Matching Items (3)
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Description
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

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.
ContributorsRamnath, Satchit (Author) / Shah, Jami J. (Thesis advisor) / Davidson, Joseph (Committee member) / Hansford, Dianne (Committee member) / Arizona State University (Publisher)
Created2016
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Description
When manufacturing large or complex parts, often a rough operation such as casting is used to create the majority of the part geometry. Due to the highly variable nature of the casting process, for mechanical components that require precision surfaces for functionality or assembly with others, some of the important

When manufacturing large or complex parts, often a rough operation such as casting is used to create the majority of the part geometry. Due to the highly variable nature of the casting process, for mechanical components that require precision surfaces for functionality or assembly with others, some of the important features are machined to specification. Depending on the relative locations of as-cast to-be-machined features and the amount of material at each, the part may be positioned or ‘set up’ on a fixture in a configuration that will ensure that the pre-specified machining operations will successfully clean up the rough surfaces and produce a part that conforms to any assigned tolerances. For a particular part whose features incur excessive deviation in the casting process, it may be that no setup would yield an acceptable final part. The proposed Setup-Map (S-Map) describes the positions and orientations of a part that will allow for it to be successfully machined, and will be able to determine if a particular part cannot be made to specification.

The Setup Map is a point space in six dimensions where each of the six orthogonal coordinates corresponds to one of the rigid-body displacements in three dimensional space: three rotations and three translations. Any point within the boundaries of the Setup-Map (S-Map) corresponds to a small displacement of the part that satisfies the condition that each feature will lie within its associated tolerance zone after machining. The process for creating the S-Map involves the representation of constraints imposed by the tolerances in simple coordinate systems for each to-be-machined feature. Constraints are then transformed to a single coordinate system where the intersection reveals the common allowable ‘setup’ points. Should an intersection of the six-dimensional constraints exist, an optimization scheme is used to choose a single setup that gives the best chance for machining to be completed successfully. Should no intersection exist, the particular part cannot be machined to specification or must be re-worked with weld metal added to specific locations.
ContributorsKalish, Nathan (Author) / Davidson, Joseph K. (Thesis advisor) / Shah, Jami J. (Thesis advisor) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2016
Description

The CNC mill is a highly valuable tool for engineering design, allowing for the creation of precise and complex metal parts. However, due to their high cost, many engineers do not have access to these machines until they enter industry, limiting the knowledge and experience of engineering students. This also

The CNC mill is a highly valuable tool for engineering design, allowing for the creation of precise and complex metal parts. However, due to their high cost, many engineers do not have access to these machines until they enter industry, limiting the knowledge and experience of engineering students. This also restricts the level of engineering design they can participate in as they are limited to lower strength materials and processes. To expand the possibilities for engineering students, hobbyists, and small businesses, we created a reliable and affordable desktop CNC mill. Our machine is capable of cutting non-ferrous metals such as aluminum with 70?m repeatable part precision and be compatible with coolant and vacuum systems.

ContributorsAltobelli, Seth (Author) / Hodson, Kenneth (Co-author) / Jordan, Shawn (Thesis director) / Sweeney, Rhett (Committee member) / Barrett, The Honors College (Contributor) / Engineering Programs (Contributor)
Created2023-05