An Interesting Uncertainty-Based Combinatoric Problem in Spare Parts Forecasting: The FRED System
This addresses architectural design challenges for knowledge-based systems in spare parts forecasting, an incremental contribution to a specific domain.
The paper tackles uncertainty problems in spare parts forecasting system design, where multiple uncertainty paradigms and meta-levels create combinatoric challenges that require novel architectural integration.
The domain of spare parts forecasting is examined, and is found to present unique uncertainty based problems in the architectural design of a knowledge-based system. A mixture of different uncertainty paradigms is required for the solution, with an intriguing combinatoric problem arising from an uncertain choice of inference engines. Thus, uncertainty in the system is manifested in two different meta-levels. The different uncertainty paradigms and meta-levels must be integrated into a functioning whole. FRED is an example of a difficult real-world domain to which no existing uncertainty approach is completely appropriate. This paper discusses the architecture of FRED, highlighting: the points of uncertainty and other interesting features of the domain, the specific implications of those features on the system design (including the combinatoric explosions), their current implementation & future plans,and other problems and issues with the architecture.