An Interesting Uncertainty-Based Combinatoric Problem in Spare Parts Forecasting: The FRED System

TL;DR

The paper discusses the complex uncertainty challenges in designing a knowledge-based spare parts forecasting system, FRED, highlighting the integration of multiple uncertainty paradigms and the combinatoric problems involved.

Contribution

It introduces the FRED system, addressing the integration of diverse uncertainty paradigms and the combinatoric challenges in real-world spare parts forecasting.

Findings

Uncertainty exists at multiple meta-levels in the system.

Combining different uncertainty paradigms is necessary.

The architecture faces combinatoric explosion issues.

Abstract

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.