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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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The process of manufacturability evaluation is composed of a series of generic tasks. Though domain knowledge is utilized to evaluate manufacturability the evaluation method itself is independent of domain. Manufacturability has different levels of abstraction – process level, workshop level and machine level. Currently existing assessment tools address manufacturability in specific domains and stages. In the emerging markets of increasing competition, streamlining the PRP involves designing with manufacturing capability in mind, and knowledge and application of new technology and processes. This paper proposes a generic domain independent shell for manufacturability that is configurable and customizable to any domain or process. The paper presents the three stages of manufacturability and its relevance to a domain independent approach to manufacturability assessment. The paper presents the problems plaguing current systems and charts out the requirements for a new generic shell that can overcome these shortcomings. The paper then presents the architecture of the shell and presents issues of implementation and two case studies (2.5D milling and injection-molding) as a proof of concept of the functioning of the shell.

Engineering design is focussed on the development of artifacts and systems to satisfy specified functions. Current CAD systems provide little support integrating the modeling of the function, behavior, and form of designed artifacts throughout the design process. The focus of this paper is to investigate four representations for use in function representation for conceptual design, embodiment design, and design for manufacturing. These four representations include: Graph Grammars, Exemplars, Bond Graphs, and Function Converters. It is shown that different representations are more suited for different phases of design depending upon required design tasks and for representing different types of function knowledge. Finally, an approach for integration of these representations is proposed, synthesizing a hybrid representation based upon the strengths of the four identified strategies.