A note on supply risk and inventory outsourcing

Author: Zhang, F.

Source: Production Planning and Control, Volume 17, Number 8, December 2006 , pp. 796-806(11)

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Abstract:

<p>To fully accommodate the correlations between semiconductor product demands and external information such as the end market trends or regional economy growth, a linear dynamic system is introduced in this paper to improve the forecasting performance in supply chain operations. In conjunction with the generic Gaussian noise assumptions, the proposed state-space model leads to an expectation-maximisation (EM) algorithm to estimate model parameters and predict production demands. When the dimension of external indicators is high, principal component analysis (PCA) is applied to reduce the model order and corresponding computational complexity without loss of substantial statistical information. Experimental study on some real electronic products demonstrates that this forecasting methodology produces more accurate predictions than other conventional approaches, which thereby helps improve the production planning and the quality of semiconductor supply chain management.</p>

Keywords: Linear dynamic system; state-space model; PCA; EM; supply chain

Document Type: Research article

DOI: http://dx.doi.org/10.1080/09537280600834387

Affiliations: 1: Fairchild Semiconductor, 82 Running Hill Road, M/S 35-2C, South Portland, ME 04106, USA

Publication date: 2006-12-01

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