Operations Research, Systems Engineering and Industrial Engineering Commons^™

Flipping The Classroom For Introduction To Probability And Statistics For Engineers, Philomena Krosmico

Graduate Theses, Dissertations, and Problem Reports

Introduction to Probability and Statistics for Engineers, IENG 213, is a foundational course in the Industrial Engineering curriculum at West Virginia University (WVU). The challenge has been finding the best teaching method to instill concept learning. A “flipped classroom” teaching style has been gaining momentum throughout higher education and has had proven success in STEM fields. At WVU, beginning with the 2016 Fall semester, the teaching model for the class used a flipped classroom style for one of the instructors. Data on statistical concept learning, using the University of Oklahoma validated statistics concept inventory instrument (Allen K., 2006), was collected …

An Equest Based Building Energy Modeling Analysis For Energy Efficiency Of Buildings, Saroj Lamichhane

Graduate Theses, Dissertations, and Problem Reports

Building energy performance is a function of numerous building parameters. In this study, sensitivity analysis on twenty parameters is performed to determine the top three parameters which have the most significant impact on the energy performance of buildings. Actual data from two fully operational commercial buildings were collected and used to develop a building energy model in eQUEST. The model is calibrated using Normalized Mean Bias Error (NMBE) and Coefficient of Variation of Root Mean Square Error (CV(RMSE)) method. The model satisfies the NMBE and CV(RMSE) criteria set by the American Society of Heating, Refrigeration, and Air-Conditioning (ASHRAE) Guideline 14, …

Models And Solution Approaches For Integrated Student To School Assignment And School Bus Routing Problem Focusing On Special Needs Students, Azadeh Ansari

Graduate Theses, Dissertations, and Problem Reports

This dissertation addresses the integrated problem of assigning students to schools and generating school bus routes particularly focusing on the special needs students is addressed. Special needs students generally require supplementary accommodations and must be picked up from and dropped off at their home addresses. This will increase the number of nodes in the network and therefore introduces additional complexities to the problems of assignment and routing for students. An integrated single objective mathematical model is first developed that simultaneously assigns the students to schools based on their needs and generates efficient bus routes to deliver the students to their …

Effect Of Feedrate, Depth Of Cut, Tool Material, And Toolpath On Dimensional Accuracy And Surface Roughness Of Milled Cfrp, Assem Hesham Almadani

Graduate Theses, Dissertations, and Problem Reports

This thesis investigates the effect of different factors on Carbon Fiber Reinforced Polymers (CFRP) milling, like feedrate, tool material, and cutting speed. CFRP offers excellent material properties, which led to the increase of the material in today's manufacturing industry. CFRP offers up to 2.25 times steel's modulus of elasticity at about a fifth of the weight and excellent thermal properties, which allow the use of this material in applications with high heat like automobiles. Many industries have implemented the use of CFRP in their applications, like airplanes and automobiles, which lead to a decrease in weight and increase in strength. …

Determination Of Effectiveness Of Energy Management System In Buildings, Vivash Karki

Graduate Theses, Dissertations, and Problem Reports

Building Energy Management Systems (BEMS) are computer-based systems that aid in managing, controlling, and monitoring the building technical services and energy consumption by equipment used in the building. The effectiveness of BEMS is dependent upon numerous factors, among which the operational characteristics of the building and the BEMS control parameters also play an essential role. This research develops a user-driven simulation tool where users can input the building parameters and BEMS controls to determine the effectiveness of their BEMS. The simulation tool gives the user the flexibility to understand the potential energy savings by employing specific BEMS control and help …

Multivariate Time Series Classification Of Sensor Data From An Industrial Drying Hopper: A Deep Learning Approach, Md Mushfiqur Rahman

Graduate Theses, Dissertations, and Problem Reports

In recent years, the advancement of industry 4.0 and smart manufacturing has made a large number of industrial process data attainable with the use of sensors installed in the machineries. This thesis proposes an experimental predictive maintenance framework for an industrial drying hopper so that it can detect any unusual event in the hopper which reduces the risk of erroneous fault diagnosis in the manufacturing shop floor. The experimental framework uses Deep Learning (DL) algorithms in order to classify Multivariate Time Series (MTS) data into two categories- failure or unusual events and regular events, thus formulating the problem as binary …

Sustainability Key Performance Indicators For Mass Customization, Md Fahid Hasan Pulak

Graduate Theses, Dissertations, and Problem Reports

Today’s manufacturers are striving towards a more sustainable and customized product offering in their value chain to satisfy customer demand and compete on the marketplace. By adopting sustainability practices, companies are not only complying with environmental regulations but are strategically addressing the triple bottom line (TBL) of sustainability (environmental, social, and economic). Similarly, mass customization allows a company to better satisfy their customers by creating individualized products economically. Moving forward, it is important to better understand the relationship of these two competitive strategies. In order to assess the sustainability performance of mass customization, it is important to understand the appropriate …

Validation Of Shoulder Strain Index, Fabiha Islam

Graduate Theses, Dissertations, and Problem Reports

Musculoskeletal disorders (MSDs) of shoulder are one of the most frequent and major causes of morbidity and pain among full-time workers in the USA. In 2018, shoulder disorders were the most severe type of MSDs in terms of lost workdays. Recent epidemiological studies have identified several biomechanical, organizational, and psychological factors that increase the risk of shoulder MSDs. Though multiple biomechanical studies have evaluated physical causal factors of shoulder MSDs with a goal of risk mitigation, literature lacks a standardized risk assessment tool. The main objective of this study was to validate a previously developed shoulder strain index. The strain …

Prediction Of Tensile Behaviors Of L-Ded 316 Stainless Steel Parts Using Machine Learning, Israt Zarin Era

Graduate Theses, Dissertations, and Problem Reports

Directed energy deposition (DED) is a rising field in the arena of metal additive manufacturing and has extensive applications in aerospace, medical and rapid prototyping. The process parameters, such as laser power, scanning speed and specimen height, play a great deal in controlling and affecting the properties of DED fabricated parts. Nevertheless, both experimental and simulation methods have shown constraints and limited ability to generate accurate and efficient computational predictions on the correlations between the process parameters and the final part quality. In this work, a data driven machine learning model XGBoost has been built and applied to predict the …

Improving Real-Time Methane Monitoring In Longwall Coal Mines Through System Response Characterization Of A Multi-Nodal Methane Detection Network, Brian Philip Cappellini

Graduate Theses, Dissertations, and Problem Reports

Machine automation and atmospheric monitoring are used by many industries to improve safety and productivity in the workplace. The underground Methane Watchdog System (MWS) is a multi-nodal network of sensors currently under development. The MWS aims to improve safety and productivity by introducing 10 compact sampling units designed to be easily integrated within the current roof support equipment of the mine. Each unit contains an array of sensors used to continuously monitor the environmental conditions which include methane concentration, temperature, pressure, and relative humidity. All MWS units report information back to a remote central processing hub (CPH) which collects nodal …

Evaluation Of Lidar Systems For Rock Mass Discontinuity Identification In Underground Stone Mines From 3d Point Cloud Data, Mario Alejandro Bendezu De La Cruz

Graduate Theses, Dissertations, and Problem Reports

The goal of this thesis is to compare the accuracy and precision of the discontinuity identification results obtained by three active remote sensing technologies along with a point cloud processing program, and the results obtained by conventional methods. For this research, the active remote sensing devices were terrestrial LIDAR, mobile LiDAR with Simultaneous localization, and mapping (SLAM), and LIDAR/Camera on an autonomous UAV. The open-source point cloud data processing programs Discontinuity Set Extractor (DSE) and the Cloud Compare were used to process point cloud data.

The results of this research found that it is possible to identify certain geological structures …

Identification Of Moving Bottlenecks In Production Systems, Funmilayo Mofoluwasola Adeyinka

Graduate Theses, Dissertations, and Problem Reports

Manufacturing sector have been plagued by bottlenecks from time immemorial, leading to loss of productivity and profitability, various research effort has been expended towards identifying and mitigating the effects of bottlenecks on production lines. However, traditional approaches often fail in identifying moving bottlenecks. The current data boom and giant strides made in the machine learning field proffers an alternative means of using the large volume of data generated by machines in identifying bottlenecks. In this study, a hierarchical agglomerative clustering algorithm is used in identifying potential groups of bottlenecks within a serial production line.

A serial production line with five …