Using an Expert System to Monitor an Automatic Stock Control System

Abstract

The theory of the control of stock is well understood, and a large number of firms use automatic stock control and ordering techniques as a major part of their inventory control systems. However, the effectiveness of such automatic stock control systems depends on the correct selection of system parameters for each item in the inventory and on the accurate reporting of information. It is not unusual for errors to be made in both the selection of parameters and the entry of data, and regular failures of either can cause severe problems in stock control. It is generally difficult for a human stock controller to discover errors quickly because of the large number of items that is usually found in a company inventory. This paper describes the use of an expert system to examine stock records and diagnose anomalies in the data provided or parameters applied to individual items in a stock control system. The expert system ‘reasons’ from symptoms such as reports from the forecasting system or high stock levels, to defects in the stock model used or data-collection processes, and from there to possible remedial action. Results are presented for runs of the expert system on a simulated stock control system.

Keywords:

• Artificial Intelligence
• Expert Systems
• Stock Control
• System Monitoring