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- All Subjects: Measurement
- All Subjects: Coordinate measuring machines
- Genre: Academic theses
- Creators: Shah, Jami J.
- Creators: Ainsworth, Barbara E
- Resource Type: Text
Description
The health benefits of physical activity are widely accepted. Emerging research also indicates that sedentary behaviors can carry negative health consequences regardless of physical activity level. This dissertation explored four projects that examined measurement properties of physical activity and sedentary behavior monitors. Project one identified the oxygen costs of four other care activities in seventeen adults. Pushing a wheelchair and pushing a stroller were identified as moderate-intensity activities. Minutes spent engaged in these activities contribute towards meeting the 2008 Physical Activity Guidelines. Project two identified the oxygen costs of common cleaning activities in sixteen adults. Mopping a floor was identified as moderate-intensity physical activity, while cleaning a kitchen and cleaning a bathtub were identified as light-intensity physical activity. Minutes spent engaged in mopping a floor contributes towards meeting the 2008 Physical Activity Guidelines. Project three evaluated the differences in number of minutes spent in activity levels when utilizing different epoch lengths in accelerometry. A shorter epoch length (1-second, 5-seconds) accumulated significantly more minutes of sedentary behaviors than a longer epoch length (60-seconds). The longer epoch length also identified significantly more time engaged in light-intensity activities than the shorter epoch lengths. Future research needs to account for epoch length selection when conducting physical activity and sedentary behavior assessment. Project four investigated the accuracy of four activity monitors in assessing activities that were either sedentary behaviors or light-intensity physical activities. The ActiGraph GT3X+ assessed the activities least accurately, while the SenseWear Armband and ActivPAL assessed activities equally accurately. The monitor used to assess physical activity and sedentary behaviors may influence the accuracy of the measurement of a construct.
ContributorsMeckes, Nathanael (Author) / Ainsworth, Barbara E (Thesis advisor) / Belyea, Michael (Committee member) / Buman, Matthew (Committee member) / Gaesser, Glenn (Committee member) / Wharton, Christopher (Christopher Mack), 1977- (Committee member) / Arizona State University (Publisher)
Created2012
Description
Dimensional Metrology is the branch of science that determines length, angular, and geometric relationships within manufactured parts and compares them with required tolerances. The measurements can be made using either manual methods or sampled coordinate metrology (Coordinate measuring machines). Manual measurement methods have been in practice for a long time and are well accepted in the industry, but are slow for the present day manufacturing. On the other hand CMMs are relatively fast, but these methods are not well established yet. The major problem that needs to be addressed is the type of feature fitting algorithm used for evaluating tolerances. In a CMM the use of different feature fitting algorithms on a feature gives different values, and there is no standard that describes the type of feature fitting algorithm to be used for a specific tolerance. Our research is focused on identifying the feature fitting algorithm that is best used for each type of tolerance. Each algorithm is identified as the one to best represent the interpretation of geometric control as defined by the ASME Y14.5 standard and on the manual methods used for the measurement of a specific tolerance type. Using these algorithms normative procedures for CMMs are proposed for verifying tolerances. The proposed normative procedures are implemented as software. Then the procedures are verified by comparing the results from software with that of manual measurements.
To aid this research a library of feature fitting algorithms is developed in parallel. The library consists of least squares, Chebyshev and one sided fits applied on the features of line, plane, circle and cylinder. The proposed normative procedures are useful for evaluating tolerances in CMMs. The results evaluated will be in accordance to the standard. The ambiguity in choosing the algorithms is prevented. The software developed can be used in quality control for inspection purposes.
To aid this research a library of feature fitting algorithms is developed in parallel. The library consists of least squares, Chebyshev and one sided fits applied on the features of line, plane, circle and cylinder. The proposed normative procedures are useful for evaluating tolerances in CMMs. The results evaluated will be in accordance to the standard. The ambiguity in choosing the algorithms is prevented. The software developed can be used in quality control for inspection purposes.
ContributorsVemulapalli, Prabath (Author) / Shah, Jami J. (Thesis advisor) / Davidson, Joseph K. (Committee member) / Takahashi, Timothy (Committee member) / Arizona State University (Publisher)
Created2014
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 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
Description
Having accurate measurements of sedentary behaviors is important to understand relationships between sedentary behaviors and health outcomes and to evaluate changes in interventions and health promotion programs designed to reduce sedentary behaviors. This dissertation included three projects that examined measurement properties of wearable monitors used to measure sedentary behaviors. Project one examined the validity of three monitors: the ActiGraph GT3X+, activPAL™, and SenseWear 2. None of the monitors were equivalent with the criterion measure of oxygen uptake to estimate the energy cost of sedentary and light-intensity activities. The ActivPAL™ had the best accuracy as compared with the other monitors. In project two, the accuracy of ActiGraph GT3X+and GENEActiv cut-points used to assess sedentary behavior were compared with direct observation during free-living conditions. New vector magnitude cut-points also were developed to classify time spent in sedentary- and stationary behaviors during free-living conditions. The cut-points tested had modest overall accuracy to classify sedentary time as compared to direct observation. New ActiGraph 1-minute vector cut-points increased overall accuracy for classifying sedentary time. Project 3 examined the accuracy of the sedentary sphere by testing various arm elevation- and movement-count configurations using GENEActiv and ActiGraph GT3X+ data obtained during free-living conditions. None of the configurations were equivalent to the criterion measure of direct observation. The best configuration of the GENEActiv was: worn on the dominant wrist at 15 degrees below the horizontal plane with a cut-point <489 for each 15-second interval. The best configuration for the ActiGraph was: worn on the non-dominant wrist at 5° below the horizontal plane with a cut-point of <489 counts for each 15-second interval. Collectively, these findings indicate that the wearable monitors and methods examined in this study are limited in their ability to assess sedentary behaviors and light intensity physical activity. Additional research is needed to further understand the scope and limitations of wearable monitors and methods used to assess sedentary behaviors and light intensity physical activity.
ContributorsFlorez Pregonero, Argemiro Alberto (Author) / Ainsworth, Barbara E (Thesis advisor) / Buman, Matthew P (Committee member) / Hooker, Steven P (Committee member) / Keller, Colleen S (Committee member) / Swan, Pamela (Committee member) / Arizona State University (Publisher)
Created2017
Description
The essence of this research is the reconciliation and standardization of feature fitting algorithms used in Coordinate Measuring Machine (CMM) software and the development of Inspection Maps (i-Maps) for representing geometric tolerances in the inspection stage based on these standardized algorithms. The i-Map is a hypothetical point-space that represents the substitute feature evaluated for an actual part in the inspection stage. The first step in this research is to investigate the algorithms used for evaluating substitute features in current CMM software. For this, a survey of feature fitting algorithms available in the literature was performed and then a case study was done to reverse engineer the feature fitting algorithms used in commercial CMM software. The experiments proved that algorithms based on least squares technique are mostly used for GD&T; inspection and this wrong choice of fitting algorithm results in errors and deficiency in the inspection process. Based on the results, a standardization of fitting algorithms is proposed in light of the definition provided in the ASME Y14.5 standard and an interpretation of manual inspection practices. Standardized algorithms for evaluating substitute features from CMM data, consistent with the ASME Y14.5 standard and manual inspection practices for each tolerance type applicable to planar features are developed. Second, these standardized algorithms developed for substitute feature fitting are then used to develop i-Maps for size, orientation and flatness tolerances that apply to their respective feature types. Third, a methodology for Statistical Process Control (SPC) using the I-Maps is proposed by direct fitting of i-Maps into the parent T-Maps. Different methods of computing i-Maps, namely, finding mean, computing the convex hull and principal component analysis are explored. The control limits for the process are derived from inspection samples and a framework for statistical control of the process is developed. This also includes computation of basic SPC and process capability metrics.
ContributorsMani, Neelakantan (Author) / Shah, Jami J. (Thesis advisor) / Davidson, Joseph K. (Committee member) / Farin, Gerald (Committee member) / Arizona State University (Publisher)
Created2011