I/O monitoring and AI infer obsolete controller logic, generating equivalent code for new industrial controllers with less manual rework.
A shared industrial IDE brokers parallel design input, preserves project consistency, and shortens automation integration and debugging cycles.
An edge device maps AI model outputs and industrial protocols to PLCs, automating data exchange while reducing custom coding and format errors.
By monitoring controller I/O states, this case generates functional design specs and equivalent code to speed legacy controller migration.
A collaboration management layer brokers parallel design inputs in an industrial IDE to keep automation projects consistent and efficient.
Centralized bot assignment, package delivery, and schedule control make RPA deployment across managed endpoints more flexible and scalable.
A generic machine tool model maps app requirements to each machine, enabling edge deployment across heterogeneous protocols without multiple app versions.
A dual-mode GUI uses image-based and process-flow editing to simplify semiconductor command scripts and reduce manual errors.
A generic machine tool model maps application requirements to each controller, enabling portable edge deployment across mixed protocols and configurations.