Through recent advancements in high-density dimensional (HDD) measurement technologies, such as 3D laser scanners, data-sets consisting of an almost complete representation of a manufactured part's geometry can now be obtained. While HDD data measurement devices have traditionally been used in reverse engineering application, they are beginning to be applied as in-line measurement devices. Unfortunately, appropriate quality control (QC) techniques have yet to be developed to take full advantage of this new data-rich environment and for the most part rely on extracting discrete key product characteristics (KPCs) for analysis. In order to maximize the potential of HDD measurement technologies requires a new quality paradigm. Specifically, when presented with HDD data, quality should not only be assessed by discrete KPCs but should consider the entire part being produced, anything less results in valuable data being wasted. This dissertation addresses the need for adapting current techniques and developing new approaches for the use of HDD data in manufacturing systems to increase overall quality control (QC) capabilities. Specifically, this research effort focuses on the use of HDD data for 1) Developing a framework for self-correcting compliant assembly systems, 2) Using statistical process control to detect process shifts through part surfaces, and 3) Performing automated part inspection for non-feature based faults. The overarching goal of this research is to identify how HDD data can be used within these three research focus areas to increase QC capabilities while following the principles of the aforementioned new quality paradigm. / Ph. D.

The procedure of joining flexible or nonrigid parts using applied loads is called compliant assembly, and it is widely used in automotive, aerospace, electronics, and appliance manufacturing. Uncontrolled assembly processes may produce geometric errors that can exceed design tolerances and induce an increment of elastic energy in the structure due to the accumulation of internal stresses. This condition might create unexpected deformations and residual stress distributions across the structure that compromise product functionality. This thesis presents a method based on nonlinear Finite Element Analysis (FEA), metamodelling, and optimization techniques to provide accurate and on-time shimming strategies to support the definition of optimum assembly strategies. An example of the method on a typical aerospace wing box structure is demonstrated in the present study. The delivered outputs intend to support the production line by anticipating the response of the structure under a specific assembly condition and presenting alternative assembly strategies that can be applied to address eventual predicted issues on product requirements. / Graduate