Master of Science in Engineering, Youngstown State University, 2015, Department of Mechanical, Industrial and Manufacturing Engineering

The additive manufacturing industry has the potential to transform nearly every sector of our lives and jumpstart the next Industrial Revolution. Engineers and designers have been using 3D printers for more than three decades but mostly to make prototypes quickly and cheaply before they embark on the expensive business of tooling up a factory to produce the real things. In sand casting industries, a growing number of companies have adopted 3D sand printing to produce final casts. Yet recent research suggests that the use of 3D sand printing has barely begun to achieve its potential market. It is not surprising that executives are having difficulty adopting additive manufacturing; the technology has many second - order effects on business operations and economics. One of the most important factors is the lack of awareness of additive manufacturing's applications and values in the sand casting manufacturing process. The lack of awareness is significantly slowing down the adoption rates. This research will help executives to optimize their adoption decision by answering the question of "At what level of part complexity should sand printing be used instead of the conventional process in molds and cores manufacturing?" Moreover, this thesis defines and analyzes the geometric attributes which influence the parts' complexity. As known in the conventional sand casting process, the high level of complexity leads to higher manufacturing cost. On the other hand, in the additive manufacturing process, the manufacturing cost is fairly constant regardless of the level of complexity. Therefore, 3D sand printing provides a unique advantage that the increasing in geometric complexity of the part has no impact on the molds and cores manufacturing cost or what is known as "complexity for free."

Master of Science (MS), Ohio University, 2012, Industrial and Systems Engineering (Engineering and Technology)

Reliable cost estimation of systems in the early design stages can be very beneficial. Some methods that do focus on system estimation are based on high level parametric models, which are not always detailed enough to provide a reliable or useful prediction model. This thesis provides a repeatable method for creating Cost Estimating Relationships (CERs) for the estimation of a system of parts using attributes available at a preliminary design stage. The methodology provides guidelines for collecting data, classifying data, and creating CERs. Also, Attribute Estimating Relationships (AERs) are discussed for estimating the CER inputs that may not be available in preliminary design with attributes that are available in preliminary design. The methodology was tested on a system of parts from a jet engine and the resulting CERs were compared to other higher level models. The results indicated the proposed method was slightly less accurate than some alternative models. However, the proposed method provided a more detailed and logical CER than the alternate models.

Master of Science (MS), Ohio University, 2002, Industrial and Manufacturing Systems Engineering (Engineering)

Cost tolerance optimization for piecewise continuous cost tolerance functions

Master of Science (MS), Ohio University, 2005, Mechanical Engineering (Engineering)

Following are the processes and results of the development of a more accurate forging cost estimating equation useful for any forged part of given material and final dimensions. A current forging cost estimating equation standard is used as a benchmark. Error from this equation is calculated at 23 percent. Prototype equations are developed using current methods of metal processing. Models are then tweaked or discarded as testing progresses through varied methods of error trapping. The final equation (below) has an error of 15 percent, a reduction of eight percent over the benchmark. Process cost = K*E*Fcom*(A*Pave)n Where K and n are constants, A is the cross-sectional area of the forging, Pave is the average pressure needed to produce the forging using the “slab” method of calculation, E is an escalation factor ($102.57 in this study), and Fcom is a forging shape complexity multiplier.

Doctor of Philosophy, University of Toledo, 2017, Higher Education

An Abstract of Cost Containment Practices of a Private Non-Profit College: A Qualitative Case Study by Pratap Patwardhan Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Doctor of Philosophy Degree in Higher Education The University of Toledo December 2017 Private colleges have grown accustomed to increasing tuition and fees to meet their expenses. These policies have contributed to the increased college cost for Americans. Most American students and parents have believed that the higher education improved their life by offering better job opportunities, higher salaries and thus a better standard of life. During the last 35 years, inflation in higher education has skyrocketed. The purpose of this qualitative single case study was to understand, how a private college dealt with the escalating college cost challenges. I chose a private non-profit college for the case study. It was called MWPC (Midwestern Private College). This case study identified how one private college managed to control cost containment strategies. The study detailed how cost containment strategies were created and how well these cost containment strategies worked for the institution after implementation. Student enrollments and endowments were important to the financial health to the institution. MWPC agreed to share its financial information for this case study research. MWPC came very close to shutting the doors of this institution due to its financial crisis. The Board of Trustees employed a president, who appointed new senior leadership to address the critical situation. This case study details how the president and the senior leadership of MWPC identified and implemented cost containment to turn the college around and came up with an approach with new cost containment. Cost containment practices became a way of life for MWPC.

Master of Science (MS), Ohio University, 2013, Industrial and Systems Engineering (Engineering and Technology)

Using Design for Manufacturability to integrate manufacturing and design has been shown over the years to reduce manufacturing costs and increasing overall revenues. Much research has been provided with a focus on integrating the design of a product and its respective manufacturing processes, but without the consideration of the existing facility capacity. By incorporating the existing capacity, manufacturing cost estimations can more accurately represent true factors such as overtime and material handling. This thesis describes a methodology to incorporate system capacity in cost estimation. Ideal manufacturing costs, widely used as a standard for production cost estimation, incorporates only material and labor costs. Ideal cost is used as an input to the methodology proposed, and determines true manufacturing costs using the existing manufacturing system design. The methodology compares multiple possible designs for a given part and estimates true cost of each design. Along with estimating true cost, the methodology considers three alternatives for implementing each design and the total costs of each: minimizing material handling costs by minimizing intracellular movement; minimizing overtime costs by utilizing all machine capacity, and minimizing total costs by purchasing additional machines to meet demand. The methodology will provide an estimate of the true cost for each design being evaluated for each alternative presented. This will allow the user to not only get a more accurate representation of manufacturing costs, but also allow for cost analysis of multiple implementation alternatives for versatility. A mathematical model which maximizes facility profit by using the methodology proposed will be created and evaluated. The model will show how the methodology presented can be used in alternative scenarios in manufacturing settings.

MS, Kent State University, 2024, College of Arts and Sciences / Department of Computer Science

Search and rescue missions are critical endeavours aimed at locating survivors trapped in the aftermath of various calamities such as earthquakes, landslides, tsunamis etc. The time efficiency required for these missions is pivotal in saving lives, prompting the adoption of robotics with advanced technology to expedite operations. Effective planning and strategizing play key roles in enhancing a robot's efficiency, particularly in prioritizing areas of need. Typically, search and rescue missions often present a high level of complexity due to a multitude number of factors to be considered when planning and optimizing operations. Factors such as determining hot-spot regions, harsh weather conditions, terrain complexity, environmental hazards, and time sensitivity, just to a mention few, introduce intricacies to the task of effective planning. For instance, a factor such as environmental conditions is considered dynamic as it may change from time to time. Additionally, the criticality of different regions may change dynamically as soon as the information is made available, further complicating the task for both rescue robots and even fast responders. This research addresses the challenge of optimizing path planning in search and rescue missions, treating it as a variant of the travelling salesman problem and proposes a hybrid technique that incorporates both algorithmic and non-algorithmic techniques, to tackle the problem. The hybrid technique leverages a tweaked version of the U-net neural network that is trained on two pieces of information: static data, data that encircles topological map data such as slope and dynamic data deduced from map findings data that would be vital in singling out hotspots and priority regions on the map. Blending these two pieces of information, an amalgamated cost, a value that incorporates both priority and cost of traversal, is determined to aid robot path planning decisions. Training a neural network on this data (open full item for complete abstract)

Doctor of Philosophy (PhD), Ohio University, 2021, Industrial and Systems Engineering (Engineering and Technology)

The first section of this research develops a mathematical model to determine vehicle routing in the context of humanitarian logistics denominated Social Cost Vehicle Routing Problem. The objective function of the model minimizes social cost which incorporates private and deprivation cost. Private costs include logistics, procurement, and transportation cost. Deprivation cost account for survivors' suffering due to the lack of access to critical supplies. Due to the NP-hard nature of the problem, a hybrid metaheuristic algorithm with a novel local search is developed. The algorithm uses Tabu Search (TS), Simulated Annealing (SA), and Variable Neighborhood Search (VNS) in a combined manner that SA is embedded in TS and VNS implements randomized number of local searches. The model is applied to the case study of water distribution in Puerto Rico; similar challenge faced after Hurricanes Irma and Maria in 2017. This research develops a strategy for water distribution in post disasters. Numerical experiments indicate the efficiency of the algorithm to provide optimal or near-optimal solutions in reasonable execution times that make the methodology/solution procedure viable for operational implementation. Sensitivity analysis scenarios evaluate the robustness of the model as water rationing changes. The second section of this research develops a two-stage stochastic programming model applicable for Post-Disaster Humanitarian Logistics (PD-HL). The model solves the Social Cost Vehicle Routing Problem incorporating uncertainty in travel times. The first stage concerns with determining vehicle routings prior to the realization of travel time. The main decision in the second stage is travel time which affects the arrival time of the vehicle to the affected population. The objective of the model minimizes social cost which includes logistics cost and deprivation cost. Considering the NP hard nature of the problem, TS-SA-VNS is applied. The case study of water distribution (open full item for complete abstract)

PHD, Kent State University, 2021, College of Business and Entrepreneurship, Ambassador Crawford / Department of Accounting

This study discovers deliberate managerial decisions on cost structure under uncertain political environment surrounding firms. Political uncertainty has attracted significant attention in the accounting literature because it can have considerable financial and non-financial impacts on firms' business environment. In this study, I first examine whether firms are likely to change their cost structure (the proportion of fixed inputs to variable inputs in cost structure) when facing political uncertainty. Second, I further investigate whether the association between political uncertainty and cost structure is conditional on (1) the presence of government customers, (2) asset redeployability, and (3) political connections. Using the sample from 2003 to 2019, I find that firms are likely to have a more rigid cost structure in response to political uncertainty. The positive association between political uncertainty and cost rigidity is more pronounced for firms without government customers, firms using less redeployable assets, and firms without political connections. This study contributes to the debate on cost rigidity in uncertain business environment by focusing on political uncertainty.

Master of Sciences (Engineering), Case Western Reserve University, 2019, Civil Engineering

Tornadoes are hazards of low probability of occurrence and high consequences that cost the United States billions of dollars each year. Electric power distribution systems are susceptible to damage due to tornadoes with the utility poles being the most vulnerable components. Additionally, the reliability of power distribution systems can be affected by the deterioration of the strength of utility poles with age. Many utility companies nowadays are considering the use of steel and prestressed concrete poles instead of wood poles, which are the most widely used in the United States. Up to date, very few studies have been performed to study the behavior of power networks when subjected to tornadoes. This research proposes a framework to perform reliability analysis, cost analysis, and target hardening of power distribution systems subjected to tornado hazard. It also offers a framework to compare the reliability of wood, steel, and prestressed concrete utility poles subjected to tornadoes through fragility analysis considering the deterioration of the strength of the poles with age.

Master of Arts, Miami University, 2017, Economics

Using online daily price data I explore the validity of a theory relating price stickiness to price adjustment costs in the form of price setters' fear of alienating customers with frequent price changes. I argue that prices change more frequently for goods that are bought less often because of this price-setting strategy. I find that semi-durable goods (which are purchased more frequently than durable goods) change their prices less frequently than durable goods. However, non-durable goods change their prices more frequently than goods in other two categories. I attribute the latter relationship to the vital necessity of food, an important category within non-durable goods. While I find evidence that durable goods' price-change frequency is consistent with all models of price-adjustment costs, semi-durable and non-durable goods have price adjustment costs that are positively related to their prices. I argue that this difference in price adjustment costs is due to customer alienation costs, which are derived from customers' “price memory” (expectation of what a “fair” price for this good is).

Doctor of Philosophy, University of Toledo, 2017, Foundations of Education

African American college enrollment rates continue to increase, while graduation rates do not. This state of affairs lends itself to a wealth disparity between African Americans and other racial groups. As such, this research investigated if university demographics and classification of institutional type can predict African American student success, operationally defined by graduation rates and ROI (20 years). Multiple statistical models, analyzing government and proprietary normative data found one key variable emerged. An African American student increases their odds of both graduating and receiving the highest ROI, by attending a university with the highest overall university graduation rate, regardless of the percentage of African American Students in attendance, cost, public or private, or enrollment size. A SUCCESS Model ties together all statistical findings, anecdotal discoveries and larger implications of this research. Findings generalize beyond the African American student.

Doctor of Philosophy, The Ohio State University, 1966, Graduate School

Master of Science in Engineering, Youngstown State University, 2016, Department of Mechanical, Industrial and Manufacturing Engineering

The widespread adoption of Additive Manufacturing (AM) can be greatly attributed to the lowering prices of entry-level extrusion-based 3D printers. It has enabled the use of AM for prototypes, STEM education and often, to produce complex custom commercial products. With increased access to material extrusion-based 3D printers and newer materials, the influence of print parameters such as infill patterns on resulting mechanical strength and print costs, need to be investigated. This research investigates the relationship among (1) infill designs, (2) selection of printer (entry-level vs. production grade), (3) mechanical properties (e.g. tensile, compressive and flexural) and (4) production cost (print time and material). Finite Element Analysis (FEA) simulation using ANSYS software was conducted on the 4-point bending specimens to develop an FEA model that was correlated with the experimental data (±8% accuracy). Relevant infill designs are evaluated and recommended based on the loading conditions and savings in production cost when compared to solid infill design. In the case of tension, a larger air gap in the infill design was the most cost effective. In the case of compression, low density and high density infills were more cost effective when compared to solid samples. In the case of the flexural loading, low density infill was also the most cost effective infill design. It was found that print time had a greater effect on total cost and hence, influence of print time is analyzed using both entry-level and production grade printers. The findings from this study will help formulate criteria for selection of optimal infill design based on loading conditions and cost of printing. In summary, it was found that in the case of entry-level printers, solid infill design is preferred due to minimal cost savings when compared to other infill designs. On the contrary, it was found that low density infill is more cost efficient than solid infill design while using producti (open full item for complete abstract)

Doctor of Philosophy, University of Akron, 2016, Civil Engineering

Self-centering concentrically braced frame (SC-CBF) systems have been developed to increase the drift capacity of braced frame systems prior to damage to reduce post-earthquake damages in braced frames. However, due to special details required by the SC-CBF system, the construction cost of an SC-CBF is expected to be higher than that of a conventional CBF. While recent experimental research has shown better seismic performance of SC-CBF system subjected to design basis earthquakes, superior seismic performance of this system needs to be demonstrated for both structural and nonstructural components in all ground motion levels and more building configurations. Moreover, Stakeholders would be attracted to utilize SC-CBF if higher construction cost of this system can be paid back by lower earthquake induced losses during life time of the building. In this study, the seismic performance and economic effectiveness of SC-CBFs are assessed and compared with CBF system in three building configurations. First, probabilistic demand formulations are developed for engineering demand parameters (inter-story drift, residual drift and peak floor acceleration) using results of nonlinear time history analysis of the buildings under suites of ground motions. Then, Seismic fragility curves, engineering demand (inter-story drift, peak floor acceleration and residual drift) hazard curve and annual probabilities of exceeding damage states are used to evaluate and compare seismic performance of two systems. Finally, expected annual loss and life cycle cost of buildings are evaluated for prototype buildings considering both direct and indirect losses and prevailing uncertainties in all levels of loss analysis. These values are used evaluate economic benefit of using SC-CBF system instead of CBF system and pay-off time (time when the higher construction cost of SC-CBF system is paid back by the lower losses in earthquakes) for building configurations. Additionally, parametric study is per (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2013, City and Regional Planning

Investments in the urban energy infrastructure for distributing electricity and natural gas are analyzed using (1) property data measuring distribution plant value at the local/tax district level, and (2) system outputs such as sectoral numbers of customers and energy sales, input prices, company-specific characteristics such as average wages and load factor. Socio-economic and site-specific urban and geographic variables, however, often been neglected in past studies. The purpose of this research is to incorporate these site-specific characteristics of electricity and natural gas distribution into investment cost model estimations. These local characteristics include (1) socio-economic variables, such as income and wealth; (2) urban-related variables, such as density, land-use, street pattern, housing pattern; (3) geographic and environmental variables, such as soil, topography, and weather, and (4) company-specific characteristics such as average wages, and load factor. The classical output variables include residential and commercial-industrial customers and sales. In contrast to most previous research, only capital investments at the local level are considered. In addition to aggregate cost modeling, the analysis focuses on the investment costs for the system components: overhead conductors, underground conductors, conduits, poles, transformers, services, street lighting, and station equipment for electricity distribution; and mains, services, regular and industrial measurement and regulation stations for natural gas distribution. The Box-Cox, log-log and additive models are compared to determine the best fitting cost functions. The Box-Cox form turns out to be superior to the other forms at the aggregate level and for network components. However, a linear additive form provides a better fit for end-user related components. The results show that, in addition to output variables and company-specific variables, various site-specific variables are statistically s (open full item for complete abstract)

MS, University of Cincinnati, 2009, Pharmacy : Pharmaceutical Sciences

The cost of health care is rising, and this trend is also seen in transplantation. One particularly important complication of transplantation is rejection; however, the cost of rejection has not been quantified in a manner that is comprehensive, generalizable and based on standard of care. The purpose of this research project was to quantify the cost of processes of care (diagnosis and management), both inpatient and outpatient, of acute rejection events and associated complications in renal transplant recipients in a real-world US practice setting. A retrospective matched case-control study was undertaken. A database of patients transplanted at The University Hospital, Cincinnati, Ohio, was analyzed to identify patients who had experienced a rejection episode. The same database was used to create a cohort of patients matched on age ± ten years, sex, ethnicity and type of transplant. There were 22 patients in each cohort. Data was collected for six months after the diagnosis of rejection, and the same time period post transplantation forward for six months in the matched controls. Costs were evaluated from the health-system perspective. Health-system costs were reported from the hospital cost accounting system and standardized to 2007 US dollars, outpatient medications were reported in average wholesale costs in 2009 dollars and outpatient clinic visit costs were derived from Medicare reimbursement, 2008 dollars. The total costs were significantly different between the groups for six months of care. The mean cost of care for rejection patients was $51,765 ($14,291-137,021) versus no rejection patients $32,784 ($10,358-78,109), p = 0.004. Total health-system costs were also significantly different: $30,000 ($405-400,961) versus 11,460 ($260-84,954), rejection versus no rejection, respectively, (p = 0.029). It was expected that diagnostic costs would be higher in the rejection group, and this was consistent with the findings. Radiology costs were significantly higher (open full item for complete abstract)

Master of Arts, University of Toledo, 2011, Economics

Two costs are associated with visiting a recreational site: the opportunity cost of time and the travel cost. This research examines the robustness of various estimates of the opportunity cost of time in order to more accurately estimate the willingness to pay for wetland restoration at Maumee Bay State Park. Samples are drawn from the Northwest Ohio Wetland Survey, which was conducted in 2008. Because employment classification reveals information about the individual's opportunity cost of time, respondents were split into subgroups based on their employment classification. An individual can be out of the labor market, work a fixed schedule and be underemployed, work a fixed schedule and be overemployed, or an individual can be free to choose their work hours. I also allow for the possibility that an individual working a fixed schedule is content working their current hours. Models using different discount rates, k, were used to estimate the sensitivity of the willingness to pay estimate to various measures of the opportunity cost of time. Using estimates from a bivariate Poisson lognormal model, the willingness to pay estimates varied significantly, from $14.91 per person per year when k=0 to $56.42 per person per year when k=1, depending on the opportunity cost of time. Allowing k to vary by employment subgroup leads to a willingness to pay estimate of $26.40, which was similar to the estimate calculated when k was 1/3.

Doctor of Philosophy, The Ohio State University, 2006, Public Health

Comprehensive sex education programs are intervention programs that address sexual reproduction, contraception and use of protective barriers such as condoms against sexually transmitted diseases. These programs typically promote abstinence as the safest method for preventing pregnancy and sexually transmitted diseases as well as emphasize safer sex through the use of condom and other contraceptive methods. In general, comprehensive sex education programs have been found to be effective. Looking beyond the intervention programs effectiveness, the purpose of this study is to determine if these programs are cost-effective. Therefore, utilizing decision analytic technique, the baseline cases of pregnancy and sexually transmitted diseases, and their associated medical costs for one-year are estimated. Furthermore, applying the intervention program effects to the baseline cases and medical costs, the estimated one-year avertable medical costs due to intervention are obtained. To further explore potential medical cost savings, three scenarios are investigated. Scenario One is the determination of the effects of one percent of the population delaying coital debut for one year. Scenario Two quantifies the impact of delaying further coitus for one year among those who are sexually active. Scenario Three is the determination of the impact of increasing by one percent the percentage of adolescents who say they used a condom at last intercourse. The findings are that, in 2000, the avertable medical costs associated with sexually transmitted diseases ($4.1 billion) and pregnancy ($6.0 billion) amounted to $10 billion; and the incremental cost savings due to one-year delay of coitus among 13-14 years-old adolescents amounted to $218 million. The one-year estimated avertable medical costs due to intervention range from $0 – $5; $ – $99; and $0 – $280 per adolescent for age-groups 13-14 years; 15-17 years; and 18-19 years; respectively. In addition, the results of the scenarios sho (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2004, Evolution, Ecology, and Organismal Biology

In this study, we explore large-scale movements in ruffed grouse (Bonasa umbellus) in Ohio by characterizing juvenile and adult dispersal, investigating the effect of landscape characteristics on movement behavior and examining the relationship between movement and the risk of predation. Our first objective was to investigate the natal and adult dispersal characteristics of ruffed grouse throughout the entire annual breeding cycle, using a behavioral definition of dispersal. Once dispersal movements could be accurately identified, we explored whether landscape variables measured at coarse-grained scales could help explain general movement characteristics. We used Akaike Information Criterion (AIC) techniques for model selection to explore the relationship between metrics of both landscape composition and configuration and the decision to disperse by adults and juveniles, their net dispersal distances and rates of movement, and their home range sizes. Ecologists often assume that dispersing individuals experience an increase in predation risk due to increased exposure to predators while moving. We tested the hypothesis that predation risk is a function of rate of movement and site familiarity using a Cox's proportional hazards model. Overall, we documented a surprisingly high proportion of adults undertaking seasonal dispersal movements and juveniles undergoing dispersal in the spring, particularly compared to grouse studies conducted in the northern portion of its range (Chapter 1). We also found that coarse-grained landscape characteristics affect movement behavior, but effects varied considerably among specific behaviors and across spatial scales. While large-scale landscape composition (i.e. % forest) and edge density significantly affected dispersal behavior little evidence was found for landscape configuration per se affecting movements (Chapter 2). Finally, we found evidence indicating that increased movement rates may increase the risk of predation for adult (open full item for complete abstract)