CEA'10 Proceedings of the 4th WSEAS international conference on Computer engineering and applications
Resiliency and vulnerability in short life cycle products' supply chains: a system dynamics model
WSEAS TRANSACTIONS on SYSTEMS
Using system dynamics for short life cycle supply chains evaluation
Proceedings of the Winter Simulation Conference
Towards automated extraction of expert system rules from sales data for the semiconductor market
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Computational Intelligence - Volume Part II
Characterization and analysis of sales data for the semiconductor market: An expert system approach
Expert Systems with Applications: An International Journal
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Over the past decade, the high-tech industry has been rapidly innovating technology and introducing new products. Firms have moved from vertically integrated operations to horizontally integrated operations that include contract manufacturers. In September 2002, Agere Systems recognized that it needed new tools for managing the capacity in its increasingly complex, global supply chain. Agere and the Center for Value Chain Research at Lehigh University formed a team to develop new methods for characterizing the demands for short life-cycle technology products. The team developed a leading-indicator engine that identifies products that provide advanced warning of demand changes for a group of products. For a data set including 3,500 semiconductor products, the analysis identified leading indicators that predicted the demand pattern of the product group one to seven months ahead of time with correlation values ranging from 0.51 to 0.95. The leading-indicator concept provides a new perspective on demand forecasting and can be extended to other corporate planning functions, such as financial forecasting and inventory forecasting.