Data processing: structural design – modeling – simulation – and em – Modeling by mathematical expression
Reexamination Certificate
1999-08-31
2003-07-08
Broda, Samuel (Department: 2123)
Data processing: structural design, modeling, simulation, and em
Modeling by mathematical expression
C705S007380, C705S002000, C700S096000, C700S099000
Reexamination Certificate
active
06591232
ABSTRACT:
BACKGROUND AND SUMMARY OF THE INVENTION
In current day society, there is usually more than one way to achieve an end result and, in many cases, a combination of ways to do so. Each way of achieving the end result has an associated amount of cost and risk.
For example, Any new aircraft program or any major modification program of an existing product is faced with the following important question: Which technology or combination of technologies (technology mix) should be used to meet the mission requirements at the lowest possible cost and risk? This question can be posed with any product focus in mind such as avionics and controls, structures, propulsion, etc.
The emergence of a great variety of manufacturing technologies over the last two decades has made finding the answer to the above question very complicated. Examples of these candidate technologies are high speed machining, resin transfer molding, automated fiber placement, pultrusion, automated tape layup, etc. In addition, the traditional technologies of sheet metal construction and composite hand layup are also viable candidates for many applications. Many of these technologies compete with each other for the same type of part and are expected to perform differently (in terms of component cost) depending on their respective level of maturity, production readiness, applicability, mission requirements, etc. Recent work by Metschan, S. L., Graesser, D. L., Mabson, G. E., Proctor, M. R., Tervo, D. K., and Ilcewicz, L. B., “
Manufacturing Data for COSTADE Analysis of Composite Fuselage Panels”, Fifth NASA Advanced Composites Technology Conference,
Seattle, Wash., pp. 93-126, Aug. 22-25, 1994;, and Mabson, G. E., Flyn, B. W., Ilcewicz, L. B., and Graesser, D. L., “
The Use of COSTADE in Developing Commercial Aircraft Fuselage Structures”, Proceedings of
35
th AIAA/ASME/ASCE/AHS/ASC SDM Conference,
Hilton Head, S.C., Apr. 18-24, 1994, which are incorporated herein by reference in their entirety, discuss the progress that has been made in including cost early in trade studies and linking the design process to optimizing software that, for a given technology, will determine the lowest cost and/or weight configuration. However, this work stops short of simultaneously trading multiple technologies over multiple families and accounting for the risk associated with the use of each candidate technology.
Selecting which technologies should be used, and to what extent, is traditionally based on previous experience with some of the technologies and a perception of the risk associated with applying these technologies. Risk is related to the degree of confidence of how consistently a technology will meet or exceed the cost goals of the program. A more accurate definition of risk for the purposes of this investigation will be given later. In what follows the term technology refers to a combination of manufacturing technology, material, and design concept.
Both previous experience and the subjective perception of risk tend to limit the options and significantly decrease the potential cost improvements that would be realized when a technology mix is implemented. An approach is needed that can quantify the cost associated with technologies even where little or no experience is available. This approach should also include a more accurate assessment of risk that is independent of subjective evaluations as much as possible. Finally, the approach should provide a means of selecting the optimum technology mix for an application.
SUMMARY OF THE INVENTION
The present invention presents the formulation for such an approach that will minimize the (recurring) cost associated with fabricating entire fuselages or significant portions thereof at a predetermined risk level. It is based on developing estimates of the cost variation of each candidate technology around its expected (mean) value that account for the production-readiness level of each technology. This variation is directly related to the uncertainty associated with choosing one technology over another or applying a combination of technologies at different parts of the structure in question. A portfolio optimization problem is then formulated and an algorithm proposed for selecting the technology mix that gives the lowest recurring cost given a pre-selected uncertainty level. By varying the uncertainty level, different optimum technology mixes can be obtained. From these the one that maximizes the cost savings with a low probability (e.g., 1%) of lower savings is selected as the overall optimum technology mix.
The incorporation of the cost as an objective function to be minimized during the design process has led to design configurations where the mission requirements (loads, stiffness, etc.) are met and at the same time the cost and/or weight are minimized. See, Zabinsky, Z. B, Tuttle, M. E., Graesser, D. L., Kim., G. I., Hatcher, D., Swanson, G. D., Ilcewicz, L. B., “
Multi
-
Parameter Optimization Tool for Low
-
Cost Commercial Fuselage Crown Designs”, First NASA Advanced Composite Technology Conference,
NASA-CP-3104, Seattle, Wash,, pp. 737-748, Oct. 29-Nov. 1, 1990; Metschan, S. L., Mabson, G. E., Swanson, G. D., Gessel, M. H., Humphrey, R. J., and Tervo, D. K., “
Integration of Advanced Composite Manufacturing Trials into a Design/Cost Database”, Fourth NASA Advanced Composite Technology Conference,
Salt Lake City, Utah, Jun. 7-11, 1993; Metschan et al., “
Manufacturing Data for COSTADE Analysis of Composite Fuselage Panels”,
supra; and Mabson et al.,“
The Use of COSTADE in Developing Commercial Aircraft Fuselage Structures”,
supra. However, in these and other similar studies, the optimization was limited to determining the geometry that would minimize the cost or weight once the manufacturing process, material, and design concept were selected. A vital step preceding this step is the selection of the technologies to be used and their corresponding percentages of application on a vehicle such as the fuselage of an aircraft.
Once the most promising technologies are selected from a list of candidate technologies, and their corresponding levels of application are determined so that cost and risk are minimized, detailed optimization on the component level, accounting for the actual applied loads, can be done using the approaches presented in prior art literature. However, the first step of optimum technology selection will improve the results significantly as the selection of technologies will not only rely on experience or company preferences but also on an optimization approach that will pinpoint which technologies and to what extent those technologies should be used for a particular application. The selection of the optimum technology mix not only helps steer research programs and technology investments, but also provides a reliable guideline of what level of cost will be incurred during production and what the associated risk will be.
While the examples provided herein focus on the optimum mix of manufacturing technologies for fabricating a fuselage structure of a helicopter, it is contemplated that the present invention and the teachings provided herein are directly applicable to other disciplines. For example, the present invention can be used for (1) selecting the appropriate mix of aircraft for attacking a particular target while minimizing aircraft losses; (2) selecting a mix of investments to achieve a desired return while minimizing cost and risk; or (3) selecting an appropriate series of directions for getting to a destination while minimizing expenses and time. These are just a few of the many distinct applications that the present invention can be applied to. Those skilled in the art of operational research would readily be able to apply the teachings herein to any of these or other applications.
REFERENCES:
patent: 5408663 (1995-04-01), Miller
patent: 5930762 (1999-07-01), Masch
patent: 6198980 (2001-03-01), Costanza
Timothy Gutowski, David Hoult, Greg Dillon, Stuart Muter, Eric Kim, Mawuli Tse, Ein-Teck Neoh, “Development of a Theoretical Cost Mosel for Advance
Bachman & LaPointe P.C.
Broda Samuel
Phan Thai
Sikorsky Aircraft Corporation
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