Global ETD Search

21	Development and Evaluation of a Machine Vision System for Digital Thread Data Traceability in a Manufacturing Assembly Environment Alexander W Meredith (15305698) 29 April 2023 (has links) <p>A thesis study investigating the development and evaluation of a computer vision (CV) system for a manufacturing assembly task is reported. The CV inference results are compared to a Manufacturing Process Plan and an automation method completes a buyoff in the software, Solumina. Research questions were created and three hypotheses were tested. A literature review was conducted recognizing little consensus of Industry 4.0 technology adoption in manufacturing industries. Furthermore, the literature review uncovered the need for additional research within the topic of CV. Specifically, literature points towards more research regarding the cognitive capabilities of CV in manufacturing. A CV system was developed and evaluated to test for 90% or greater confidence in part detection. A CV dataset was developed and the system was trained and validated with it. Dataset contextualization was leveraged and evaluated, as per literature. A CV system was trained from custom datasets, containing six classes of part. The pre-contextualization dataset and post-contextualization dataset was compared by a Two-Sample T-Test and statistical significance was noted for three classes. A python script was developed to compare as-assembled locations with as-defined positions of components, per the Manufacturing Process Plan. A comparison of yields test for CV-based True Positives (TPs) and human-based TPs was conducted with the system operating at a 2σ level. An automation method utilizing Microsoft Power Automate was developed to complete the cognitive functionality of the CV system testing, by completing a buyoff in the software, Solumina, if CV-based TPs were equal to or greater than human-based TPs.</p> Automation engineering Flexible manufacturing systems Industrial engineering Manufacturing safety and quality Knowledge representation and reasoning Computer vision Object detection and classification object detection and tracking Smart Manufacturing Systems MES system Smart Manufacturing Approach Quality engineering Manufacturing automation systems manufacturing automation Cognitive Systems Engineering cognitive system computer vision machine vision manufacturing execution system robotic process automation Digital Thread (DT) Digital Thread digital twin approach manufacturing assembly assembly quality manufacturing traceability advanced manufacturing advanced quality control Quality 4.0 Industry 4.0 Industry 5.0 Quality 5.0 Human Machine Interactions
22	A plm implementation for aerospace systems engineering-conceptual rotorcraft design Hart, Peter Bartholomew 08 April 2009 (has links) The thesis will discuss the Systems Engineering phase of an original Conceptual Design Engineering Methodology for Aerospace Engineering-Vehicle Synthesis. This iterative phase is shown to benefit from digitization of Integrated Product&Process Design (IPPD) activities, through the application of Product Lifecycle Management (PLM) technologies. Requirements analysis through the use of Quality Function Deployment (QFD) and 7 MaP tools is explored as an illustration. A "Requirements Data Manager" (RDM) is used to show the ability to reduce the time and cost to design for both new and legacy/derivative designs. Here the COTS tool Teamcenter Systems Engineering (TCSE) is used as the RDM. The utility of the new methodology is explored through consideration of a legacy RFP based vehicle design proposal and associated aerospace engineering. The 2001 American Helicopter Society (AHS) 18th Student Design Competition RFP is considered as a starting point for the Systems Engineering phase. A Conceptual Design Engineering activity was conducted in 2000/2001 by Graduate students (including the author) in Rotorcraft Engineering at the Daniel Guggenheim School of Aerospace Engineering at the Georgia Institute of Technology, Atlanta GA. This resulted in the "Kingfisher" vehicle design, an advanced search and rescue rotorcraft capable of performing the "Perfect Storm" mission, from the movie of the same name. The associated requirements, architectures, and work breakdown structure data sets for the Kingfisher are used to relate the capabilities of the proposed Integrated Digital Environment (IDE). The IDE is discussed as a repository for legacy knowledge capture, management, and design template creation. A primary thesis theme is to promote the automation of the up-front conceptual definition of complex systems, specifically aerospace vehicles, while anticipating downstream preliminary and full spectrum lifecycle design activities. The thesis forms a basis for additional discussions of PLM tool integration across the engineering, manufacturing, MRO and EOL lifecycle phases to support business management processes. Teamcenter systems engineering Teamcenter community Teamcenter unified Teamcenter engineering Teamcenter manufacturing CATIA V5 Rotorcraft design Boeing AHS Joint heavy lift VPLM MBOM EBOM Product change control Product definition Configuration management Product structure architecture Design engineering Aerospace engineering System engineering PLM CIE IDE SE Affordability Cost savings Executive helicopter Joint chiefs of staff Marine CAE CAD CAM CAA MDO RSM DOE Consulting Engineering management Perfect storm Engineering software Requirements data management CATIA V4 NX Engineering communications RFP Digitization Air Force Navy Army BAMS FIPER ACSYNT Sikorsky Bell Georgia Tech Engineering methodology Requirements engineering System engineering Search Rescue IDE Integrated digital environment Kingfisher Search and rescue Helicopter Helicopter engineering QFD Legacy design IPPD Quality engineering Defense systems acquisition Coast Guard Decision support systems Rotors (Helicopters) Design Concurrent engineering
23	Minimization of Noise and Vibration Related to Driveline Imbalance using Robust Design Processes Al-Shubailat, Omar 17 August 2013 (has links) Variation in vehicle noise, vibration and harshness (NVH) response can be caused by variability in design (e.g. tolerance), material, manufacturing, or other sources of variation. Such variation in the vehicle response causes a higher percentage of produced vehicles to have higher levels (out of specifications) of NVH leading to higher number of warranty claims and loss of customer satisfaction, which are proven costly. Measures must be taken to ensure less warranty claims and higher levels of customer satisfactions. As a result, original equipment manufacturers (OEMs) have implemented design for variation in the design process to secure an acceptable (or within specification) response. The focus here will be on aspects of design variations that should be considered in the design process of drivelines. Variations due to imbalance in rotating components can be unavoidable or costly to control. Some of the major components in the vehicle that are known to have imbalance and traditionally cause NVH issues and concerns include the crankshaft, the drivetrain components (transmission, driveline, half shafts, etc.), and wheels. The purpose is to assess NVH as a result of driveline imbalance variations and develop a tool to help design a more robust system to such variations. program. Java quality engineering quality capability studies manufacturing processes manufacturing engineer design engineer sales profit customer concern warranty objectionable Eigen functions vectors Eigen Eigen values identity Euler differential equations differential transfer case shaft driveline static imbalance dynamic imbalance passenger customer driver inboard ear driver outboard ear steering wheel seat track variation Gamma distribution normal distribution standard deviation average variance mean phasor victor scalar linear system LTI linear time invariant transfer function output input microphone accelerometers tachometer channels order frequency frequency domain time domain convolution Transformation Fourier Transformer Fourier imaginary and real logarithmic decibel sensitivity curves run down run up two wheel drive Four Wheel Drive Nissan Truck OEM Original Equipment Manufacturers Data Acquisitions Channels Simulation Six Sigma variability Design Robust sensitivity Vibration Imbalance Noise Harshness NVH Driveline

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