Operations Research, Systems Engineering and Industrial Engineering Commons^™

Crude Oil Prices Forecasting: Time Series Vs. Svr Models, Xin James He

Journal of International Technology and Information Management

This research explores the weekly crude oil price data from U.S. Energy Information Administration over the time period 2009 - 2017 to test the forecasting accuracy by comparing time series models such as simple exponential smoothing (SES), moving average (MA), and autoregressive integrated moving average (ARIMA) against machine learning support vector regression (SVR) models. The main purpose of this research is to determine which model provides the best forecasting results for crude oil prices in light of the importance of crude oil price forecasting and its implications to the economy. While SVR is often considered the best forecasting model in …

Table Of Contents Jitim Vol 27 Issue 3, 2018

Journal of International Technology and Information Management

Table of Contents

A Dynamic Policing Simulation Framework, Khan Md Ariful Haque

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Crime is a serious problem to a society, and its costs are an economic burden. With the help of technology and developed tools, law enforcement agencies are making significant efforts to combat crime, so as to create a safer environment for society, both mentally and physically. The dynamic nature of crime and limited police resources often make their efforts challenging. Although there are numerous crime prediction models found in the policing literature, guidelines for policing strategies based on those models are still lacking. Towards addressing this gap, this dissertation constructs a dynamic policing simulation framework based on the concept of …

A Parametric Process-Based Cost Estimation Framework To Support Conceptual Product Family Design And Production, Zahra Banakar

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

In today’s globally competitive environment, production costs estimation is a challenging task. This competitive market has brought specific strategies in the manufacturing sector, such as introducing more new products into the market with lower prices. In order to have the most accurate production costs estimation, accurate production cost information in a useful and relevant form is needed. This study presents a cost estimation framework that integrates both activity and parametric cost estimation methods to increase the ease, accuracy, and speed of producing cost estimates for a family of products or services. There is a need for an integrated production cost …

A Dynamic Multiple Stage, Multiple Objective Optimization Model With An Application To A Wastewater Treatment System, Prashant Tarun

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Decision-making for complex dynamic systems involves multiple objectives. Various methods balance the tradeoffs of multiple objectives, the most popular being weighted-sum and constraint-based methods. Under convexity assumptions an optimal solution to the constraint-based problem can also be obtained by solving the weighted-sum problems, and all Pareto optimal solutions can be obtained by systematically varying the weights or constraint limits. The challenge is to generate meaningful weights or constraint limits that yield practical solutions. In this dissertation, we utilize the Analytic Hierarchy Process (AHP) and develop a methodology to generate weight vectors successively for a dynamic multiple stage, multiple objective (MSMO) …

Global Renewable And Nonrenewable Energy Use Impact Assessment Of U.S. Manufacturing: An Integrated Cradle-To-Gate Lca And Dea Approach, Bahadir Ezici

Master's Theses

In this thesis, U.S. manufacturing industries` global supply chain-linked energy use and economic output are investigated considering a total of 16 renewable and nonrenewable energy carriers. A multiregion input output (MRIO) framework is employed to conduct the global supply chain-linked energy use impact assessment. The study period was between 1995 and 2014 based on data availability. Thus, 20 MRIO models were developed. Each MRIO model consists of the 40 largest economies of the world and the rest of the world (ROW) as the 41st country. Each country’s economy was structured into 35 manufacturing and service industries based on the Worth …

Collaborative Robotic Path Planning For Industrial Spraying Operations On Complex Geometries, Steven Brown

Graduate Theses and Dissertations

Implementation of automated robotic solutions for complex tasks currently faces a few major hurdles. For instance, lack of effective sensing and task variability – especially in high-mix/low-volume processes – creates too much uncertainty to reliably hard-code a robotic work cell. Current collaborative frameworks generally focus on integrating the sensing required for a physically collaborative implementation. While this paradigm has proven effective for mitigating uncertainty by mixing human cognitive function and fine motor skills with robotic strength and repeatability, there are many instances where physical interaction is impractical but human reasoning and task knowledge is still needed. The proposed framework consists …

Classifying Interdependencies In The Food And Agriculture Critical Infrastructure Sector, John Doerpinghaus

Graduate Theses and Dissertations

This work classifies examples of infrastructure interdependencies found in the food and agriculture critical infrastructure sector. Interdependencies are identified through an examination of rice and poultry agriculture throughout the state of Arkansas. The subtleties of interdependence examples in the food and agriculture sector are inadequately captured by the well-studied interdependence classification taxonomies. Through 39 interviews, we develop an understanding of the subtle temporal, geographic, and productivity scales of interdependence in over 100 examples and present five new, distinct classifications of interdependence: (1) dynamic physical, (2) dynamic geographic, (3) deadline, (4) delay, and (5) human, economic, and natural resource interdependencies. An …

System Engineering Analysis Of Terraforming Mars With An Emphasis On Resource Importation Technology, Brandon Wong

LMU Theses and Dissertations

This project uses System Engineering principles to delve into the viability of different methods for Terraforming Mars, with a comparison between Paraterraforming, Terraforming and Bioforming. It will then examine one subsystem that will be integral to the terraforming process, which is the space infrastructure necessary to import enough gases to recreate Earth’s atmosphere on Mars. It will analyze the viability of Chemical Rockets, Nuclear Rockets, Space Elevators, Skyhooks, Rotovators, Mass Drivers, Launch Loops and Orbital Rings for this subsystem and provide recommendations for an implementation plan.

Budget-Constrained Regression Model Selection Using Mixed Integer Nonlinear Programming, Jingying Zhang

Graduate Theses and Dissertations

Regression analysis fits predictive models to data on a response variable and corresponding values for a set of explanatory variables. Often data on the explanatory variables come at a cost from commercial databases, so the available budget may limit which ones are used in the final model.

In this dissertation, two budget-constrained regression models are proposed for continuous and categorical variables respectively using Mixed Integer Nonlinear Programming (MINLP) to choose the explanatory variables to be included in solutions. First, we propose a budget-constrained linear regression model for continuous response variables. Properties such as solvability and global optimality of the proposed …

Discrete Event Simulation And Cost Model For Optimization Of Manufacturing Resource Usages Associated With Implementation Of A Redesigned Product, Alexander Eierle

Theses and Dissertations

This paper demonstrates an approach to evaluating production factors related to schedule and resources based on changes to the production process. A discrete event simulation model was developed to evaluate different production factors, such as arrival times, number of entities, resource availabilities, and work in process (WIP) times, compared to the total yield at a production facility. This model helped to develop relationships between the required asset resource usages and the overall production resource allocation with the related effects to process wait times and production outputs. A comparative analysis with cost was performed to determine the effect that varied resources …

Integrated Reward Scheme And Surge Pricing In A Ride-Sourcing Market, Hai Yang, Chaoyi Shao, Hai Wang, Jieping Ye

Research Collection School Of Computing and Information Systems

Surge pricing is commonly used in on-demand ride-sourcing platforms (e.g., Uber, Lyft and Didi) to dynamically balance demand and supply. However, since the price for ride service cannot be unlimited, there is usually a reasonable or legitimate range of prices in practice. Such a constrained surge pricing strategy fails to balance demand and supply in certain cases, e.g., even adopting the maximum allowed price cannot reduce the demand to an affordable level during peak hours. In addition, the practice of surge pricing is controversial and has stimulated long debate regarding its pros and cons. To address the limitation of current …

Data Center Holistic Demand Response Algorithm To Smooth Microgrid Tie-Line Power Fluctuation, Ting Yang, Yingjie Zhao, Haibo Pen, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

With the rapid development of cloud computing, artificial intelligence technologies and big data applications, data centers have become widely deployed. High density IT equipment in data centers consumes a lot of electrical power, and makes data center a hungry monster of energy consumption. To solve this problem, renewable energy is increasingly integrated into data center power provisioning systems. Compared to the traditional power supply methods, renewable energy has its unique characteristics, such as intermittency and randomness. When renewable energy supplies power to the data center industrial park, this kind of power supply not only has negative effects on the normal …

Introduction To Data Analytics And Emerging Real-World Use Cases, Art Chaovalitwongse

Operations Management Presentations

Data analytics is a rapidly emerging interdisciplinary research area that involves advances in engineering, computer science, statistics and operations research. This webinar is focused on introducing the foundation of data analytics and emerging real-world use cases of data analytics. This presentation will begin with a discussion of the mathematical and statistical modeling aspects of various levels of data analytics (i.e., descriptive, predictive and prescriptive). In this webinar, you will hear an overview of data analytics in real world problems ranging from healthcare analytics, retail analytics and financial analytics.

Smart Disease Prevention App: Informing The Public In Their Own Geographic Location, Apoorva Sulakhe, Shafali Rana, Zoe Disori, William Nogay, Kyle Plummer, Meredith Shannon, Morgan Young, Alyssa Zielinski, Vincent G. Duffy

Purdue Journal of Service-Learning and International Engagement

Apoorva Sulakhe and Shefali Rana are graduate students in the School of Industrial Engineering at Purdue. They have both been teaching assistants under their coauthor, Dr. Vincent Duffy, while supervising multiple projects. Coauthors Zoe Disori, William Nogay, Kyle Plummer, Meredith Shannon, Morgan Young, and Alyssa Zielinski are listed in alphabetical order. They were all seniors in School of Industrial Engineering at the time of this project in 2017. The purpose of their study, described in this article, was to develop an application to provide users with accurate information about diseases spreading in their geographic locations.

Cost Benefit Analysis Of Led Vs Florescent Lighting, Kurtis Clark, Phillip Humphrey

Student Research

Over the last few years, the state of Oklahoma has been looking at ways to reduce expenses to address concerns about a budget deficit. There have been efforts made to reduce expenses due to the use of energy. It has been said, when the lights are on, work is getting done. Running lights is therefore the cost of doing business. Our research examines the question, “is there a way to provide better lighting while operating at a lower cost.” This research examines the current lighting at Southwestern State University, primarily fluorescent lighting (FL), and a cost benefit analysis of switching …

Characterizing Interfacial Bonds In Hybrid Metal Am Structures, John Ross Linn

Theses and Dissertations

The capabilities of various metal Additive Manufacturing (AM) processes, such as Powder Bed Fusion – Laser (PBF-L) and Direct Energy Deposition (DED) are increasing such that it is becoming ever more common to use them in industrial applications. The ability to print atop a substrate broadens that scope of applications. There is ongoing research regarding the mechanical properties of additively processed materials, but little regarding the interaction between additive material and its substrate. An understanding of the mechanical and performance properties of the AM/substrate interface is imperative. This paper describes a study of the strength properties of AM/substrate interfaces, with …

Logistics Best Practices For Regional Food Systems: A Review, Anuj Mittal, Caroline C. Krejci, Teri J. Craven

Industrial, Manufacturing, and Systems Engineering Faculty Publications - Archive

The modern industrial food supply system faces many major environmental and social sustainability challenges. Regional food systems, in which consumers prefer geographically proximate food producers, offer a response to these challenges. However, the costs associated with distributing food from many small-scale producers to consumers have been a major barrier to long-term regional food system success. Logistics best practices from conventional supply chains have the potential to improve the efficiency and effectiveness of regional food supply chains (RFSCs). This paper provides a structured and in-depth review of the existing literature on RFSC logistics, including recommended and implemented best practices. The purpose …

Analysis Of Parkinson's Disease Data, Ram Deepak Gottapu, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this paper, we investigate the diagnostic data from patients suffering with Parkinson's disease (PD) and design classification/prediction model to simplify the diagnosis. The main aim of this research is to open possibilities to be able to apply deep learning algorithms to help better understand and diagnose the disease. To our knowledge, the capabilities of deep learning algorithms have not yet been completely utilized in the field of Parkinson's research and we believe that by having an in-depth understanding of data, we can create a platform to apply different algorithms to automate the Parkinson's Disease diagnosis to certain extent. We …

Multi-Objective Evolutionary Neural Network To Predict Graduation Success At The United States Military Academy, Gene Lesinski, Steven Corns

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper presents an evolutionary neural network approach to classify student graduation status based upon selected academic, demographic, and other indicators. A pareto-based, multi-objective evolutionary algorithm utilizing the Strength Pareto Evolutionary Algorithm (SPEA2) fitness evaluation scheme simultaneously evolves connection weights and identifies the neural network topology using network complexity and classification accuracy as objective functions. A combined vector-matrix representation scheme and differential evolution recombination operators are employed. The model is trained, tested, and validated using 5100 student samples with data compiled from admissions records and institutional research databases. The inputs to the evolutionary neural network model are used to classify …