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Wayne State University Dissertations

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Full-Text Articles in Industrial Engineering

Product Development Resilience Through Innovation Management And Agile Efficiency Design, Anna Nguyen Jan 2023

Product Development Resilience Through Innovation Management And Agile Efficiency Design, Anna Nguyen

Wayne State University Dissertations

ABSTRACT

PRODUCT DEVELOPMENT RESILIENCE THROUGH INNOVATION MANAGEMENT AND AGILE EFFICIENCY DESIGN

by

ANNA NGUYEN

December 2023

Advisor: Dr. Kai YangMajor: Industrial Engineering Degree: Doctor of Philosophy In recent years there have been constantly changing innovation technology, economic inflation, and material costs considering the various headwinds that the Automotive Industry faced. To adapt to these rapid changes or under non-standard timing circumstances, Auto Parts Manufacturing focuses on technically advanced design-thinking and engineering competency but has limited the manufacturers’ visibility of new product development and control of operations on a global level. Mass production firms focus on identifying new technology but more …


Managing The Success Of Tpm Deployment & Sustainment In The Automotive Industry, Kevin Gembel Jan 2023

Managing The Success Of Tpm Deployment & Sustainment In The Automotive Industry, Kevin Gembel

Wayne State University Dissertations

Maintenance has assumed increased importance in manufacturing as companies look for ways to gain an advantage over their competitors. The philosophical benefits of jointly implementing Total Productive Maintenance (TPM) programs in concert with other lean and quality programs have been discussed in the manufacturing literature. However, there is an absence of real-life implementation studies for objective assessment. To the best of our knowledge, this is the very first longitudinal study to investigate the implementation of TPM programs at a large global OEM across several regions and facilities using objective data collected across all key functions and outcomes. We study a …


Data-Driven Semantic Modeling For Welding Assemblies, Fahim Ahmed Jan 2022

Data-Driven Semantic Modeling For Welding Assemblies, Fahim Ahmed

Wayne State University Dissertations

A significant information gap is prevalent between the design domain and the manufacturing domain. The designers lack manufacturing awareness as they have little knowledge regarding the manufacturability of their designs. The welding domain falls prey to this issue as designers lack manufacturing awareness and welding engineers lack weldability of the product assembly. Data-driven techniques have shown promising results in the analysis and understanding of complex welding processes. Data analytics play a significant role to turn data into valuable insights to assist in the weldability certification decision-making or weldability prediction for Resistance Spot Welding (RSW) as well. We have used machine …


Optimization-Based Uav Fleet Routing And Safety Assurance – Models, Algorithms, And Prototyping, Zhenyu Zhou Jan 2022

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 …


Automotive Product Assortment Planning With Consideration Of Distribution Channel Dynamics, Madagedara Maduka Rushanjalee Balasooriya Jan 2022

Automotive Product Assortment Planning With Consideration Of Distribution Channel Dynamics, Madagedara Maduka Rushanjalee Balasooriya

Wayne State University Dissertations

Automotive original equipment manufacturers (OEMs) are putting a lot of effort into maintaining an efficient order catalog to offer better products to their customers in maketo-stock (MTS) markets. While product “assortment planning" research grows to more effectively identify the best assortments for OEMs, the existing configurable assortment planning literature ignores a significant dimension: the impact of distribution channels, especially dealer franchise networks. Dealers face unique challenges in trying to best satisfy the choice preferences of their local consumers by balancing their limited product configuration inventory with profitability. In many predominantly MTS automotive markets such as the U.S., the reality is …


Improving Or Operations Using Machine Learning Techniques, Tannaz Khaleghi Jan 2022

Improving Or Operations Using Machine Learning Techniques, Tannaz Khaleghi

Wayne State University Dissertations

Recently, health care related studies are being widely conducted by researchers using unique and efficient techniques to increase system profitability, quality of care, and patient satisfaction. Surgery department is considered as the hospital's engine, and cost of surgical services has a huge impact on the overall profitability of the hospital. This thesis proposes novel approaches to improve the efficiency of surgical services by using machine learning concepts.

In the first part, this research investigates the prediction of the surgery durations and Current Procedural Terminology (CPT) Codes. Accurate prediction of the surgery duration will improve the utilization of indispensable surgical resources …


Acute Coronary Syndrome Prediction: A Data-Driven Machine Learning Modeling Approach In Emergency Care, Joshua Oluwatobiloba Emakhu Jan 2022

Acute Coronary Syndrome Prediction: A Data-Driven Machine Learning Modeling Approach In Emergency Care, Joshua Oluwatobiloba Emakhu

Wayne State University Dissertations

Healthcare facilities are faced with significant challenges all year round, with patients presenting to the emergency department (ED) with different health issues. Of these challenges, heart disease seems to be an outlier. With heart disease being the primary cause of mortality and morbidity in both developed and developing countries, clinical concerns for acute coronary syndrome (ACS) are one of emergency medicine’s most common patient encounters. Of the three sub-categories of ACS, non-ST-segment elevation myocardial infarction (NSTEMI) has a long-term impact on the well-being of patients if left untreated. Previous efforts in hospital management have applied machine learning algorithms in differentiating …


A Combined Additive - Deformation - Machining (Adm) Manufacturing Process With Controlled Microstructures, Ahmed Nabil Taher Elalem Jan 2022

A Combined Additive - Deformation - Machining (Adm) Manufacturing Process With Controlled Microstructures, Ahmed Nabil Taher Elalem

Wayne State University Dissertations

ABSTRACTA COMBINED ADDITIVE - DEFORMATION - MACHINING (ADM) MANUFACTURING PROCESS WITH CONTROLLED MICROSTRUCTURES by AHMED NABIL TAHER ELALEM August 2022

Advisor: Dr. Xin WuMajor: Mechanical Engineering Degree: Doctor of Philosophy

Direct metal additive manufacturing provides great flexibility in 3D shaping compared to traditional manufacturing processes of metal casting, deformation followed by machining and joining for obtaining the final production shape. On the other hand, it suffered from its dendric microstructure produced during solidification. This study reports the development of new combined metal additive and deformation processes to take advantage and reduce/eliminate the drawback of individual processes. The heating source mainly …


Intelligent Healthcare Process Discovery And Operational Coordination Using Discrete Event Simulation And Machine Learning, Suleyman Yildirim Jan 2021

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 …


Medical Surge Capability: Performance Modeling Of Hospital Emergency Departments, Egbe-Etu Emmanuel Etu Jan 2021

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 …


Methods To Integrate Domain Expert User Knowledge Into Process Discovery, Jasim Alnahas Jan 2021

Methods To Integrate Domain Expert User Knowledge Into Process Discovery, Jasim Alnahas

Wayne State University Dissertations

Process Mining (PM) is a new era in business development management that reinforces business process sustainability. Process Mining uses various techniques to discover the process model and identify the root cause analysis of process delays based on the event log. There are three main types of process models: procedural models, declarative models, and hybrid models. Procedural models tend to discover the main pattern of the activity flows in the process. In contrast, declarative models analyze the process behavior and express this behavior as a compact set of rules between pair of two activities. Hybrid models are a combination of procedural …


Integrated Optimization And Learning Methods Of Predictive And Prescriptive Analytics, Mehmet Kolcu Jan 2021

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 …


Predicting The Geometrical Disassembly Feasibility Of Mechanical Assemblies In Design Phase, Header Alrufaifi Jan 2021

Predicting The Geometrical Disassembly Feasibility Of Mechanical Assemblies In Design Phase, Header Alrufaifi

Wayne State University Dissertations

Disassembly of products has gained more and more attention due to the economic, environmental, and social benefits and the contribution to the protection of natural resources [1]. Where, disassembly is the first and usually the most critical and challenging process in most recovery processes (i.e. remanufacturing, reuse, maintenance, and recycling processes) which are essential reverse flows in circular economy systems. As policies, regulations, products, and systems move towards and strive for a circular economy, it is increasingly vital that disassembly analysis, models, and methods are feasible during development and manufacturing life-cycle stages. However, checking disassembly feasibility is considered a critical …


Framework For Effective Resilience Managmenet Of Complex Supply Networks, Elham Taghizadeh Jan 2021

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 …


Maximizing User Engagement In Short Marketing Campaigns Within An Online Living Lab: A Reinforcement Learning Perspective, Aniekan Michael Ini-Abasi Jan 2021

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, …


Customer Choice Modeling For Retail Category Assortment Planning And Product-Line Extension, Elham Nosratmirshekarlou Jan 2020

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 …


A Structured Methodology For Tailoring And Deploying Lean Manufacturing Systems, Kenneth John Gembel Ii Jan 2019

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 …


Understanding The Relationship Of Innovation And Quality In A Fast-Changing Market: An Automotive Industry Perspective, Donna Leanne Bell Jan 2019

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 …


Understanding The Impact Of Virtual-Mirroring Based Learning On Collaboration In A Data And Analytics Function: A Resilience Perspective, Nabil Raad Jan 2019

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 …


Deep Learning Based Reliability Models For High Dimensional Data, Mohammad Aminisharifabad Jan 2019

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 …


Enhancing Set-Based Design To Engineer Resilience For Long-Lived Systems, Gregory Hartman Jan 2018

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 …


An Agile Quality Management System For Laboratory Developed Tests, Rita D'Angelo Jan 2018

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 …


Modular Product Architecture’S Decisions Support For Remanufacturing-Product Service System Synergy, Johnson Adebayo Fadeyi Jan 2018

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 …


Data-Driven Modeling For Decision Support Systems And Treatment Management In Personalized Healthcare, Milad Zafar Nezhad Jan 2018

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. …


Reliability Analysis By Considering Steel Physical Properties, Wujun Si Jan 2018

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, …


A Data-Driven And Mixed Methods Analysis Of Automotive Retail Operations Management, Mark Allen Colosimo Jan 2018

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 …


Venous Thromboembolism (Vte) Harm Measurement And Risk Assessment In Real-Time Using Electronic Health Records(Ehr), Seyed Mani Marashi Jan 2018

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, …


Influential Factors In Consumer's Adoption Of Innovative Products, Mahdokht Kalantari Jan 2018

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 …


Developing Innovation Capability In A Mass Production Organization, Mark Douglas Dolsen Jan 2017

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 …


Product Development Resilience Through Set-Based Design, Stephen H. Rapp Jan 2017

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 …