Abstract:
The rise of Industry 4.0 and related concepts, such as Cloud Manufacturing, has created
newrequirements for control systems, including machine tool control. A proposed solution
to meet these requirements is cloud-based control. Cloud-based control of machine tools
uses resources in the cloud to gain flexibility and computational power. It unlocks new
capabilities such as advanced trajectory planning, optimisation, interoperability, and
upgradability. The computational capabilities of conventional control are often static and
limited by its hardware, making upgrades difficult or otherwise very costly.
Researched cloud-based control solutions for machine tools are based on a centralised local
control that interfaces with the cloud. The local control handles the real-time machine
control, while the cloud enhances higher-level functions such as HMI and trajectory
planning. In contrast, this thesis proposes the application of IoT principles to machine
tool control. The individual sensors and actuators of the machine connect directly to
the cloud or each other through their own network-enabled controllers. The additional
expected advantages are lower entry barriers and even higher flexibility. It is not necessary
to acquire a complete local hardware or software control, and a change of connections or
information flow does not require rewiring but can be solved in software.
While the network connections introduce flexibility, their unreliability poses a challenge.
Delay, jitter and possible connection loss are factors that need to be considered by the
architecture. Different tiers of control loops are established depending on their real-time
requirements and variable coupling. Motion control loops remain as a unit, have their
respective control nodes and are synchronised through timestamped setpoints.
Mechanisms are devised to guarantee the system’s safety under adverse network connections.
The control monitors the network connection and initiates a coordinated emergency
slow or shutdown of the moving axes if necessary. The emergency shutdown follows the
originally planned path of the machine while maintaining sufficient braking limits and
stopping distance. Upon restoration of the network connection, the control can resume
operation.
Suitable hardware for the local control nodes was identified, and firmware with the
necessary functionality was written. A prototype consisting of a remote cloud-based
control and several local nodes was implemented.
The challenges identified during this research are the distribution of multidimensional
feedback loops under real-time constraints and the inherent limitations of message transfer.
Time synchronisation of high accuracy is crucial in achieving a low machining error of
the proposed control. Based on the observed network conditions and machining speeds it
was found that the control and architecture are suitable for entry-level machine tools and
retrofits.