Mathematical Sciences, Technology, and Economic Competitiveness (1991) / Chapter Skim
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3 THE PRODUCT CYCLE
3 THE PRODUCT CYCLE
Pages 32-54
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From page 32... ...
This chapter draws on case studies to consoler specific approaches, based on the mathematical sciences, to specific economic functions in specific industries. 3.l Economic Planning Decision makers involved in financial analysis generally rely on conventional capital budgeting techniques to quantify the dollar value of an investment.
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, OPT has been successfully applied to capital investment decisions involving new manufacturing technologies, new product introduction, and flexible plant capacity. More specifically, it has been used as a financial too} to evaluate developmental activities for new technologies that would require sequential capital investments.
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Recent extensions of the technique provide significant assistance in evaluating international projects by explicitly l;aking into account the impact of exchange rate volatility. Financial executives in industry have indicated the importance of using OPT to evaluate their most complex investment decisions.
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Cost accounting, which neglects the option value of investments, leads to systematic undervaluation of research and to short time horizons. Whether for these or other reasons, the results of the last decade show a consistently lower rate of investment in R&D by U.S.
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More importantly, based on computational fluid dynamics, far greater ranges of tests can now be carried out in wind tunnels. Manufacturers of commercial aircraft use computer modeling to obtain certificates of airworthiness for new aircraft designs more quickly than would otherwise be possible.
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Mathematical models are especially useful either when a proposed design is to be tested for feasibility or when the number of degrees of freedom is so large that guidance is necessary to reduce the range of design or control choices. In a semiconductor wafer fabrication facility, for instance, the manufacturing process may
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From page 39... ...
For example, it is well known that the manner in which orders are released through a multi-product manufacturing facility can have a major impact on the throughput of the system. Machine interference can occur when orders are improperly schecluTecI, which can significantly affect the productivity of the facility.
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system of simultaneous linear equations. Thus, significant effort has been expen{led in recent years to develop computational algorithms capable of solving these large systems of equations.
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A clisadvantage of simulation, relative to the more limited tools described above, is that building simulation models typically requires considerably more development effort on the part of the systems designer (in part because a simulation usually models the system at a higher level of detail)
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The focus of the collaboration was processing of silicon carbide whisker reinforced alumina matrix composites used as advanced cutting tools. The object of the experiment was to study the cause-and-effect relationships among processing conditions (whisker characteristics and amount, time, temperature, and pressure)
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The following physical problems have been studied systematically by mathematical scientists: building correct mathematical models from physical principles; understanding the mathematical properties of the models, such as existence, uniqueness, regularity, and continuous dependence of the solution upon data; developing cliscretization methods in a stable and accurate fashion; and producing computational algorithms, which take advantage of the emerging computer architectures for efficient solution. Exploration via seismic inverse techniques leads to an extremely difficult mathematical problem.
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Since primary and secondary recovery techniques leave up to 70 percent of the original oil in place, improved oil recovery methods are necessary so that we may use this major domestic source of energy. Large-scale reservoir simulation is '?
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Interface methods follow the fluid interfaces, and adaptive grid refinement methods resolve the local physics of the complex chemical and physical fluid interactions. The nonlinear fingering process must be understood in the context of reservoir heterogeneities.
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At the same time, the emphasis on collecting data and applying basic and standard statistical techniques was highly successful in improving quality and reducing costs. Statistically planned experiments were, in the main, developed within the context of agricultural experimentation.
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3.7 Manufacturing Process Control Continuous production control is vital in the metals, glass, and chemical industries, among others. Process control in these applications typically involves 20 to 200 control variables and 10 to 100 quality (response)
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The first goal requires the identification of quality variables specifically sensitive to particular steps in the process or particular pieces of equipment that may be drifting out of control. The second goal requires the development of a high-dimensional model, presumably nonlinear, that quantifies the effect of changes in the values of the control variables on the quality variables.
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the steps in the VEST fabrication process, statistically, in order to be able to monitor and adjust the quality of TCs as they are being produced, and to detect equipment malfunctions at; the end of a process step rather than at the end of the entire fabrication process. 3.S Sensor-Based Manufacturing Modern control theory has shown in the aerospace industry that dramatic improvements can be achieved by using all available sensors.
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From page 50... ...
However, they are also essential in the application of modern multivariate control strategies, which when given the measurements of a reasonable number of sensor variables and given a reasonable number of control parameters, can give significantly better control than that achievable with single variable controls. Through the use of computers and signal processing strategies, the mathematical models on which the coni;ro!
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Mathematical techniques of efficient experimentation and measurement process control are fundamental to establishing these elements. The round-robin experiment required a high-precision test specimen, which was developed by LIST.
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A procedure was developed by NIST statisticians to ensure measurement process control for the certification of each standard reference material (SRM) issued for sale to the IC industry.
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A new production planning process, designed with operations research techniques and statistical data analysis, was tested and implemented. In less than two years, inventories were reduced by $~15 million with neither a decrease in sales or customer service, nor an increase in other manufacturing costs.
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After the construction of this optimally designed facility, the actual operation gave rise to additional data in terms of revised probability measures in the simulation model, which allowed further simulations, to achieve improved performance. The economic leverage of these simulations is considerable, as a small investment in simulation can save many hundreds of thousands of dollars on a project of the size discussed above.
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