A program for the control
of manufacturing systems (last update Dec-98)
One of the main activities in planning research carried out in the Approximate Reasoning and Artificial Intelligence Group of the University of Granada is the design of planning methods able to obtain sequential control programs for manufacturing systems.

The design of these programs for a manufacturing system is a difficult task which is traditionally carried out by engineers. We have developed MACHINE, a nonlinear planner with an automata-based representation of operators, which is able to obtain control sequences for manufacturing systems. These control sequences are an abstract representation of a sequential control program which may be easily translated into real programs expressed as GRAFCET charts or Petri nets. Now, our work consists in extending this planner in order to solve more complex problems, particularly, we are interested in including reaction to sensing information, adaptability or failure tolerance and finally in increasing the efficiency of the planner through knowledge acquisition techniques.