleaning medium.

 

Hygienic cleaning of your plants and production areas

 

The cleaning system being developed by the LocSens project facilitates the cleaning of production areas where many machines and their surroundings need to be cleaned every day. This reduces the workload and stress of your employees and guarantees reproducible and efficient cleaning processes.

Risks to hygiene are minimized and product and process safety are significantly enhanced.

Do you have any questions about the cleaning of your production plants or would you like further information about the LocSens project? Then please get in touch with us!

 

Further Project Information

 

Project Duration until December 31, 2021
Project partners

indurad GmbH

Fraunhofer IOSB, Institutsteil AST

Innovations- und Simulationsservice Festenberg

ADVITEC Informatik GmbH

Hohe Tanne GmbH

Project advisory committee:

CITTI Handelsgesellschaft mbH & Co. KG

Tönnies Holding ApS & Co. KG

 

Additional Information

Production under hygienic conditions

Services we offer in the area of cleaning, sterilization, and production under hygienic conditions: