Since 2008, the world has been in recession. As daily news outlets report, this crisis has prompted many small businesses and large corporations to file for bankruptcy, which has grave global social implications. Despite government intervention and incentives to stimulate the economy that have put nations in hundreds of billions of dollars of debt, and have reduced the prime rates to almost zero, efforts to combat the increase in unemployment rate as well as the decrease in discretionary income have been troublesome. It is a vicious cycle: consumers are apprehensive of spending due to the instability of their jobs and ensuing personal financial problems; businesses are weary from the lack of revenue and are forced to tighten their operations which likely translates to layoffs; and so on. Cautious movement of cash flows are rooted in and influenced by the psychology of the players (stakeholders) of the game (society). Understandably, the complexity of this economic fallout is the subject of much attention. And while the markets have recovered much of the lost ground as of late, there is still great opportunity to learn about all the possible factors of this recession, in anticipation of and bracing for one more downturn before we emerge from this crisis. In fact, there is no time like today more appropriate for research in bankruptcy prediction because of its relevance, and in an age where documentation is highly encouraged and often mandated by law, the amount and accessibility of data is paramount – an academic’s paradise! The main objective of this thesis was to develop a model supported by Data Envelopment Analysis (DEA) to predict the likelihood of failure of US companies in the retail-apparel industry based on information available from annual reports – specifically from financial statements and their corresponding Notes, Management’s Discussion and Analysis, and Auditor’s Report. It was hypothesized that the inclusion of variables which reflect managerial decision-making and economic factors would enhance the predictive power of current mathematical models that consider financial data exclusively. With a unique and comprehensive dataset of 85 companies, new metrics based on different aspects of the annual reports were created then combined with a slacks-based measure of efficiency DEA model and modified layering classification technique to capture the multidimensional complexity of bankruptcy. This approach proved to be an effective prediction tool, separating companies with a high risk of bankruptcy from those that were healthy, with a reliable accuracy of 80% – an improvement over the widely-used Altman bankruptcy model having 70%, 58% and 50% accuracy when predicting cases today, from one year back and from two years back, respectively. It also provides a probability of bankruptcy based on a second order polynomial function in addition to targets for improvement, and was designed to be easily adapted for analysis of other industries. Finally, the contributions of this thesis benefit creditors with better risk assessment, owners with time to improve current operations as to avoid failure altogether, as well as investors with information on which healthy companies to invest in and which unhealthy companies to short.

Radiation treatment planning is a process through which a certain plan is devised in order to irradiate tumors or lesions to a prescribed dose without posing surrounding organs to the risk of receiving radiation. A plan comprises a series of shots at di erent positions with di erent shapes. The inverse planning approach which we propose utilizes certain optimization techniques and builds mathematical models to come up with the right location and shape, for each shot, automating the whole process. The models which we developed for PerfexionTM unit (Elekta, Stockholm, Sweden), in essence, have come to the assistance of oncologists in automatically locating isocentres and de ning sector durations. Sector duration optimization (SDO) and sector duration and isocentre location optimization (SDIO) are the two classes of these models. The SDO models, which are, in fact, variations of equivalent uniform dose optimization model, are solved by two nonlinear optimization techniques, namely Gradient Projection and our home-developed Interior Point Constraint Generation. In order to solve SDIO model, a commercial optimization solver has been employed. This study undertakes to solve the isocentre selection and sector duration optimization. Moreover, inverse planning is evaluated, using clinical data, throughout the study. The results show that automated inverse planning contributes to the quality of radiation treatment planning in an unprecedentedly optimal fashion, and signi cantly reduces computation time and treatment time.

Reducing emergency department (ED) wait times are a major priority for the Ontario Government. Overcrowded EDs, cumulative effects of the delays in hospital processes and lack of resources are manifested in the phenomenon of long wait times. This thesis aims to estimate in real-time, a minimum wait time confidence interval for urgent abdominal pain patients on weekdays based on ED operations, waiting room status and ED census indicators through multivariate backwards stepwise regression modeling. The ED wait times model accurately predicted a 95% wait time confidence interval for patients. Common underlying factors attributed to long wait times include the total number of emergent and urgent patients in the waiting room, the total number of patient waiting for a consultation and the number of patients not seen within the Ontario Government’s target times. This information is useful in managing patient expectations and appropriately allocating resources to improve wait times.

Master of Science / Department of Industrial & Manufacturing Systems Engineering / Todd W. Easton / Integer programming is a useful tool for modeling and optimizing real world problems. Unfortunately, the time required to solve integer programs is exponential, so real world problems often cannot be solved. The knapsack problem is a form of integer programming that has only one constraint and can be used to strengthen cutting planes for general integer programs. These facts make finding new classes of facet-defining inequalities for the knapsack problem an extremely important area of research. This thesis introduces three set inequalities (TSI) and an algorithm for finding them. Theoretical results show that these inequalities will be of dimension at least 2, and can be facet defining for the knapsack problem under certain conditions. Another interesting aspect of these inequalities is that TSIs are some of the first facet-defining inequalities for knapsack problems that are not based on covers. Furthermore, the algorithm can be extended to generate multiple inequalities by implementing an enumerative branching tree. A small computational study is provided to demonstrate the effectiveness of three set inequalities. The study compares running times of solving integer programs with and without three set inequalities, and is inconclusive.

Doctor of Philosophy / Department of Industrial & Manufacturing Systems Engineering / Zhijian Pei / Donghai Wang / In the U.S. and many other countries, the transportation sector is almost entirely dependent on petroleum-based fuels. In 2011, half of the petroleum used in the U.S. was imported. The dependence on foreign petroleum is a real threat to national energy security. Furthermore, the transportation sector is responsible for about 30% of U.S. greenhouse gas emissions and is growing faster than any other major economic sector. National energy security, economy, environment sustainability are all driving the U.S. to develop alternative liquid transportation fuels that are domestically produced and environmentally friendly. Promoting biofuel is one of the efforts to reduce the use of petroleum-based fuels in the transportation sector. Cellulosic biomass are abundant and diverse. Thus, the ability to produce biofuel from cellulosic biomass will be a key to making ethanol competitive with petroleum-based fuels. Ultrasonic vibration- assisted (UV-A) pelleting can increase not only the density of cellulosic biomass but also the sugar yield. This PhD dissertation consists of fourteen chapters. Firstly, an introduction of the research is given in Chapter 1. Chapters 2, 3, 4, and 5 present experimental investigations on effects of input variables in UV-A pelleting on pellet quality. Chapter 6 investigates effects of input variables on energy consumption in UV-A pelleting. Chapter 7 develops a predictive model for energy consumption in UV-A pelleting using the response surface method. Chapter 8 investigates effects of input variables on energy consumption, water usage, sugar yield, and pretreatment energy efficiency in dilute acid pretreatment. Chapter 9 develops a predictive model for energy consumption in dilute acid pretreatment using the response surface method. Chapter 10 studies ultrasonic vibration-assisted (UV-A) dilute acid pretreatment of poplar wood for biofuel manufacturing. Chapter 11 compares sugar yields in terms of total sugar yield and enzymatic hydrolysis sugar yield between two kinds of materials: pellets processed by UV-A pelleting and biomass not processed by UV-A pelleting in terms of total sugar yield and enzymatic hydrolysis sugar yield. Chapter 12 develops a physics-based temperature model to predict temperature in UV-A pelleting. Chapter 13 develops a physics-based density model to predict pellet density in UV-A pelleting. Finally, conclusions and contributions of this research are summarized in Chapter 14.

Master of Science / Industrial & Manufacturing Systems Engineering / Todd W. Easton / Integer programming is a field of mathematical optimization that has applications across a wide variety of industries and fields including business, government, health care and military. A commonly studied integer program is the knapsack problem, which has applications including project and portfolio selection, production planning, inventory problems, profit maximization applications and machine scheduling. Integer programs are computationally difficult and currently require exponential effort to solve. Adding cutting planes is a way of reducing the solving time of integer programs. These cutting planes eliminate linear relaxation space. The theoretically strongest cutting planes are facet defining inequalities. This thesis introduces a new class of cutting planes called multiple variable merging cover inequalities (MVMCI). The thesis presents the multiple variable merging cover algorithm (MVMCA), which runs in linear time and produces a valid MVMCI. Under certain conditions, an MVMCI can be shown to be a facet defining inequality. An example demonstrates these advancements and is used to prove that MVMCIs could not be identified by any existing techniques. A small computational study compares the computational impact of including MVMCIs. The study shows that finding an MVMCI is extremely fast, less than .01 seconds. Furthermore, including an MVMCI improved the solution time required by CPLEX, a commercial integer programming solver, by 6.3% on average.

Master of Science / Department of Industrial & Manufacturing Systems Engineering / Malgorzata J. Rys / In this thesis, various safety aspects of center line rumble strips were evaluated. Based on the literature review center line rumble strips (CLRS) are considered to be effective safety countermeasure for reducing crossover accidents on two-lane, two-way roadways. CLRS are indentations milled into the center line of undivided two-lane, two-way roadways to warn driver of drifting into upcoming traffic. Researchers at Kansas State University (KSU) have conducted studies on CLRS and retroreflective pavement markings (RRPM) installed over them. Based on the literature review and the survey conducted on motorcycle riders it can be concluded that majority of riders believe in the effectiveness of CLRS and they recommend the KDOT to implement CLRS in more locations. From the survey conducted on residents of US 40 it can be concluded that RRPM help them in providing visual guidance. They also noticed that there is considerable deterioration of RRPM over CLRS on US 40. From the studies conducted on US 24, US 50 and US 40 it can be concluded that wet retroreflectivity of pavement markings installed over CLRS is considerably lower than dry retroreflectivity. In locations without CLRS wet retroreflectivity of RRPM is higher than dry retroreflectivity. Also, the analysis performed on retroreflectivity measurements from US 24, US 50 and US 40 show that retroreflectivity follows a linear reduction in performance over time. In addition, a new methodology was developed for evaluating RRPM over CLRS. Various tests and analysis were performed and the new method seems effective.

Master of Science / Department of Industrial & Manufacturing Systems Engineering / Malgorzata J. Rys / Centerline rumble strips (CLRS) are raised or indented patterns installed in the center of undivided rural two-lane highways. Their main function is to alert drivers who are encroaching or leaving the intended travel lane, by producing vibration and noise when crossed by vehicles’ tires. CLRS have been demonstrated to be an effective way in reducing head on and opposite direction sideswipe on two-lane highways (cross-over accidents). However, there are some disadvantages in their utilization, such as the exterior noise created by the strips, which may disturb residents in the highway vicinity. The objective of this study was to verify if the amount of noise created by CLRS is enough to impact negatively on residences and businesses, and to discover if the mean level of noise created by CLRS is statistically different than the noise generated by vehicles driving over smooth pavement. Two types of vehicles were driven over two different patterns of milled-in CLRS (rectangular and football-shaped) and over smooth asphalt pavement, at two different speeds. Researchers collected the noise levels at three distances 50, 100, and 150 feet, measured orthogonally from the center line, in 8 different open space locations. Results indicate that vehicle type, vehicle speed, pavement type, location and distances affect the levels of noise. In addition, both football and rectangular CLRS produced significantly higher levels of noise as compared to the smooth asphalt pavement. A 15 passenger van produced higher levels of noise in comparison with a sedan. Moreover, lower the vehicle speed, noise levels were lower. At every 50 feet of distance, the noise levels dropped significantly. CLRS do increase levels of noise relative to smooth pavement at distances up to 150 feet.

Master of Science / Department of Industrial & Manufacturing Systems Engineering / Malgorzata J. Rys / The community of Manhattan, Kansas was recently chosen as the future site of the National Bio- and Agro-Defense Facility (NBAF). At this site, research of agricultural and animal diseases and pathogens will take place. Due to the fact that the site will be in close proximity to a university, as well as many residents, a risk assessment must be completed to determine whether or not the current road infrastructure would be sufficient for evacuating the city in the event of an emergency. It should be noted that while NBAF is a large concern for this report, risk management is important in other scenarios as well, such as natural disasters or chemical spills, and this information can be applied to such events. This paper discusses the creation and analysis of a discrete-event simulation using ARENA software. The simulation described several scenarios. They were a base case scenario with only campus traffic evacuating; a scenario in which campus and outside traffic evacuate; a case with increased outside traffic; a case in which a vehicle breaks down; a case which includes guardians of children attending campus childcare are re-routed to pick up their children before evacuating; a case which accounts for reduced traveling speeds due to cell phone usage; and a case which closes a direction outside of Manhattan due to wind direction. Such simulations are an ideal performance measure of traffic flow under certain conditions due to the fact that physical resources are not needed to make a realistic comparison between each of them. Each of the situations described above were compared based on percentage of traffic leaving Manhattan and arriving at a defined safe zone each hour. Based on the findings, those involved with disaster management planning can determine if the percentages of vehicles leaving the system per hour are acceptable. They should be evaluated against potential spread rates of diseases to ensure that all residents may evacuate without the danger of becoming infected. For applications outside of NBAF, the results give insight into the degree of change in evacuation percentage that changes within the system may cause, and change any routing accordingly.

Doctor of Philosophy / Department of Industrial & Manufacturing Systems Engineering / Zhijian Pei / High-performance materials, such as silicon, aerospace stainless steels, titanium alloys, and carbon fiber reinforced plastic (CFRP) composites, have a variety of engineering applications. However, they usually have poor machinability and are classified as hard-to-machine materials. Drilling is one of the important machining processes for these materials. Industries are always under tremendous pressure to meet the ever-increasing demand for lower cost and better quality of the products made from these high-performance materials. Rotary ultrasonic machining (RUM) is a non-traditional machining process that combines the material removal mechanisms of diamond grinding and ultrasonic machining. It is a relatively low-cost, environment-benign process that easily fits in the infrastructure of the traditional machining environment. Other advantages of this process include high hole accuracy, superior surface finish, high material removal rate, low tool pressure, and low tool wear rate. The goal of this research is to provide new knowledge of machining these high performance materials with RUM for further improvement in the machined hole quality and decrease in the machining cost. A thorough research in this dissertation has been conducted by experimental, numerical, and theoretical investigations on output variables, including cutting force, torque, surface roughness, tool wear, cutting temperature, material removal rate, edge chipping (for silicon), power consumption (for CFRP), delamination (for CFRP), and feasible regions (for dry machining of CFRP). In this dissertation, an introduction of workpiece materials and RUM are discussed first. After that, two literature reviews on silicon drilling and dry drilling are presented. Then, design of experiment and finite element analysis on edge chipping in RUM of silicon, experimental investigations and finite element analysis on RUM of aerospace stainless steels, an ultrasonic vibration amplitude measurement method and a cutting temperature measurement method for RUM using titanium alloys as workpiece, experimental and theoretical investigations on RUM of CFRP composites, and experimental studies on CFRP/Ti stacks are presented, respectively. Finally, conclusions and contributions on RUM drilling are discussed.