In this work we developed decision support frameworks that relied on the modeling of multidisciplinary integration to enable the selection of optimal product design alternative and to facilitate efficient chemical product design planning and execution. In recent years, the design of chemical products has received renewed and growing interest, as the industry transitions from a dominant bulk chemical product portfolio to one of high value-add specialty products that focus on product end-use properties. This industry shift results from the onset of global competitive pressures accompanied by intense market and consumer demand for improved product quality, lower product cost, shortened development cycle and greater product differentiation. Concurrently, the chemical manufacturers of commodity products are faced with pricing pressures and limited cost reduction options. The existence of these challenging market situations demand the adoption of rapid and efficient product design approaches that leverage specialized capabilities across disciplines within the chemical enterprise. The findings from a recent industry benchmark study, conducted as a part of this research, supported the motivation for this work. An assessment of current industry practices involving 15 chemical manufacturers revealed varying levels of organizational maturity as it relates to multidisciplinary and cross-functional leveraging of knowledge in product design undertaking. The chemical manufacturers were evaluated on current practices of integrating consumer preferences, product-process integration and practices of linking business decisions into the product design process. The investigation revealed the absence of formalized frameworks to integrate the critical resources necessary to support optimal product performance and design process execution. In this study, the set of decision support procedures formalize the interaction between product design and product portfolio decision making by integrating critical elements of both domains. Hence the methodologies incorporates structural framework to forge strategic alignment while optimizing domain interaction with an aim to minimize cost, reduce cycle time and determine optimal product design alternative. Embedded industry case studies illustrate the application of the proposed methodologies which utilize a hybrid approach, involving the application of structural frameworks for domain integration, along with Monte Carlo Simulation and algorithmic processing to optimize the product design planning and execution process.
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xii, 167 p. : ill.
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Ph.D.
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by Beverly Veronica Smith
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Marianthi G.
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Ioannis
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Stephen Lubiak
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Rutgers University
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Graduate School - New Brunswick
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2010
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2010
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xx
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Rutgers University Electronic Theses and Dissertations
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Graduate School - New Brunswick Electronic Theses and Dissertations
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doi:10.7282/T35X28P0
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ETD doctoral
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2010-10-01 16:47:40
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Rutgers University. Graduate School - New Brunswick
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