Prediction of assembly variation during early design

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, 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 Datum 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. Results of a demonstration test case study for vertical fin design were encouraging with modeling methods coming within 15% of deviation compared to the detailed design simulation.