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The concept of learning has invariably been related to a classroom environment and/or industrial seminars, workshops, etc. The recent development in Artificial Intelligence, particularly in Neural Network applications offer interesting opportunities in developing continuous learning mechanisms for industrial applications in specific sectors. This paper gives information about neural models and an application example elucidating how a learning system can be developed for determining and forecasting parts quantities in a supply chain. If a continuous system can reliably predict numbers of parts required at the right time and at the right place, then the entire production schedule throughout the entire supply chain and within each organisation within it can be planned. All information flow routes and material flow paths can be optimised. The possibilities are very promising. The challenge, however, is as to how these learning systems can be validated and used with Computerised Enterprise Resource Planning (CERP) packages already used in industry