Mixing expressiveness and efficiency in a manufacturing planner

The application of arti® cial intelligence planning techniques to real world problems is a very di cult task which usually implies overcoming expressiveness and e ciency handicaps. Expressiveness in order to cope with the great amount of knowledge involved in these problems and also to obtain results directly, or almost directly, applicable in the ® eld of study. E ciency to achieve a good course through the potentially enormous search spaces and, therefore, a satisfactory response capability. This work describes M a c h i n e , a manufacturing planning architecture which is able to obtain sequential control programs for manufacturing systems, the steps given to overcome these expressiveness and e ciency handicaps and how it is able to solve some real size problems.