Operations Research, Systems Engineering and Industrial Engineering Commons^™

Integrated Cyberattack Detection And Handling For Nonlinear Systems With Evolving Process Dynamics Under Lyapunov-Based Economic Model Predictive Control, Keshav Kasturi Rangan, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Safety-critical processes are becoming increasingly automated and connected. While automation can increase effciency, it brings new challenges associated with guaranteeing safety in the presence of uncertainty especially in the presence of control system cyberattacks. One of the challenges for developing control strategies with guaranteed safety and cybersecurity properties under suffcient conditions is the development of appropriate detection strategies that work with control laws to prevent undetected attacks that have immediate closed-loop stability consequences. Achieving this, in the presence of uncertainty brought about by plant/model mismatch and process dynamics that can change with time, requires a fundamental understanding of the characteristics …

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. …

The Impact Of Machine Learning Algorithms On Benchmarking Process In Healthcare Service Delivery, Egbe-Etu Emmanuel Etu

Wayne State University Theses

Currently, organizations have adopted and implemented a variety of innovative quality management philosophies, approaches, and techniques to stay competitive in an ever-changing global economy. Benchmarking is one of such techniques deployed by organizations to stay competitive. The motivation for this research stems from a real-world problem being faced by hospitals in the healthcare industry who have amassed a ton of data and want to embark on benchmarking project to assess the performance of the emergency departments due to challenges faced with poor management of operations which has led to high patient boarding rates, high patient wait-times, poor quality service, low …

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 …

A Prediction Modeling Framework For Noisy Welding Quality Data, Junheung Park

Wayne State University Dissertations

Numerous and various research projects have been conducted to utilize historical manufacturing process data in product design. These manufacturing process data often contain data inconsistencies, and it causes challenges in extracting useful information from the data. In resistance spot welding (RSW), data inconsistency is a well-known issue. In general, such inconsistent data are treated as noise data and removed from the original dataset before conducting analyses or constructing prediction models. This may not be desirable for every design and manufacturing applications since every data can contain important information to further explain the process. In this research, we propose a prediction …

Developing An Automated Forecasting Framework For Predicting Operation Room Block Time, Azad Sadr Haghighi

Wayne State University Theses

Operating rooms are the most important part of the hospitals, since they have highest influence on financial state of the hospital. Because of high uncertainty in surgery cases demands and their durations, the scheduling of the surgeries becomes a very challenging and critical issue in hospitals. One of the most common approaches to overcome this uncertainty is applying block times which is the time intervals allocated to surgery groups in the hospital. Assigning sufficient amount of the time to each block, is very important, since overestimating lead to wasting resources and on the other hand underestimation causes the overtime staffing …

A Customer Choice Modeling Framework For Assortment Planning Of Configurable Products In Automotive Industry, Farah Dubaisi

Wayne State University Theses

Due to the increased competition in the auto industry, proliferation of the vehicle models and increased customer need for choice and customization, it has become more critical than ever to offer a variety of features and customization flexibility while at the same time restraining and, even better, cutting down the costs. Product complexity, in the automotive industry, can be measured by the size of the assortment offered, i.e., set of vehicle configurations a customer can choose from (e.g., for a given model of a brand). While complexity fosters growth with increased alignment of product characteristics and customer needs, it results …

Predictive Analytics For Disease Condition Of Patients In Emergency Department, Azade Tabaie

Wayne State University Theses

Emergency Departments (EDs) in hospitals are experiencing severe crowding and prolonged patient waiting times. The reported crowding in hospitals shows patients in hospital hallways, long waiting times and full occupancy of ED beds. ED crowding has several potential unfavorable effects including patients and staff frustration, lower patient satisfaction and poor health outcomes. The primary motivations behind this study are shortening the patients’ waiting time and improving patient satisfaction and level of care.

The very initial interaction between clinicians and a patient is recorded on nurse triage notes which contain details of the reason for patient’s visit including specific symptoms and …

Comparison Of Individual And Moving Range Chart Combinations To Individual Charts In Terms Of Arl After Designing For A Common “All Ok” Arl, Dewi Rahardja

Journal of Modern Applied Statistical Methods

In some process monitoring situations, consecutive measurements are spaced widely apart in time, making monitoring process aim and spread difficult. This study uses three cases to compare the effectiveness of two such monitoring schemes, i.e., the X chart alone (X-only chart) and the Individuals and Moving Range Chart Combination (X/MR chars), in terms of Average Run Length (ARL) after designing for a common “all OK” (in-control) ARL. The study finds that X chart alone is sufficient (and hence, recommended) in detecting changes in all the 3 cases: changes in the process mean, changes in the process standard deviation, and changes …

A Decision Modeling For Phasor Measurement Unit Location Selection In Smart Grid Systems, Seung Yup Lee

Wayne State University Theses

As a key technology for enhancing the smart grid system, Phasor Measurement Unit (PMU) provides synchronized phasor measurements of voltages and currents of wide-area electric power grid. With various benefits from its application, one of the critical issues in utilizing PMUs is the optimal site selection of units.

The main aim of this research is to develop a decision support system, which can be used in resource allocation task for smart grid system analysis. As an effort to suggest a robust decision model and standardize the decision modeling process, a harmonized modeling framework, which considers operational circumstances of component, is …

Optimization Of Strategic Planning Processes For Configurable Products: Considerations For Global Supply, Demand, And Sustainability Issues, Edward Lawrence Umpfenbach

Wayne State University Dissertations

The assortment planning problem is to decide on the set of products that a retailer or manufacturer will offer to its customers to maximize profitability. While assortment planning research has been expanding in recent years, the current models are inadequate for the needs of a configurable product manufacturer. In particular, we address assortment planning for an automobile manufacturer. We develop models to integrate assortment planning and supply chain management, designed for use by a large automaker in its strategic planning phase. Our model utilizes a multinomial logit model transformed into a mixed integer linear program through the Charnes-Cooper transformation. It …

A Framework For Personalized Dynamic Cross-Selling In E-Commerce Retailing, Arun K. Timalsina

Wayne State University Dissertations

Cross-selling and product bundling are prevalent strategies in the retail sector. Instead of static bundling offers, i.e. giving the same offer to everyone, personalized dynamic cross-selling generates targeted bundle offers and can help maximize revenues and profits. In resolving the two basic problems of dynamic cross-selling, which involves selecting the right complementary products and optimizing the discount, the issue of computational complexity becomes central as the customer base and length of the product list grows. Traditional recommender systems are built upon simple collaborative filtering techniques, which exploit the informational cues gained from users in the form of product ratings and …

Self Learning Strategies For Experimental Design And Response Surface Optimization, Adel Alaeddini

Wayne State University Dissertations

Most preset RSM designs offer ease of implementation and good performance over a wide range of process and design optimization applications. These designs often lack the ability to adapt the design based on the characteristics of application and experimental space so as to reduce the number of experiments necessary. Hence, they are not cost effective for applications where the cost of experimentation is high or when the experimentation resources are limited. In this dissertation, we present a number of self-learning strategies for optimization of different types of response surfaces for industrial experiments with noise, high experimentation cost, and requiring high …

Task Analysis, Modeling, And Automatic Identification Of Elemental Tasks In Robot-Assisted Laparoscopic Surgery, Lavie Pinchas Golenberg

Wayne State University Dissertations

Robotic microsurgery provides many advantages for surgical operations, including tremor filtration, an increase in dexterity, and smaller incisions. There is a growing need for a task analyses on robotic laparoscopic operations to understand better the tasks involved in robotic microsurgery cases. A few research groups have conducted task observations to help systems automatically identify surgeon skill based on task execution. Their gesture analyses, however, lacked depth and their class libraries were composed of ambiguous groupings of gestures that did not share contextual similarities.

A Hierarchical Task Analysis was performed on a four-throw suturing task using a robotic microsurgical platform. Three …