Development of As-Manufactured CAD Model for the Concept of "Product DNA".

Abstract

Manufacturing quality control is characterized by a plethora of data, continuously collected across the manufacturing processes and throughout a product’s life cycle. Traditionally, most of the quality inspection systems can only handle the dimensional information and few system addresses the issue of product performance both during assembly and in the field of use. Besides geometric dimensions, the product performance is also determined by other non-dimensional characteristics. For example, the density distribution of a blade plays an important role on its aerodynamic performance. Hence, in order to seamlessly integrate all the dimensional and non-dimensional information for better quality inspection, process diagnosis and performance analysis, I propose a representation for the concept of “Product DNA”. I have developed a representation of “Product DNA”, called as-manufactured CAD model, to encode high-definition features including geometry dimensions, surface texture, and physical attributes. By decoding the high-definition features, the information of manufacturing processes and functional performance can be examined and correlated. Under the framework of as-manufactured CAD model based “Product DNA” concept, this research mainly focuses on the coding process. For the dimensional geometry genome, a non-rigid registration approach is proposed to encode the geometry information into the as-manufactured CAD model based on inspection points. In this approach, a weighted mutual distance method is utilized to establish the correspondence and then the template object is iteratively transformed and morphed to best fit the measured points with affine and free-from deformation (FFD) transformation while maintaining geometry constraints. For the surface texture genome, a B-spline wavelet-based multi-resolution analysis (MRA) approach has been proposed for surface texture characterization. Compared to traditional surface texture analysis methods, the B-spline wavelet-based MRA method allows finer frequency regimes decomposition and thus achieves more precise diagnosis of process faults. For the physical attribute genome, a systematic approach to reconstruct a heterogeneous model based on mass density points is proposed. The decoupled B-spline based representations to model geometry and mass density allows more modeling flexibility and save huge storage space. Moreover, constraints and multi-resolution based mass density fitting algorithm guarantees to achieve reasonable mass density range and satisfied accuracy.