In addition to stabilizing feedback control, safe and economic operation of industrial process plants requires discrete-event type logic control, for example automatic control sequences, interlocking and protections. A lot of complex routine reasoning is involved in the design and verification and validation of such automatics. Similar reasoning is required in action planning and fault diagnosis during plant operation.
Much of the required reasoning is so straightforward that it could be accomplished by a computer if only there were plant models which allow versatile mechanised problem solving. Such plant models and related inference algorithms are the main subject of this report.