In today’s fast-paced manufacturing environment, modular robotics offer a
solution to address the challenges of short production life cycles and increasing
product variations. These adaptable systems can be quickly reconfigured to
accommodate new designs and production requirements, significantly reducing
downtime and enhancing flexibility.
When implementing modular robotics in manufacturing, safety considerations
are paramount. The interaction between different modules introduces complexities
that must be carefully managed to prevent accidents and ensure smooth
operations. Each module’s integration and coordination need thorough risk
assessment to identify potential hazards.
Information modeling is particularly valuable for managing the combinatory
aspects of modular robotics. By digitally representing each module and their
potential configurations, manufacturers can identify potential safety issues.
Consequently, this reduces the effort required for risk assessments.

Aims

The aim of this thesis is to conduct a comprehensive analysis of current safety
engineering procedures, information models, and standards for risk assessment
used in robotics. It will identify strengths and weaknesses in existing practices,
focusing on how they address the complexities of module interactions. An
additional aim is the design of a new safety information model tailored to
enhance the integration and safety of modular robotics systems. This model
will aim to streamline risk assessments and improve overall safety management.
Ultimately, the goal is to provide a robust framework that supports safer and
more efficient deployment of modular robotics in manufacturing environments.

Helpful previous knowledge

• Knowledge about metadata modelling
• Knowledge about robotic systems
• Lecture Cyber-Physical Production Systems