Please use this identifier to cite or link to this item: https://doi.org/10.1109/TASE.2004.829414
Title: Strategic sourcing and collaborative planning in internet-enabled supply chain networks producing multigeneration products
Authors: Gaonkar, R.S. 
Viswanadham, N. 
Keywords: Collaboration
Collaborative scheduling
Integrated supply chain management
Internet-enabled supply chains
Managing product families
Product introduction
Product rollovers
Supply chain planning
Supply chain scheduling
Issue Date: Jan-2005
Source: Gaonkar, R.S.,Viswanadham, N. (2005-01). Strategic sourcing and collaborative planning in internet-enabled supply chain networks producing multigeneration products. IEEE Transactions on Automation Science and Engineering 2 (1) : 54-66. ScholarBank@NUS Repository. https://doi.org/10.1109/TASE.2004.829414
Abstract: The design and planning of supply chain networks supporting production and distribution of multiple product generations overlapping with each other is of critical importance in the high-tech industry. In this paper, we address the strategic supply chain network design problem in rapidly changing industry segments, where the selection of partners such as component suppliers, contract manufacturers and logistics providers is done, based on the capabilities of the partners for supporting the strategic needs of the current and near future generations of a finished product. We develop a mixed integer-programming model for integrated planning and scheduling across the supply chain and show how such a model may be used for making decisions related to introduction and rollovers of finished products and components from one generation to another. We assume that all stakeholders in the supply chain collaborate and share information on their capacities, schedules and cost structures. Based on this information the model addresses the issue of partner selection and planning for optimal profit. The model was solved using optimization tools from ILOG. Managerial insights are obtained by performing a series of simulated experiments on the model developed. For example, we show that an expensive supplier possessing the ability to develop and supply components required across a number of generations, might be preferred against a cheaper supplier supplying components suitable for a specific generation of the product. In addition, we show how the supply chain network configuration changes over the lifecycle of the product, wherein cheaper overseas suppliers slowly replace responsive and expensive local suppliers as the product matures. We also develop a framework to quantify and compare the costs and benefits of pursuing alternative product introduction plans and deadlines. Such a framework might be employed to determine the optimal product introduction schedule. We show here that in some cases it might not be profitable to launch a product in the market after a certain period of time.
Source Title: IEEE Transactions on Automation Science and Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/61377
ISSN: 15455955
DOI: 10.1109/TASE.2004.829414
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