Master of Science / Department of Industrial & Manufacturing Systems Engineering / Todd Easton / Heuristics are often implemented to find better solutions to computationally challenging problems. Heuristics use varying techniques to search for quality solutions. Several optimization heuristics have drawn inspiration from real world practices. Ant colony optimization mimics ants in search of food. Genetic algorithms emulate traits being passed from a parent to a child. Simulated annealing imitates annealing metal. This thesis presents a new variable neighborhood search optimization heuristic, fútbol Strategies applied to Optimize Combinatorial problems to Create Efficient Results, which is called the SOCCER heuristic. This heuristic mimics fútbol and the closest player to the ball performs his neighborhood search and players are assigned different neighborhoods. The SOCCER heuristic is the first application of variable neighborhood search heuristic that uses a complex structure to select neighborhoods. The SOCCER heuristic can be applied to a variety of optimization problems. This research implemented the SOCCER heuristic for job shop scheduling problems. This implementation focused on creating a quality schedule for a local limestone company. A small computational study shows that the SOCCER heuristic can quickly solve complex job shop scheduling problems with most instances finishing in under an half an hour. The optimized schedules reduced the average production time by 7.27%. This is roughly a 2 day decrease in the number of days required to produce a month’s worth of orders. Thus, the SOCCER heuristic is a new optimization tool that can aid companies and researchers find better solutions to complex problems.

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.

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.

Doctor of Philosophy / Department of Industrial & Manufacturing Systems Engineering / Zhijian Pei and Donghai Wang / Currently, transportation is almost entirely dependent on petroleum-based fuels (e.g. gasoline, diesel fuel, and jet fuel). Increasing demands for sustainable sources of liquid transportation fuels make it imperative to develop alternatives to petroleum-based fuels. Biofuels derived from cellulosic biomass (forest and agricultural residues and dedicated energy crops) have been recognized as promising alternatives to petroleum-based liquid fuels. Cellulosic biofuels not only reduce the nation’s dependence on foreign petroleum but also improve the environment through reduction of greenhouse gas emissions. In order to convert cellulosic biomass into biofuels, cellulosic biomass must go through a size reduction step first, because large size cellulosic biomass (whole stems of herbaceous biomass or chunks of woody biomass) cannot be converted to biofuels efficiently with the current conversion technologies. Native cellulosic biomass has limited accessibility to enzyme due to its structural complexity. Size reduction can reduce particle size and disrupt cellulose crystallinity, rendering the substrate more amenable to enzymatic hydrolysis. The purpose of this research is to provide knowledge of how size reduction alters biomass structural features, and understand the relationships between these biomass structural features and enzymatic hydrolysis sugar yield. This research is also aimed to investigate the impacts of process parameters in biomass size reduction on the conversion of cellulosic biomass to biofuels to help realize cost-effective manufacturing of cellulosic biofuels. This dissertation consists of eleven chapters. Firstly, an introduction of this research is given in Chapter 1. Secondly, Chapters 2 presents a literature review on cellulosic biomass size reduction. Thirdly, a preliminary experimental study is included in Chapter 3. Chapters 4 to 6 present a three-phase study on confounding effects of two important biomass structural features: particle size and biomass crystallinity. Chapters 7 and 8 investigate effects of sieve size used in size reduction of woody and herbaceous biomass, respectively. Chapters 9 and 10 focus on the relationship between particle size and sugar yield. Chapter 11 studies effects of cutting orientation in size reduction of woody biomass. Finally, conclusions and contributions are given in Chapter 12.

Master of Science / Department of Industrial & Manufacturing Systems Engineering / Malgorzata J. Rys / Before year 2012 the US States must implement and continue using an assessment or management method to maintain traffic signs’ retro-reflectivity at or above the minimum levels adopted by FHWA. Overhead guide signs are a particular problem because past research has shown that with available sheeting types, external illumination may still be necessary. Newer sheeting types and more energy efficient and cost-effective lighting systems are currently available. Over the next several years there is potential for savings of tens of thousands of dollars if the states don’t have to use external illumination for their overhead guide signs, or, if more energy efficient, low cost lighting systems are used when necessary. A detailed literature review was conducted on minimum retro-reflectivity values for overhead guide signs, the legibility distance under reduced sign luminance and the lighting systems available for external illumination. There is no agreement found in the previous research studies as to what is the optimum or minimum luminance of the guide signs. In addition, a survey was sent to all state DOTs. This survey was focused on finding states’ policies regarding the use of sheeting type and external illumination requirement, and methods and lighting systems for maintaining minimum values for overhead guide sign luminance. The total response rate was 56% (28 out of 50 state DOTs responded). Out of 28 respondents 19 said that they have usage policy for the type of sheeting material used for overhead guide signs and 18 of them provided details about their policy. An equipment to control the illumination levels from vehicle headlamps was built and pilot tests were conducted in the laboratory. A pulse-with-modulation dimming circuit designed around the Atmel ARM-based microcontroller board and power MOSFETs was used to control the brightness of the headlights for the high- and low-beams. Field tests were conducted in the later stages during nighttime to evaluate three different types of sheeting materials using 10 human subjects from age group 18-34. The materials DG3 and Type IV were found to perform better than Type I material for nighttime visibility but they were not significantly different from each other.

Master of Science / Department of Industrial & Manufacturing Systems Engineering / John English / This research builds upon previous efforts to explore the use of Statistical Process Control (SPC) in lieu of cycle counting. Specifically a three pronged effort is developed. First, in the work of Huschka (2009) and Miller (2008), a mixture distribution is proposed to model the complexities of multiple Stock Keeping Units (SKU) within an operating department. We have gained access to data set from a large retailer and have analyzed the data in an effort to validate the core models. Secondly, we develop a recursive relationship that enables large samples of SKUs to be evaluated with appropriately with the SPC approach. Finally, we present a comprehensive set of type I and type II error rates for the SPC approach to inventory accuracy monitoring.

Master of Science / Department of Industrial and Manufacturing Systems Engineering / Shing I. Chang / This research studies a few methodologies for real-time detection of wave profile changes. In regular profile monitoring, change detection takes place at the end of time period when a complete profile is available. In real-time change detection of profiles, a potential profile change takes place between the beginning and the end of the time period. The decision involves the identification whether a process is in control or out of control before the entire profile is generated. In this regard, five proposed methodologies were developed and tested in this thesis. Earthquake waves, manufacturing processes, and heart beat rate are a few examples of profiles with different natures that the proposed methodologies can be applied to. Water temperature profiles generated during a curing process are considered as an example in this study. Successful implementation of the proposed work on these profiles would cause saving great amounts of time and money. Five methods are studied for monitoring the water control process of a curing process. The first four proposed methodologies are based on an univariate approach where the statistic used for process monitoring is the enclosed area between the profiles and their fitted cutting lines. A multivariate approach is also proposed. A simulation study is also conducted when the best method is chosen based on it performance and simplicity of operations. Various types of acceptable and unacceptable profiles are simulated for the best proposed method identified in the preliminary study. The best method has a satisfactory performance in detecting the changes in the unacceptable profiles. In addition, the false alarm rate in identifying acceptable profiles as bad profiles is lower than 10%.

Doctor of Philosophy / Department of Industrial & Manufacturing Systems Engineering / Jessica L. Heier Stamm / Humanitarian and public health logistics systems are often characterized by decentralized decision makers in the form of response agencies who establish supply chains and the beneficiaries who access them. While classical models assume there is a single decision maker with a global objective and authority, decentralized systems consist of multiple decision makers, each with accomplishing his own objective and scope of control. The literature demonstrates that decentralized systems often perform poorly when compared to their hypothetical centralized counterparts. However, there exist few models in the literature to quantify the impact of decentralization and mechanisms for its mitigation are deficient. This research advances knowledge of decentralized systems through new game theory and optimization models, solution methodologies and theoretical characterizations of system performance. First, the author presents a literature review that synthesizes research regarding the facets of humanitarian operations that can benefit from the application of game theory. The author finds that models of decentralized behavior lack realism, neglecting sources of uncertainty, dynamism and personal preferences that influence individuals' decisions. These findings motivate the remaining components of the thesis. Next, the author focuses on decentralization on the part of response agencies who open service facilities. Decentralization can adversely impact patient access and equity, both critical factors in humanitarian contexts. A dynamic, robust facility location model is introduced to enable a comparison between a given decentralized response and a hypothetical coordinated response using identical resources. The value of the model is demonstrated through a computational study of the response to a recent cholera epidemic. Finally, the author introduces game theory models that represent the decisions of beneficiaries seeking relief. The models account for distance, congestion, and the relative importance an individual places on the two. The author constructs an algorithm that computes a decentralized solution in polynomial time. The author quantifies decentralized system performance in comparison to centralized control, bounding the cost of decentralized decision making for the least and most costly outcomes. The author identifies coordination mechanisms encourage centrally optimal decisions within decentralized systems.

Master of Science / Department of Industrial & Manufacturing Systems Engineering / Shing I. Chang / Many decision-making methods have been developed to help decision makers (DMs) make efficient decisions. One decision making method involves selecting the best choice among alternatives based on a set of criteria. Multiple Attribute Decision-Making (MADM) methods allow opportunities to determine the optimal alternative based on multiple attributes. This research aims to overcome two concerns in current MADM methods: uncertainty of attributes and sensitivity of ranking results. Based on availability of information for attributes, a DM maybe certain or uncertain on his judgment on alternatives. Researchers have introduced the use of linguistic terms or uncertain intervals to tackle the uncertainty problems. This study provides an integrated approach to model uncertainty in one of the most popular MADM methods: TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). Current MADM methods also provide a final ranking of alternatives under consideration and, the final solution is based on a calculated number assigned to each alternative. Results have shown that the final value of alternatives may be close to each other uncertain attributes, but current methods rank alternatives according to the final scores. It exhibits a sensitivity issue related to formation of the ranking list. The proposed method solves this problem by simulating random numbers within uncertain intervals in the decision matrix. The proposed outcome is a ranking distribution for alternatives. The proposed method is based on TOPSIS, which defines the best and the worst solution for each attribute and defines the best alternative as closest to best and farthest from the worst solution. Random number distributions were studied under the proposed simulation solution approach. Result showed that triangular random number distribution provides better ranking results than uniform distribution. A case study of building design selection considering resiliency and sustainability attributes was presented to demonstrate use of the proposed method. The study demonstrated that proposed method can provide better decision option for designers due to the ability to consider uncertain attributes. In addition using the proposed method, a DM can observe the final ranking distribution resulted from uncertain attribute values.