This paper presents the methods to move assembly variation analysis into early stages of aircraft development where critical partitioning, sourcing, and production decisions are often made for component parts that have not yet been designed. Our goal is to identify and develop variation prediction methods that can precede detailed geometric design and make estimates accurate enough to uncover major assembly risks. With this information in hand, design and/or manufacturing modifications can be made prior to major supplier and production commitments. In addition to estimation of the overall variation, the most significant contributors to assembly variation are also identified. In this paper, a generic framework for prediction of assembly variation has been developed. An efficient, top-down approach has been adopted. Instead of taking measurement everywhere, the variation analysis starts with airplane level requirements (e.g., load capabilities and orientation of horizontal/vertical stabilizers), and then assembly requirements (mainly geometric dimensioning and tolerancing callouts, quantifiable in quality control) are derived. Next the contributors to a particular assembly requirement are identified through data flow chain analysis. Finally, the major contributors are further characterized through a sensitivity study of metamodels or 3D variation analysis models. A case study of a vertical fin has been used to demonstrate the validity of the proposed framework. Multiple prediction methods have been studied and their applicability to variation analysis discussed. Simplified design simulation method and metamodel methods have been tested and the results are reported. Comparisons between methods have been made to demonstrate the flexibility of the analysis framework, as well as the utility of the prediction methods. The results of a demonstration test case study for vertical fin design were encouraging with modeling methods coming within 15% of deviation compared with the detailed design simulation.
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e-mail: zhaoz@research.ge.com
e-mail: bezdecny@research.ge.com
e-mail: leeb@research.ge.com
e-mail: wuy@research.ge.com
e-mail: robinsondm@research.ge.com
e-mail: lwbauer@comcast.net
e-mail: mark.slagle@boeing.com
e-mail: duke.coleman@boeing.com
e-mail: john.g.barnes@boeing.com
e-mail: stephen.a.walls@boeing.com
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September 2009
Research Papers
Prediction of Assembly Variation During Early Design
Zuozhi Zhao,
Zuozhi Zhao
Global Research Center,
e-mail: zhaoz@research.ge.com
General Electric Company
, 1 Research Circle, KW-D253E Niskayuna, NY 12309
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Michelle Bezdecny,
Michelle Bezdecny
Global Research Center,
e-mail: bezdecny@research.ge.com
General Electric Company
, 1 Research Circle, KW-D253E Niskayuna, NY 12309
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Byungwoo Lee,
Byungwoo Lee
Global Research Center,
e-mail: leeb@research.ge.com
General Electric Company
, 1 Research Circle, KW-D253E Niskayuna, NY 12309
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Yanyan Wu,
Yanyan Wu
Global Research Center,
e-mail: wuy@research.ge.com
General Electric Company
, 1 Research Circle, KW-D253E Niskayuna, NY 12309
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Dean Robinson,
Dean Robinson
Global Research Center,
e-mail: robinsondm@research.ge.com
General Electric Company
, 1 Research Circle, KW-D253E Niskayuna, NY 12309
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Lowell Bauer,
Lowell Bauer
Variation Risk Management, 787 Airplane & Services Integration,
e-mail: lwbauer@comcast.net
Boeing Company
, Building 40-87.3, Column 3A3-2.4, Everett, WA 98204
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Mark Slagle,
Mark Slagle
Variation Risk Management, 787 Airplane & Services Integration,
e-mail: mark.slagle@boeing.com
Boeing Company
, Building 40-87.3, Column 3A3-2.4, Everett, WA 98204
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Duke Coleman,
Duke Coleman
Variation Risk Management, 787 Airplane & Services Integration,
e-mail: duke.coleman@boeing.com
Boeing Company
, Building 40-87.3, Column 3A3-2.4, Everett, WA 98204
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John Barnes,
John Barnes
Variation Risk Management, 787 Airplane & Services Integration,
e-mail: john.g.barnes@boeing.com
Boeing Company
, Building 40-87.3, Column 3A3-2.4, Everett, WA 98204
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Steve Walls
Steve Walls
Variation Risk Management, 787 Airplane & Services Integration,
e-mail: stephen.a.walls@boeing.com
Boeing Company
, Building 40-87.3, Column 3A3-2.4, Everett, WA 98204
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Zuozhi Zhao
Global Research Center,
General Electric Company
, 1 Research Circle, KW-D253E Niskayuna, NY 12309e-mail: zhaoz@research.ge.com
Michelle Bezdecny
Global Research Center,
General Electric Company
, 1 Research Circle, KW-D253E Niskayuna, NY 12309e-mail: bezdecny@research.ge.com
Byungwoo Lee
Global Research Center,
General Electric Company
, 1 Research Circle, KW-D253E Niskayuna, NY 12309e-mail: leeb@research.ge.com
Yanyan Wu
Global Research Center,
General Electric Company
, 1 Research Circle, KW-D253E Niskayuna, NY 12309e-mail: wuy@research.ge.com
Dean Robinson
Global Research Center,
General Electric Company
, 1 Research Circle, KW-D253E Niskayuna, NY 12309e-mail: robinsondm@research.ge.com
Lowell Bauer
Variation Risk Management, 787 Airplane & Services Integration,
Boeing Company
, Building 40-87.3, Column 3A3-2.4, Everett, WA 98204e-mail: lwbauer@comcast.net
Mark Slagle
Variation Risk Management, 787 Airplane & Services Integration,
Boeing Company
, Building 40-87.3, Column 3A3-2.4, Everett, WA 98204e-mail: mark.slagle@boeing.com
Duke Coleman
Variation Risk Management, 787 Airplane & Services Integration,
Boeing Company
, Building 40-87.3, Column 3A3-2.4, Everett, WA 98204e-mail: duke.coleman@boeing.com
John Barnes
Variation Risk Management, 787 Airplane & Services Integration,
Boeing Company
, Building 40-87.3, Column 3A3-2.4, Everett, WA 98204e-mail: john.g.barnes@boeing.com
Steve Walls
Variation Risk Management, 787 Airplane & Services Integration,
Boeing Company
, Building 40-87.3, Column 3A3-2.4, Everett, WA 98204e-mail: stephen.a.walls@boeing.com
J. Comput. Inf. Sci. Eng. Sep 2009, 9(3): 031003 (11 pages)
Published Online: August 19, 2009
Article history
Received:
June 15, 2007
Revised:
March 6, 2009
Published:
August 19, 2009
Citation
Zhao, Z., Bezdecny, M., Lee, B., Wu, Y., Robinson, D., Bauer, L., Slagle, M., Coleman, D., Barnes, J., and Walls, S. (August 19, 2009). "Prediction of Assembly Variation During Early Design." ASME. J. Comput. Inf. Sci. Eng. September 2009; 9(3): 031003. https://doi.org/10.1115/1.3130795
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