The technologies of Artificial Intelligence enable the application of many new techniques to address some of the more difficult unstructured problems that exist in various manufacturing domains. This dissertation explores the issue of how differing views of reality can be simultaneously represented and interpreted within one modelling environment. The domain of investigation is the determination of manufacturing strategy in a large global industrial firm. The focus of the research is on the reasonableness of arguments from descriptive models of the manufacturing enterprise. Dealing with differing views on reality simultaneously, involves consideration of which factors are reasonable premises to argue from, which factors should be ignored, what is the appropriate level of aggregation in the model and how should conflicting evidence be reconciled. The architecture described in this dissertation is based on applying alternative reasoning methods to available information and then looking at the attributes of the alternative conclusions that are reached. In this manner, diverse and likely inconsistent knowledge such as budgets, plans, expectations, causal models, correlational models and historical knowledge are integrated and interpreted within a planning system. In discussing the architecture, the dissertation describes a declarative representation language for constructing models of large scale industrial enterprises. It describes a useful set of reasoning operators that represent some of the typical approaches used by strategic planners. It describes the overall control architecture that applies reasoning operators, reconciliation operators and that maintains dependency between final hypotheses, intermediate hypotheses and the evidence on which they depend. It also describes the nature of self-awareness by the system and how explanation is generated. Finally, field tests using the modelling paradigm, the strengths and weaknesses of the architecture as well as open research issues are all discussed.
| Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:dissertations-7835 |
| Date | 01 January 1990 |
| Creators | Harhen, John G |
| Publisher | ScholarWorks@UMass Amherst |
| Source Sets | University of Massachusetts, Amherst |
| Language | English |
| Detected Language | English |
| Type | text |
| Source | Doctoral Dissertations Available from Proquest |
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