A conceptual model and prototype of an adaptive production control system

The rapidly increasing complexity of production automation has prompted considerable interest in the application of artificial intelligence (AI) to the various components, e.g., controllers, machines, workstations, cells, etc., that compose production systems. As the intelligence of these components increases, each component becomes capable of making decisions that affect the overall performance of the system. The integration and coordination of autonomous decision-making components are fundamental research issues in the design of intelligent production systems. A critical factor affecting the integration and coordination of autonomous decision-making components is the coordination structure. Coordination structure refers to the pattern of decision-making and communication among a set of autonomous decision-making components. Current intelligent production systems research focuses on centralized versus decentralized coordination structures. The centralized coordination structures most often advocated are based on a functional hierarchy. The decentralized coordination structures are modeled after an economic marketplace. Centralized and decentralized coordination structures represent opposite ends of the continuum of coordination structures. By focusing on opposite ends of the continuum, researchers ignore the myriad of coordination structures that lie between these extremes. This dissertation presents a conceptual model and prototype of an adaptive production control system capable of traversing the continuum between centralized and decentralized coordination structures.