This paper describes the principles of the advanced programming techniques often dubbed Artificial Intelligence involved in decision making as may be of some value in matters related to production engineering. Automated decision making in the context of production can adopt many aspects. At the most obvious level, a robot may have to plan a sequence of actions on the basis of signals obtained from changing conditions in its environment. These signals may, indeed, be quite complex, for example the input of visual information from a television camera.
At another level, automated planning may be required to schedule the entire work cycle of a plant that includes many robots as well as other types of automated machinery. The often-quoted dark factory is an example of this, where not only some of the operations (such as welding) are done by robots, but also the transport of part-completed assemblies is automatically scheduled as a set of actions for autonomic transporters and cranes. It is common practice for this activity to be preprogrammed to the greatest detail. Automated decision making is aimed at adding flexibility to the process so that it can absolve the system designer from having to forsee every eventuality at the design stage.
Frequent reference is made in this context to artificial intelligence (AI), knowledge-based and expert systems. Although these topics are more readily associated with computer science, it is the automated factory, in general, and the robot, in particular, that will benefit from success in these fields. In this part of the paper we try to sharpen up this perspective, while in part II we aim to discuss the history of artificial intelligence in this context. In part III we discuss the industrial prospects for the field.