|dc.description.abstract||Caused by a rising mass customisation and the high variety of equipment versions, the
exibility of manufacturing systems in car productions has to be increased. In addition to
exible handling of production load changes or hardware breakdowns that are established
research areas in literature, this thesis presents a skill-based recon guration mechanism
for industrial mobile robots to enhance functional recon gurability.
The proposed holonic multi-agent system is able to react to functional process changes
while missing functionalities are created by self-organisation. Applied to a mobile commissioning
system that is provided by AUDI AG, the suggested mechanism is validated
in a real-world environment including the on-line veri cation of the recon gured robot
functionality in a Validity Check.
The present thesis includes an original contribution in three aspects: First, a recon -
guration mechanism is presented that reacts in a self-organised way to functional process
changes. The application layer of a hardware system converts a semantic description into
functional requirements for a new robot skill. The result of this mechanism is the on-line
integration of a new functionality into the running process.
Second, the proposed system allows maintaining the productivity of the running process
exibly changing the robot hardware through provision of a hardware-abstraction
layer. An encapsulated Recon guration Holon dynamically includes the actual con guration
each time a recon guration is started. This allows reacting to changed environment
settings. As the resulting agent that contains the new functionality, is identical in shape
and behaviour to the existing skills, its integration into the running process is conducted
without a considerable loss of productivity.
Third, the suggested mechanism is composed of a novel agent design that allows implementing
self-organisation during the encapsulated recon guration and dependability
for standard process executions. The selective assignment of behaviour-based and cognitive
agents is the basis for the
exibility and e ectiveness of the proposed recon guration