Assessing Risk of Innovation

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Today's manufacturing systems and equipment must perform at levels thought impossible a decade ago. Companies must push operations, quality, and efficiencies to unprecedented levels while holding down costs. In this new economy, companies must be concerned with market shares, equity growth, market saturation, and profit. U.S. manufacturing is no exception and is a prime example of businesses forced to adapt to constant and rapid changes in customer needs and product mixes, giving rise to the term ''Agile Manufacturing''. The survival and ultimate success of the American Manufacturing economy may depend upon its ability to create, innovate, and quickly assess the ... continued below

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Allgood, GO August 15, 2001.

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Today's manufacturing systems and equipment must perform at levels thought impossible a decade ago. Companies must push operations, quality, and efficiencies to unprecedented levels while holding down costs. In this new economy, companies must be concerned with market shares, equity growth, market saturation, and profit. U.S. manufacturing is no exception and is a prime example of businesses forced to adapt to constant and rapid changes in customer needs and product mixes, giving rise to the term ''Agile Manufacturing''. The survival and ultimate success of the American Manufacturing economy may depend upon its ability to create, innovate, and quickly assess the impact that new innovations will have on its business practices. Given the need for flexibility, companies need proven methods to predict and measure the impact that new technologies and strategies will have on overall plant performance from an enterprise perspective. The Value-Derivative Model provides a methodology and approach to assess such impacts in terms of energy savings, production increases, quality impacts, emission reduction, and maintenance and operating costs as they relate to enabling and emerging technologies. This is realized by calculating a set of first order sensitivity parameters obtained from expanding a Taylor Series about the system's operating point. These sensitivity parameters are invariant economic and operational indicators that quantify the impact of any proposed technology in terms of material throughput, efficiency, energy usage, environmental effects, and costs. These parameters also provide a mechanism to define metrics and performance measures that can be qualified in terms of real economic impact. Value-Derivative Analysis can be applied across all manufacturing and production segments of our economy and has found specific use in steel and textiles. Where economic models give the cost of conducting a business, Value-Derivative Analysis provides the cost to conduct business . Benefits derived from conducting a Value-Derivative Analysis include: Reduced operating, support and life-cycle costs through a better understanding of technology impacts; Energy and waste stream reduction impacts through integrated modeling; Identification of technologies that are cost-sensitive to infrastructure; Defensible technology selection; Identification of cross-cutting technologies; Ability to map technology needs onto functional requirements; Track technology and innovation impacts on the enterprise; and Determine true worth of technologies and total cost of ownership.

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  • Sensors Expo 2001, Philadelphia, PA (US), 10/01/2001--10/04/2001

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  • Report No.: P01-111599
  • Grant Number: AC05-00OR22725
  • Office of Scientific & Technical Information Report Number: 788685
  • Archival Resource Key: ark:/67531/metadc724430

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • August 15, 2001

Added to The UNT Digital Library

  • Sept. 29, 2015, 5:31 a.m.

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  • Jan. 15, 2016, 12:47 p.m.

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Allgood, GO. Assessing Risk of Innovation, article, August 15, 2001; Tennessee. (digital.library.unt.edu/ark:/67531/metadc724430/: accessed April 23, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.