abstract: Metal castings are selectively machined-based on dimensional control requirements. To ensure that all the finished surfaces are fully machined, each as-cast part needs to be measured and then adjusted optimally in its fixture. The topics of this thesis address two parts of this process: data translations and feature-fitting clouds of points measured on each cast part. For the first, a CAD model of the finished part is required to be communicated to the machine shop for performing various machining operations on the metal casting. The data flow must include GD&T specifications along with other special notes that may be required to communicate to the machinist. Current data exchange, among various digital applications, is limited to translation of only CAD geometry via STEP AP203. Therefore, an algorithm is developed in order to read, store and translate the data from a CAD file (for example SolidWorks, CREO) to a standard and machine readable format (ACIS format - *.sat). Second, the geometry of cast parts varies from piece to piece and hence fixture set-up parameters for each part must be adjusted individually. To predictively determine these adjustments, the datum surfaces, and to-be-machined surfaces are scanned individually and the point clouds reduced to feature fits. The scanned data are stored as separate point cloud files. The labels associated with the datum and to-be-machined (TBM) features are extracted from the *.sat file. These labels are further matched with the file name of the point cloud data to identify data for the respective features. The point cloud data and the CAD model are then used to fit the appropriate features (features at maximum material condition (MMC) for datums and features at least material condition (LMC) for TBM features) using the existing normative feature fitting (nFF) algorithm. Once the feature fitting is complete, a global datum reference frame (GDRF) is constructed based on the locating method that will be used to machine the part. The locating method is extracted from a fixture library that specifies the type of fixturing used to machine the part. All entities are transformed from its local coordinate system into the GDRF. The nominal geometry, fitted features, and the GD&T information are then stored in a neutral file format called the Constraint Tolerance Feature (CTF) Graph. The final outputs are then used to identify the locations of the critical features on each part and these are used to establish the adjustments for its setup prior to machining, in another module, not part of this thesis. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2016

There are many different programs that can perform Computer Aided Design (CAD). In order for these programs to share data, file translations need to occur. These translations have typically been done by IGES and STEP files. With the work done at the BYU CAD Lab to create a multi-engineer synchronous heterogeneous CAD environment, these translation processes have become synchronous by using a server and a database to manage the data. However, this system stores part data in a database. The data in the database cannot be used in traditional Product Lifecycle Management systems. In order to remedy this, a new database was developed that enables every edit made in a CAD part across multiple CAD systems to be stored as well as worked on simultaneously. This allows users to access every action performed in a part. Branching was introduced to the database which allows users to work on multiple configurations of a part simultaneously and reduces file save sizes for different configurations by 98.6% compared to those created by traditional CAD systems.