Approved for public release; distribution is unlimited / Maintaining the Fleet Readiness Plan (FRP) construct of six aircraft carriers available within 30 days, plus two additional carriers available within 90 days is a difficult task. Maintenance requirements on carriers alone make satisfying the FRP a challenging scheduling problem. We develop a carrier maintenance scheduling model with a goal to meet, as best as possible, the FRP requirements over a ten-year period, while obeying simple maintenance facility constraints. This model allows us to anticipate gaps in coverage and also quantitatively assess the benefit, or burden, of re-sizing the fleet. We conclude that by increasing the average cycle time for a Carrier Strike Group (CSG) to 27 months we can meet the FRP requirements continuously after an initial maintenance adjustment period of 62 months. / Lieutenant, United States Navy

The specific focus of this degree paper is an analysis of operational auditing and its possible effects on the delivery of services by the City of Atlanta to its citizens. Strict attention is paid to the staffing, budgeting, and timeliness of the operational auditing operation, and its effects on municipally run operations. The recent interest in operational auditing has stemmed from the desire of municipalities to adequately determine if their operations are being run as efficiently and effectively as possible. The City of Atlanta, while not facing any immediate major economic or operational problems must fact the reality of delivering more services to its citizens with a slowly expanding revenue base. With this, as well as other factors stated in this paper, operational auditing becomes a management tool that should be seriously considered as a menas of dealing with the operational problems that the City is presently facing and will face in the future.

This research study had two distinct objectives. The first objective was to determine in which areas in South African banks the most severe operational risk losses are likely to occur (based on the Basel II seven loss event types and eight business lines). Severity was assessed based on single operational risk events that might have significant monetary values attached to them. The likely frequency of single operational risk events was also assessed. The investigation of the aforementioned research problem was explorative and quantitative of nature, as the researcher made extensive use of survey research in the form of a questionnaire to all registered banks. The second part of the research study’s objective was to assess the range of practices in collecting internal loss data for operational risk purposes as required by Basel II. This part was approached from a qualitative perspective, by benchmarking the research findings against the Basel II text, the researcher’s experience in risk management in banks, the Basel Committee on Banking Supervision’s Sound Practices for the Management and Supervision of Operational Risk, and related literature. The literature review, including reference to certain surveys and studies, focuses on the main concepts of operational risk within banks that are pertinent to the research problem. The literature review also includes several references to the Basel II text and other relevant publications and papers issued by the Basel Committee on Banking Supervision. The research results revealed that respondents in South African banks believed that ‘business disruption and system failures’ is the loss event type that is likely to result in the most severe single operational risk loss. ‘Trading and sales’ scored the same high average rating as ‘business disruption and system failures’ as the business line where the most severe single operational risk loss is likely to occur in South African banks. ‘External fraud’ and ‘execution, delivery and process management’ scored the highest average ratings as the loss event types where the most frequent operational risk losses are likely to occur. Respondents indicated that ‘retail banking’ is the business line where the most frequent single operational risk losses are likely to occur in South African banks. Based on the above-mentioned findings the researcher recommends that these high-risk areas be highlighted to the Bank Supervision Department of the South African Reserve Bank, the boards of directors and senior management of banks in order for them to strengthen banks’ internal controls. The researcher recommends the inclusion of near misses and opportunity cost in operational risk loss databases. Banks should at least capture the date of the discovery of an operational risk event as this represents acceptable practice among the majority of banks. Operational risk losses should be assigned to the multiple business activities in which it occurred on a pro-rata basis. All recoveries of operational risk losses should be processed separately, but associated with the original loss event. Replacement cost is seen as the most appropriate way to capture gross loss amounts for the damage to fixed assets. The researcher encourages the recording of overtime cost for fixing systems failures. Market risk losses due to operational risk events should be treated as market risk losses, while loan-related losses due to operational risk failures should be treated as credit risk losses by banks. The researcher’s view is that banks should set different thresholds for the collection of operational risk losses for its various business units based on each business unit’s operations and nature of business. Banks should, as a starting point, map operational risk events to the Basel II 8x7 matrix. Operational risk losses should be assessed by both legal entity and on a consolidated basis.

This study is an exposition of research into the effect of operational efficiency to global competitiveness, with the Richards Bay Dry Bulk Terminal (DBT) being the case study. The Richards Bay DBT is the main dry bulk terminal in the South African ports, operated by Transnet Ports Terminals (TPT), which is a division of the state-owned Transnet Ltd. Because of the strategic position of the DBT as the main dry bulk terminal of the country and also that it is a state owned entity, its competitiveness or otherwise is a reflection of South Africa the country as a trade destination. The research seeks to investigate the problem of the declining volumes handled by the DBT, which is traced to the possible operational inefficiencies and is likely to impede competitiveness of the DBT. While this study will not propose the ultimate solutions to the DBT’s problems, it will identify the root causes and symptoms of the problems, which will ultimately guide what needs to be tested as a better solution. Based on this, it is argued that this topic should generate a lot of interest to the stakeholders both locally and internationally.

The aim of this study was to investigate the effect of frequent operational changes on the repairs and maintenance of public lighting in the Energy and Electricity Division of the City of Tshwane Metropolitan Municipality as a result of management decisions. The results of the study showed contrasting opinions and perceptions amongst all participants on the repairs and maintenance activities of public lighting. Both employees working in the maintenance operations and public lighting sections agreed that their sections were performing the repairs and maintenance of public lighting satisfactory. Customers and community leaders on the other hand agreed that the maintenance operations sections are performing the repairs and maintenance of public lighting satisfactory as compared to public lighting section. All employees were in favour and support of decisions taken respectively since these decisions were beneficial to their respective sections, but however they were concerned on the frequency of decisions taken by top management and changes implemented within their respective sections as these decisions and changes created confusion and conflict amongst employees. All sections involved in the repairs and maintenance of public lighting were faced with numerous similar challenges that created deficiencies and ineffectiveness on the maintenance activities of public lighting and that contributed to enormous complaints from customers and community leaders on the service rendered by the division.

Procuring combat systems in the Department of Defense is a balancing act where many variables, only some under control of the department, shift simultaneously. Technology changes non-linearly, providing new opportunities and new challenges to the existing and potential force. Money available changes year over year to fit into the overall US Government budget. Numbers of employees change through political demands rather than by cost-effectiveness considerations. The intent is to provide the best mix of equipment to field the best force against an expected enemy while maintaining adequate capability against the unexpected. Confounding this desire is the inability of current simulations to dynamically model changing capabilities and the very large universe of potential combinations of equipment and tactics.;The problem can be characterized as a stochastic, mixed-integer, non-linear optimization problem. This dissertation proposes to combine an agent-based model developed to test solutions that constitute both equipment capabilities and tactics with a co-evolutionary genetic algorithm to search this hyper-dimensional solution space. In the process, the dissertation develops the theoretical underpinning for using agent-based simulations to model combat. It also provides the theoretical basis for improvement of search effectiveness by co-evolving multiple systems simultaneously, which increases exploitation of good schemata and widens exploration of new schemata. Further, it demonstrates the effectiveness of using agent-based models and co-evolution in this application confirming the theoretical results.;An open research issue is the value of increased information in a system. This dissertation uses the combination of an agent-based model with a co-evolutionary genetic algorithm to explore the value added by increasing information in a system. The result was an increased number of fit solutions, rather than an increase in the fitness of the best solutions. Formerly unfit solutions were improved by increasing the information available making them competitive with the most fit solutions whereas already fit solutions were not improved.

Optimization of electronic warfare (EW) receiver scan strategies is critical to improving the probability of surviving military missions in hostile environments. The problem is that the limited understanding of how dynamic variations in radar and EW receiver characteristics has influenced the response time to detect enemy threats. The dependent variable was the EW receiver response time and the 4 independent variables were EW receiver revisit interval, EW receiver dwell time, radar scan time, and radar illumination time. Previous researchers have not explained how dynamic variations of independent variables affected response time. The purpose of this experimental study was to develop a model to understand how dynamic variations of the independent variables influenced response time. Queuing theory provided the theoretical foundation for the study using Little's formula to determine the ideal EW receiver revisit interval as it states the mathematical relationship among the variables. Findings from a simulation that produced 17,000 data points indicated that Little's formula was valid for use in EW receivers. Findings also demonstrated that variation of the independent variables had a small but statistically significant effect on the average response time. The most significant finding was the sensitivity in the variance of response time given minor differences of the test conditions, which can lead to unexpectedly long response times. Military users and designers of EW systems benefit most from this study by optimizing system response time, thus improving survivability. Additionally, this research demonstrated a method that may improve EW product development times and reduce the cost to taxpayers through more efficient test and evaluation techniques.

The feasibility of developing test circuits to perform in-circuit testing of analog circuits is investigated in this thesis. A modular approach to analog testing has been adopted. Accordingly, the testing of an operational amplifier, which is a basic building block in analog circuits, is addressed. One convenient technique for measuring the frequency response of an op-amp requires a unity gain buffer to be inserted into its feedback loop. This buffer has to be simple in construction, small and accurate. Two buffer circuits that satisfy these requirements are described in this thesis. Enhanced slewing techniques are devised to achieve increased levels of performance. The buffers were integrated with an op-amp into a test chip. Digital logic is used to provide controllability and accessibility to each of the buffers and the op-amp so that they can characterized separately. The performance of the enhanced slewing buffers was verified with measurements performed on the test chip. The performance of the buffers conformed well with the simulated values. The buffers exhibited excellent settling times even while driving large capacitive loads. Their output swing and distortion performance were good for inputs as large as 2 V peak-to-peak values. / Graduation date: 1994

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 196-211).

In oil/gas and chemical industries, dynamics is one of the most essential characteristics of any process. Time-dependent response is involved in most steps of both the physical/engineering processes and the equipment performance. The conventional Quantitative Risk Assessment (QRA) is unable to address the time dependent effect in such dynamic processes. In this dissertation, a methodology of Dynamic Operational Risk Assessment (DORA) is developed for operational risk analysis in oil/gas and chemical industries. Given the assumption that the component performance state determines the value of parameters in process dynamics equations, the DORA probabilistic modeling integrates stochastic modeling and process dynamics modeling to evaluate operational risk. The stochastic system-state trajectory is modeled based on the abnormal behavior or failure of the components. For each of the possible system-state trajectories, a process dynamics evaluation is carried out to check whether process variables, e.g., level, flow rate, temperature, pressure, or chemical concentration, remain in their desirable regions. Monte Carlo simulations are performed to calculate the probability of process variable exceeding the safety boundaries. Component testing/inspection intervals and repair time are critical parameters to define the system-state configuration; and play an important role for evaluating the probability of operational failure. Sensitivity analysis is suggested to assist selecting the DORA probabilistic modeling inputs. In this study, probabilistic approach to characterize uncertainty associated with QRA is proposed to analyze data and experiment results in order to enhance the understanding of uncertainty and improve the accuracy of the risk estimation. Different scenarios on an oil/gas separation system were used to demonstrate the application of DORA method, and approaches are proposed for sensitivity and uncertainty analysis. Case study on a knockout drum in the distillation unit of a refinery process shows that the epistemic uncertainty associated with the risk estimation is reduced through Bayesian updating of the generic reliability information using plant specific real time testing or reliability data. Case study on an oil/gas separator component inspection interval optimization illustrates the cost benefit analysis in DORA framework and how DORA probabilistic modeling can be used as a tool for decision making. DORA not only provides a framework to evaluate the dynamic operational risk in oil/gas and chemical industries, but also guides the process design and optimization of the critical parameters such as component inspection intervals.