Industrial Engineering Commons^™

Spatial Markov Equilibrium Models For Taxi Services: Driver Decision, Search Friction, And Locational Pricing, Yanchao Liu

Industrial and Systems Engineering Faculty Research Publications

This paper develops a modeling framework for stochastic multi-agent systems and applies it to equilibrium and pricing analysis in urban taxi markets. Travel demand is represented as a trip network and embedded in a Markov chain that captures both locational and in transit taxi states, with transition dynamics reflecting trip durations, search frictions, spatial competition, and drivers’ perceptions of long-term value. The framework features a parametric Markov chain with endogenous transition probabilities and a behavioral model in which agents’ decisions depend on anticipated long-term rewards. We establish equilibrium existence and examine two locational pricing schemes that align individual incentives with …

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

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 …

An Elliptical Cover Problem In Drone Delivery Network Design And Its Solution Algorithms, Yanchao Liu

Industrial and Systems Engineering Faculty Research Publications

Given n demand points in a geographic area, the elliptical cover problem is to determine the location of p depots (anywhere in the area) so as to minimize the maximum distance of an economical delivery trip in which a delivery vehicle starts from the nearest depot to a demand point, visits the demand point and then returns to the second nearest depot to that demand point. We show that this problem is NP-hard, and adapt Cooper’s alternating locate-allocate heuristic to find locally optimal solutions for both the point-coverage and area-coverage scenarios. Experiments show that most locally optimal solutions perform similarly …

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

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

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

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

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

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

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

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

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

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

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

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

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

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 …

Economic Model Predictive Control And Process Equipment: Control-Induced Thermal Stress In A Pipe, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Recent work on economic model predictive control (EMPC) has indicated that some processes may be operated in a more economically-optimal fashion under a time-varying operating policy than under a steady-state operating policy. However, a concern for time-varying operation is how such a change in operating policy might impact the equipment within which the processes being controlled are carried out. While under steady-state operation, the operating conditions to which equipment would regularly be exposed can be estimated, this would be more difficult to assess thoroughly a priori under time-varying operation. It could be explored whether the EMPC could be made aware …

On Accounting For Equipment-Control Interactions In Economic Model Predictive Control Via Process State Constraints, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Traditionally, chemical processes have been operated at steady-state; however, recent work on economic model predictive control (EMPC) has indicated that some processes may be operated in a more economically-optimal fashion under a time-varying operating policy. It is unclear how time-varying operating policies may impact process equipment, which must be investigated for safety and profit reasons. It has traditionally been considered that constraints on process states can be added to EMPC design to prevent the controller from computing control actions which create problematic operating conditions for process equipment. However, no rigorous investigation has yet been performed to analyze whether, when a …

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

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

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

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 …

Economic Model Predictive Control Design Via Nonlinear Model Identification, Laura Giuliani, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Increasing pushes toward next-generation/smart manufacturing motivate the development of economic model predictive control (EMPC) designs which can be practically deployed. For EMPC, the constraints, objective function, and accuracy of the state predictions would benefit from process models that describe the process physics. However, obtaining first- principles models of chemical process systems can be time-consuming or challenging such that it is preferable to develop physics-based process models automatically from process operating data. In this work, we take initial steps in this direction by suggesting that because experiments that are used to characterize first-principles models often target specific types of data, an …

Data-Based Nonlinear Model Identification In Economic Model Predictive Control, Laura Giuliani, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Many chemical/petrochemical processes in industry are not completely modeled from a first-principles perspective because of the complexity of the underlying physico-chemical phenomena and the cost of obtaining more accurate, physically relevant models. System identification methods have been utilized successfully for developing empirical, though not necessarily physical, models for advanced model-based control designs such as model predictive control (MPC) for decades. However, a fairly recent development in MPC is economic model predictive control (EMPC), which is an MPC formulated with an economics-based objective function that may operate a process in a dynamic (i.e., off steady-state) fashion, in which case the details …

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

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

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

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. …