Constructing and Maintaining Detailed Production Plans: Investigations into the Development of K-B Factory Scheduling
To be useful in practice, a factory production schedule must reflect the influence of a large and conflicting set of requirements, objectives and preferences. Human schedulers are typically overburdened by the complexity of this task, and conventional computer-based scheduling systems consider only a small fraction of the relevent knowledge. This article describes research aimed at providing a framework in which all relevant scheduling knowledge can be given consideration during schedule generation and revision. Factory scheduling is cast as a complex constraint-directed activity, driven by a rich symbolic model of the factory environment in which various influencing factors are formalized as constraints. A variety of constraint-directed inference techniques are defined with respect to this model to provide a basis for intelligently compromising among conflicting concerns. Two knowledge-based factory scheduling systems that implement aspects of this approach are described.
Copyright © 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.