Engineering Commons^™

Optimization-Based Uav Fleet Routing And Safety Assurance – Models, Algorithms, And Prototyping, Zhenyu Zhou

Wayne State University Dissertations

Unmanned aerial vehicles (UAVs), especially multi-rotor drones, have been increasingly used in various scenarios in the last decade. With the reduced hardware costs, improved battery life, and enhanced processor performance, we can eventually allow all kinds of drones to automatically travel through the low-altitude airspace. The large-scale application of drones will extend the basic transportation facilities from the ground to the air and form 3D transportation networks for the future. Compared to current ground-vehicle and aircraft traffic systems, multi-UAV systems are far from well-developed. Most current multi-UAV systems are human-operated or pre-programmed to perform specific tasks. The current application of …

Medical Surge Capability: Performance Modeling Of Hospital Emergency Departments, Egbe-Etu Emmanuel Etu

Wayne State University Dissertations

Hospitals are faced with significant challenges during and after natural or human-caused disasters. Surge planning is a critical component of every healthcare facility’s emergency plan and response system. The process of managing and allocating scarce resources by tackling the vulnerability inherent to patients means that defining improvement priorities is one of the main challenges healthcare systems face when responding to a medical surge event (e.g., COVID-19). The consequences of these challenges include increased patient mortality, ambulance diversion, long wait times, and unavailability of beds. Previous efforts in hospital operations management have successfully applied operations research techniques in analyzing and optimizing …

Maximizing User Engagement In Short Marketing Campaigns Within An Online Living Lab: A Reinforcement Learning Perspective, Aniekan Michael Ini-Abasi

Wayne State University Dissertations

ABSTRACT

MAXIMIZING USER ENGAGEMENT IN SHORT MARKETING CAMPAIGNS WITHIN AN ONLINE LIVING LAB: A REINFORCEMENT LEARNING PERSPECTIVE

by

ANIEKAN MICHAEL INI-ABASI

August 2021

Advisor: Dr. Ratna Babu Chinnam Major: Industrial & Systems Engineering Degree: Doctor of Philosophy

User engagement has emerged as the engine driving online business growth. Many firms have pay incentives tied to engagement and growth metrics. These corporations are turning to recommender systems as the tool of choice in the business of maximizing engagement. LinkedIn reported a 40% higher email response with the introduction of a new recommender system. At Amazon 35% of sales originate from recommendations, …

Integrated Optimization And Learning Methods Of Predictive And Prescriptive Analytics, Mehmet Kolcu

Wayne State University Dissertations

A typical decision problem optimizes one or more objectives subject to a set of constraints on its decision variables. Most real-world decision problems contain uncertain parameters. The exponential growth of data availability, ease of accessibility in computational power, and more efficient optimization techniques have paved the way for machine learning tools to effectively predict these uncertain parameters. Traditional machine learning models measure the quality of predictions based on the closeness between true and predicted values and ignore decision problems involving uncertain parameters for which predicted values are treated as the true values.Standard approaches passing point estimates of machine learning models …

Framework For Effective Resilience Managmenet Of Complex Supply Networks, Elham Taghizadeh

Wayne State University Dissertations

In today's environment with high global and complex supply chains for engineered products, the ability to assess and manage the resilience of supply chains is not a luxury but a fundamental prerequisite for business continuity and success. This is particularly true for firms with deep-tier supply chains, such as the automotive original equipment manufacturers (OEMs) and their suppliers. Automotive supply networks are particularly facing growing challenges due to their complexity, globalization, economic volatility, rapidly changing technologies, regulations, and environmental/political shocks. These risks and challenges can disrupt and halt operations in any section of the supply network. Given that supply chains …

Intelligent Healthcare Process Discovery And Operational Coordination Using Discrete Event Simulation And Machine Learning, Suleyman Yildirim

Wayne State University Dissertations

The healthcare system in the US is rapidly changing and reshaping to adopt continuously evolving demand for improved operational efficiency and treatment effectiveness from patients and providers in critical health services. Healthcare service systems and clinical treatment operations need to be more predictable to increase operational efficiency through proactive operations management. This research contributes to the literature by discovering clinical processes and calibrating discrete-event simulation models in healthcare service systems using data-driven and process-driven predictive models. Unlike the data-driven predictive approaches such as machine learning and statistical methods, the proposed methodologies in this thesis leverages and focuses on process-based methods …

Customer Choice Modeling For Retail Category Assortment Planning And Product-Line Extension, Elham Nosratmirshekarlou

Wayne State University Dissertations

Growing competitiveness and increasing availability of data is generating great interest in data-driven analytics across industries. One of the areas that has gained a lot of attention is Customer choice modeling, which aims to explain the choices individual customers make in choosing from a set of products based on their preferences. While effective customer choice modeling is essential to a wide variety of application domains, including retail, it is challenging in practice due to limitations around the quality of the data available for modeling and potentially complex choice behaviors. This dissertation presents a hybrid modeling approach that relies on both …

Understanding The Impact Of Virtual-Mirroring Based Learning On Collaboration In A Data And Analytics Function: A Resilience Perspective, Nabil Raad

Wayne State University Dissertations

Large multinational organizations are struggling to adapt and innovate in the face of increasing turbulence, uncertainty, and complexity. The lack of adaptive capacity is one of the major risks facing such organizations as the rapid change in technology, urbanization, socio-economic trends, and regulations continues to accelerate and outpace their ability to adapt. This is a resilience problem that organizations are addressing by investing in Data and Analytics to improve their innovation and competitive capabilities. However, Data and Analytics projects are more likely to fail than to succeed. Competing on data and analytics is not only a technical challenge but also …

Understanding The Relationship Of Innovation And Quality In A Fast-Changing Market: An Automotive Industry Perspective, Donna Leanne Bell

Wayne State University Dissertations

In a time when the consumer electronics industry is getting new products to market at a rapid rate, automotive original equipment manufacturers (OEM) must identify ways of getting new products and features to customers faster and with high quality to maintain or increase market share. This accelerated product development process requires a positive relationship between conceptual design and quality in order for a firm to have high performance in strategic areas innovation and quality. The purpose of this dissertation is to research the impact that quality practices have on the advanced product development process. Specifically, this research is focused on …

Deep Learning Based Reliability Models For High Dimensional Data, Mohammad Aminisharifabad

Wayne State University Dissertations

The reliability estimation of products has crucial applications in various industries, particularly in current competitive markets, as it has high economic impacts. Hence, reliability analysis and failure prediction are receiving increasing attention. Reliability models based on lifetime data have been developed for different modern applications. These models are able to predict failure by incorporating the influence of covariates on time-to-failure. The covariates are factors that affect the subjects’ lifetime.

Modern technologies generate covariates which can be utilized to improve failure time prediction. However, there are several challenges to incorporate the covariates into reliability models. First, the covariates generally are high …

A Structured Methodology For Tailoring And Deploying Lean Manufacturing Systems, Kenneth John Gembel Ii

Wayne State University Dissertations

The seminal works of Peter Drucker and James Womack in the 1990’s outlined the lean manufacturing practices of Toyota Motor Corporation (TMC) to become a world leader in manufacturing. These philosophies have since become the springboard for a significant paradigm shift in approaching manufacturing systems and how to leverage them to optimize operational practices and gain competitive advantage. While there is no shortage of literature touting the benefits of Lean Manufacturing Systems (LMS), there has been significant difficulty in effectively deploying them to obtain and sustain the performance that TMC has achieved.

This body of work provides a novel methodology …

Modular Product Architecture’S Decisions Support For Remanufacturing-Product Service System Synergy, Johnson Adebayo Fadeyi

Wayne State University Dissertations

Remanufacturing is identified as the most viable product end-of-life (EOL) management strategy. However, about 80% of manufactured products currently end up as wastes. Besides other benefits, the product service system (PSS) could curtail the main bottlenecks to remanufacturing namely quantity, quality, recovery time of used product, and negative perception of remanufactured products. Therefore, the integration of PSS and remanufacturing has been increasingly recommended as an enhanced product offering. However, an integration that is informed by mathematical analysis is missing. Meanwhile, the variables that bolster the performance of PSS and remanufacturing are substantially influenced by product development (PD) decisions. Among the …

Reliability Analysis By Considering Steel Physical Properties, Wujun Si

Wayne State University Dissertations

Most customers today are pursuing engineering materials (e.g., steel) that not only can achieve their expected functions but also are highly reliable. As a result, reliability analysis of materials has been receiving increasing attention over the past few decades. Most existing studies in the reliability engineering field focus on developing model-based and data-driven approaches to analyze material reliability based on material failure data such as lifetime data and degradation data, without considering effects of material physical properties. Ignoring such effects may result in a biased estimation of material reliability, which in turn could incur higher operation or maintenance costs.

Recently, …

Data-Driven Modeling For Decision Support Systems And Treatment Management In Personalized Healthcare, Milad Zafar Nezhad

Wayne State University Dissertations

Massive amount of electronic medical records (EMRs) accumulating from patients and populations motivates clinicians and data scientists to collaborate for the advanced analytics to create knowledge that is essential to address the extensive personalized insights needed for patients, clinicians, providers, scientists, and health policy makers. Learning from large and complicated data is using extensively in marketing and commercial enterprises to generate personalized recommendations. Recently the medical research community focuses to take the benefits of big data analytic approaches and moves to personalized (precision) medicine. So, it is a significant period in healthcare and medicine for transferring to a new paradigm. …

A Data-Driven And Mixed Methods Analysis Of Automotive Retail Operations Management, Mark Allen Colosimo

Wayne State University Dissertations

The importance of effective retail operations management has never been more significant. Our research aims to expand the understanding for efficiency and dynamics of franchise outlets within retail networks with a focus on sales performance and profitability. The focus and contribution is the development of an actionable data analytics driven process by which automotive dealerships (retail outlets) can be analyzed to identify areas of opportunity for improvement. In general, automotive dealerships aim to sell product to make a profit, the manufacturer of the product/brand desires to sell vehicles to make a profit, and the customer desires to find a suitable …

An Agile Quality Management System For Laboratory Developed Tests, Rita D'Angelo

Wayne State University Dissertations

ABSTRACT

AN AGILE QUALITY MANAGEMENT SYSTEM FOR LABORATORY DEVELOPED TESTS

By

RITA D’ANGELO

MAY 2017

Advisor: Dr. Ratna Babu Chinnan

Major: Industrial & Systems Engineering

Degree: Doctor of Philosophy Statement of the Problem: We explore the 2014 draft guidance by the FDA entitled Framework for Regulatory Oversight of Laboratory Developed Tests (LDT) extended from the medical device industry and discuss how these requirements may be applicable to laboratory medicine. We introduce terms, definitions and provide a call for action for leaders to prepare for the potential adherence to regulatory requirements and explore if compliance was achievable in a laboratory environment …

Enhancing Set-Based Design To Engineer Resilience For Long-Lived Systems, Gregory Hartman

Wayne State University Dissertations

At the heart of Set-Based Design is the concept that down-select decisions are deferred until sufficient information is available to make a decision, i.e., a set of possible solutions is maintained. Due to the extended service lives of many of our current and future systems, the horizon for accurately predicting the system’s requirement is shorter than the service life, so the needed information to down-select to a single optimized solution is unavailable at the time of fielding. Set-Based Design can, however, be extended to explicitly carry a set of possible solutions past the point of the initial fielding of the …

Influential Factors In Consumer's Adoption Of Innovative Products, Mahdokht Kalantari

Wayne State University Dissertations

This dissertation addresses the challenges involved with the process of diffusion of innovations in the contexts of innovative educational materials and technological innovations.

Chapters 2 and 3 discuss building and using Online Brand Communities (OBCs) to disseminate innovative math educational materials. OBCs are known to be important platforms where consumers can communicate with the brand as well as other consumers. Through the effective use of these platforms, brands could accelerate the process of diffusion of their innovations. However, OBCs will not survive if consumers do not get engaged and participate in these communities. The purpose of this section of the …

Venous Thromboembolism (Vte) Harm Measurement And Risk Assessment In Real-Time Using Electronic Health Records(Ehr), Seyed Mani Marashi

Wayne State University Dissertations

Venous Thromboembolism (VTE) is a deadly disease and is considered as one of the top reasons for avoidable hospital deaths in the United States and around the world. Patients who survive this disease often must face life-long complications such as Post-thrombotic syndrome (PTS), Chronic thromboembolic pulmonary hypertension (CTPH), etc. Therefore, it is important to monitor and reduce the number of VTE instances in hospitals. This study shows how Electronic Health Records (EHRs) can be utilized to achieve this goal.

First, a new near real-time VTE harm measurement model was developed. Not only the developed model can deliver near real-time results, …

Developing Innovation Capability In A Mass Production Organization, Mark Douglas Dolsen

Wayne State University Dissertations

ABSTRACT

DEVELOPING INNOVATION CAPABILITY IN A MASS PRODUCTION ORGANIZATION

by

MARK DOLSEN

May 2017

Advisor: Dr. Ratna Babu Chinnam

Major: Industrial Engineering

Degree: Doctor of Philosophy

Auto parts manufacturing is a key element of the North American automotive supply chain, and a significant component of the economy of Ontario, Canada. Employment in this sector declined 40% from 2003 to 2010 as the industry experienced a recession, and many firms relocated to lower wage jurisdictions as the Canadian currency strengthened against the US dollar. Experts contend that the solution for the industry lies in innovation; however, recommendations found in the current …

Human-Machine Interface Development For Modifying Driver Lane Change Behavior In Manual, Automated, And Shared Control Automated Driving, Walter Joseph Talamonti

Wayne State University Dissertations

Rear-end crashes are common on U.S. roads. Driver assistance and automated driving technologies can reduce rear-end crashes (among other crash types as well). Braking is assumed for forward collision warning (FCW) and automatic emergency braking (AEB) systems. Braking is also used for adaptive cruise control (ACC) and in automated driving systems more generally. However, steering may be advised in an emergency if the adjacent lane is clear and braking is unlikely to avoid a collision. Steering around an obstacle when feasible also eliminates the risk of becoming the new forward collision hazard. Driver assist technology like emergency steer assist (ESA) …

Evolving Clustering Algorithms And Their Application For Condition Monitoring, Diagnostics, & Prognostics, Fling Finn Tseng

Wayne State University Dissertations

Applications of Condition-Based Maintenance (CBM) technology requires effective yet generic data driven methods capable of carrying out diagnostics and prognostics tasks without detailed domain knowledge and human intervention. Improved system availability, operational safety, and enhanced logistics and supply chain performance could be achieved, with the widespread deployment of CBM, at a lower cost level. This dissertation focuses on the development of a Mutual Information based Recursive Gustafson-Kessel-Like (MIRGKL) clustering algorithm which operates recursively to identify underlying model structure and parameters from stream type data. Inspired by the Evolving Gustafson-Kessel-like Clustering (eGKL) algorithm, we applied the notion of mutual information to …

Product Development Resilience Through Set-Based Design, Stephen H. Rapp

Wayne State University Dissertations

Often during a system Product Development program external factors or requirements change, forcing system design change. This uncertainty adversely affects program outcome, adding to development time and cost, production cost, and compromise to system performance. We present a development approach that minimizes the impacts, by considering the possibility of changes in the external factors and the implications of mid-course design changes. The approach considers the set of alternative designs and the burdens of a mid-course change from one design to another in determining the relative value of a specific design. The approach considers and plans parallel development of alternative designs …

Knowledge Reuse Through Electronic Knowledge Repositories: An Empirical Study And Ontological Improvement Effort For The Manufacturing Industry, Peter Panha Chhim

Wayne State University Dissertations

Knowledge management adoption is growing, and will continue to grow in no small part because of its recent inclusion into the ISO 9001 quality standard. As organizations look towards ways in which to manage their knowledge, the codification of explicit knowledge through Knowledge Management Systems (KMS) and Electronic Knowledge Repositories (EKRs) will undoubtedly gain more interest.

An EKR is a form of KMS that emphasizes the codification and storage of organizational expertise for the purposes of Knowledge Reuse (KRU). Unfortunately, the factors surrounding KRU are not well understood. While previous studies have viewed EKR usage from a narrow perspective, a …

Computational Modeling Approaches For Task Analysis In Robotic-Assisted Surgery, Mahtab Jahanbani Fard

Wayne State University Dissertations

Surgery is continuously subject to technological innovations including the introduction of robotic surgical devices. The ultimate goal is to program the surgical robot to perform certain difficult or complex surgical tasks in an autonomous manner. The feasibility of current robotic surgery systems to record quantitative motion and video data motivates developing descriptive mathematical models to recognize, classify and analyze surgical tasks. Recent advances in machine learning research for uncovering concealed patterns in huge data sets, like kinematic and video data, offer a possibility to better understand surgical procedures from a system point of view. This dissertation focuses on bridging the …

Technology Decisions In New Product Development, Amir Sanayei

Wayne State University Dissertations

Selecting the right technology is one of the most important and challenging decisions in new product development (NPD) process that can greatly affect all downstream design activities which have a great impact on product success in the market place. Although new technologies may bring more competitive advantage by offering higher performance to price, they also make the NPD process more risky and challenging. We model the technology selection problem of a firm that is defining its new product in the presence of the technology uncertainty. At each review stage, firm has the options: select and commit to any technology alternatives …

A Framework To Improve A Nation's Competitiveness Through Quality Awards And Performance Improvement Tools, Amr Alamri

Wayne State University Dissertations

Each country, represented by its government, aims to serve its citizens better. This is achieved by better utilization of resources and higher productivity. The ability to do so will lead to a competitive nation. Recently, countries were able to compare themselves in terms of competitiveness using international indexes and references. These references gave countries a benchmark to know where they exist compared to other nations. They help governments to understand their strengths and weaknesses within the competitiveness components. However, nations differ in the actions which are to be taken in order to improve their competitiveness. Governments establish and regulate many …

Lean Thinking For Lead-Time Reduction And Efficient Knowledge Creation In Product Development, Satish Kumar Tyagi

Wayne State University Dissertations

There are many distinct differences between manufacturing process and Product Development (PD) process, so lean tools have to be customized to deliver results in the later domain. The main focus of this dissertation is to extend them to manage and improve the PD process in order to develop the product faster while improving or at least maintaining the level of performance and quality. For aforesaid purpose, value stream mapping (VSM) method is used to explore the wastes, inefficiencies, non-valued added steps in a single, definable process out of complete PD process. Besides numerous intangible benefits, VSM framework will help the …

Modeling And Optimization Of Non-Profit Hospital Call Centers With Service Blending, Yanli Zhao

Wayne State University Dissertations

This dissertation focuses on the operations problems in non-profit hospital call centers with inbound and outbound calls service blending.

First, the routing policy for inbound and outbound calls is considered. The objective is to improve the system utilization under constraints of service quality and operators' quantity. A collection of practical staffing assignment methods, separating and mixing staffing policy are evaluated. Erlang C queuing model is used to decide the minimum number of operators required by inbound calls. Theoretical analysis and numerical experiments illustrate that through dynamically assigning the inbound and outbound calls to operators under optimal threshold policy, mixing staffing …

Reliability Analysis And Optimal Maintenance Planning For Repairable Multi-Component Systems Subject To Dependent Competing Risks, Nailong Zhang

Wayne State University Dissertations

Modern engineering systems generally consist of multiple components that interact in a complex manner. Reliability analysis of multi-component repairable systems plays a critical role for system safety and cost reduction. Establishing reliability models and scheduling optimal maintenance plans for multi-component repairable systems, however, is still a big challenge when considering the dependency of component failures. Existing models commonly make prior assumptions, without statistical verification, as to whether different component failures are independent or not. In this dissertation, data-driven systematic methodologies to characterize component failure dependency of complex systems are proposed. In CHAPTER 2, a parametric reliability model is proposed to …