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An advanced decision process for capacity expansion in manufacturing networks

By Nirupam Julka


Manufacturing companies develop multiple production sites for various reasons from cheaper labour to access to local markets. Expansion of capacity in such a manufacturing network is a complex decision and requires consideration of multiple factors. Traditionally, industrial decision makers attempt to minimise the cost of expansion and, usually as an afterthought, consider soft factors like manpower availability and logistics connectivity. This approach has gained acceptance as the research community has focused on developing better mathematical representations of the problem rather than investigate the larger decision process. A review of the literature revealed that all existing processes for multi-site capacity expansion decision fail in this way. Therefore, this research sets out to fulfil the needs of practitioners by developing a more complete process for the capacity expansion decision in multi-site manufacturing networks. The research programme consists of five parts. In the first part an extensive literature review is conducted to identify the state-of-the-art in capacity expansion decision processes. Then, in the second part, a representative process is formed and industrially tested. This generates the specifications for an advanced decision process which addresses the shortcomings of the present body of knowledge and is developed in the third part of the research. In the fourth part the advanced decision process is applied in an industrial setting to validate its effectiveness. Finally, in the fifth part the advanced decision process is refined and illustrated. The outcome of this research is an improved decision making capability. The advanced decision process has been both validated and appreciated by industrial practitioners. Specifically the contribution to knowledge is an advanced decision process for capacity expansion in multi-site manufacturing network

Publisher: Cranfield University
Year: 2008
OAI identifier:
Provided by: Cranfield CERES

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