Engineering Commons^™

The Effect Of Process Parameters And Surface Condition On Bond Strength Between Additively Manufactured Components And Polymer Substrates, Bharat Bhushan Chivukula

Graduate Theses and Dissertations

Additive patching is a process in which printers with multiple axes deposit molten material onto a pre-defined surface to form a bond. Studying the effect of surface roughness and process parameters selected for printing auxiliary part on the bond helps in improving the strength of the final component. Particularly, the influence of surface roughness, as established by adhesion theory, has not been evaluated in the framework of additive manufacturing (AM). A full factorial design of experiments with five replications was conducted on two levels and three factors, viz., layer thickness, surface roughness, and raster angle to examine the underlying effects …

Grouping Techniques To Manage Large-Scale Multi-Item Multi-Echelon Inventory Systems, Anvar Abaydulla

Graduate Theses and Dissertations

Large retail companies operate large-scale systems which may consist of thousands of stores. These retail stores and their suppliers, such as warehouses and manufacturers, form a large-scale multi-item multi-echelon inventory supply network. Operations of this kind of inventory system require a large number of human resources, computing capacity, etc.

In this research, three kinds of grouping techniques are investigated to make the large-scale inventory system “easier” to manage. The first grouping technique is a network based ABC classification method. A new classification criterion is developed so that the inventory network characteristics are included in the classification process, and this criterion …

Safety Performance Prediction Of Large-Truck Drivers In The Transportation Industry, Emily Moneka Francis Xavier

Graduate Theses and Dissertations

The trucking industry and truck drivers play a key role in the United States commercial transportation sector. Accidents involving large trucks is one such big event that can cause huge problems to the driver, company, customer and other road users causing property damage and loss of life. The objective of this research is to concentrate on an individual transportation company and use their historical data to build models based on statistical and machine learning methods to predict accidents. The focus is to build models that has high accuracy and correctly predicts an accident. Logistic regression and penalized logistic regression models …

Incorporating A New Class Of Uncertainty In Disaster Relief Logistics Planning, Emre Kirac

Graduate Theses and Dissertations

In recent years, there has been a growing interest among emergency managers in using Social data in disaster response planning. However, the trustworthiness and reliability of posted information are two of the most significant concerns, because much of the user-generated data is initially not verified. Therefore, a key tradeoff exists for emergency managers when considering whether to incorporate Social data in disaster planning efforts. By considering Social data, a larger number of needs can be identified in a shorter amount of time, potentially enabling a faster response and satisfying a class of demand that might not otherwise be discovered. However, …

Risk Estimation Toward A Natural History Model For Low Grade Glioma Patients, Anh Thi Hoang Pham

Graduate Theses and Dissertations

Glioma is a common type of primary brain tumor that represents 28% of all brain tumors and 80% of malignant tumors. According to a recent study by the Centers for Disease Control and Prevention (CDC), gliomas account for 53%, 35% and 29% of all brain tumors (68%, 74% and 81% of malignant brain tumors) among children (aged 0-14), teenagers (aged 15-19) and young adults, respectively. Gliomas are often diagnosed through radiological imaging and histopathology. There are two main groups of gliomas following World Health Organization’s classification: Low grade gliomas (LGG), or grade I and II gliomas; and high grade gliomas …

A Tabu Search, Augment-Merge Heuristic To Solve The Stochastic Location Arc Routing Problem, Tiffany L. Yang

Graduate Theses and Dissertations

The location arc routing problem (LARP) is a network optimization problem combining strategic facility location decisions and tactical or operational vehicle routing decisions for customer demand located on arcs of a network. The LARP seeks to locate facilities, or depots, and create vehicle delivery routes to minimize costs. The total cost is comprised of three components: fixed facility locations costs, fixed route creation (or vehicle acquisition) costs, and variable arc traversal costs. The applications of the LARP are varied and often include public services such as mail delivery, garbage collection, and street sweeping. In all of these applications, the magnitude …

Use Of Response Surfaces In The Design Of A Simple Step Stress Accelerated Test Plan, Alexander H. Wong

Graduate Theses and Dissertations

In designing accelerated testing plans, cost is a factor that is missing in much of the literature. This paper explicits considers cost by developing an optimization model with the objective to minimize costs for a simple step stress accelerated test plan. Two methodologies are employed. One is an optimization approach in which an attempt is made to quantify the behavior of a series-parallel hardware system over all stages of testing using a response surface, and then an optimization model is used to determine the settings for stresses and failure mode modifications for all stages of testing prior to the start …