No description available.

Design of a repairable item and its logistic support system requires consideration of several interrelated decision problems. These decision problems concern the variables, controllable by the design engineer and/or system manager, which affect system performance. This research develops a framework for integration of these decision problems and evaluation of system design tradeoffs. These design decision problems are represented in the model base of a decision support system (DSS). Interrelationships between decision problems are defined using data flow diagrams. Data flows within and between these decision problems are integrated in the DSS database. A simulation capability, imbedded into the DSS permits short-term, accelerated time excursions into possible futures for decision-making purposes. Alternative system designs are evaluated using a multicriteria decision model which considers reliability, maintainability, availability, and life cycle costs. The logistic support system is modeled as a multilevel inventory system. These inventories include spare repairable items, spare parts, labor, maintenance equipment, and other support resources. Repairable item and logistic support system design decision problems affect the quantity and location of these inventories. Five decision problems identified by Moore [1986] were selected to demonstrate the utility of this framework. The selected decision problems are: 1) the equipment design problem; 2) the maintenance configuration problem; 3) the spare equipment problem; 4) the level of repair problem; and 5) the replacement policy problem. The framework developed supports integration of these decision problems throughout the item’s life cycle. A repairable item can be systematically divided into subelements until individual repairable components are identified. This systematic subdivision of the item produces an inverted, tree-like structure. This structure is used as the representational view of the DSS database. As the life cycle progresses and the item design becomes more detailed, the structure expands. The DSS database is designed to accommodate this expansion so that the framework can be used throughout the item’s life cycle. The initial fielding and the retirement of the repairable item population produces nonstationary demands on the logistics support system. A multistream model captures the nonstationary aspects of demand, eliminating the need for item-by-item tracking within the model. The framework developed is illustrated using a comprehensive case study. The case study addresses the design of a Side Loadable Warping Tug (SLWT) and its logistics support system. A population of SLWT’s must be deployed to meet demands in two different operating environments. The SLWT is a component of the U.S. Navy’s Container Offloading and Transfer System (COTS). / Ph. D.

In 1991, seven corrosion inhibitors, surface applied liquids and concrete admixtures, were identified as promising for the repair of reinforced concrete structures subject to chloride induced corrosion. Small scale (1 ft.²) reinforced concrete specimens were cast to evaluate the inhibitors effectiveness. A treatment matrix was established to evaluate the inhibitors performance on three ranges of corrosion activity and evaluate the effect of application time and drying. Corrosion rate measurements taken with a linear polarization device were used to monitor the inhibitors effectiveness. The effect of the admixtures on the concrete properties, and the effect of the surface applied inhibitors on the overlay bond strength were evaluated. Rapid freeze-thaw tests were conducted to estimate the durability of the inhibitor modified concrete. Three combinations of inhibitors were identified for large scale testing after ten months of accelerated chloride exposure. The larger specimens, removed from an actual bridge deck, were treated to test the effective inhibitors field application techniques. Service life estimates were made for the two combinations of inhibitors which were most effective to aid the engineer in assessing the inhibitors cost effectiveness. / Master of Science

Master of Science

Master of Science

The purpose of this study is to analyze the adequacy of the automobile mechanics courses taught in certain Texas high schools to determine (1) what high schools of Texas offer courses in auto mechanics; (2) in what place in the curriculum are such courses offered; (3) what methods of teaching auto mechanics are being used; (4) how many units are offered and what is contained in each unit; and (5) the opinions of the school administrators, auto mechanics teachers, and industrial arts teachers as to what should be taught in the auto mechanics courses.

As construction of the nation’s interstate highway system nears completion, the emphasis must now be focussed on the rehabilitation of many of the older sections of the system which have undergone damage or deterioration. The efficiency and effectiveness of the concrete removal operation will profoundly affect the outcome of the bridge rehabilitation. Pneumatic breakers, milling machines, and hydro-demolition are three concrete removal technologies utilized to remove concrete that has experienced various levels of damage or deterioration. A general examination of the three technologies is presented in the following five areas: the equipment, the work, production, cost, and quality. The information was primarily obtained through interviews and discussions with persons involved in bridge rehabilitation: contractors, State Highway Agency personnel, and equipment manufacturers and distributors. It is anticipated that the information presented will enable persons involved in the bridge rehabilitation industry to more effectively utilize the technologies discussed. / Master of Science

No description available.

A municipal water distribution system is a network of underground pipes, usually mirroring the city street network, that connects water supply sources such as reservoirs and water towers with demand points such as residential homes, industrial sites and fire hydrants. These systems are extremely expensive to install, with costs typically in the tens of millions of dollars. Existing pipes wear out, leak and break due to various factors including corrosion and cold weather ruptures, each requiring inconvenient and expensive repairs. Therefore, over time, these pipes need to be considered for replacement. Meanwhile, increasing urban development and water use rates dictate the need for larger and larger pipes to handle increased flow rates, while keeping water pressure within an acceptable range. However, larger pipes cost considerably more to install and maintain, causing the pipe sizing decision to be a critical task. We develop an optimal network design and replacement strategy that meets hydraulic requirements under all likely demand and failure scenarios. Two submodels are used in a hierarchical fashion to integrate the reliability and cost analysis, and the network optimization process, within the overall network design process. The pipe reliability and cost submodel uses statistical methodologies based on historical records of pipe breaks to estimate future maintenance costs, and to recommend replacing relatively expensive-to-maintain or undercapacitated pipes. The pipe network optimization submodel provides a least cost construction and replacement plan along with optimal flows and energy heads for each fixed network configuration and demand pattern. Traditional approaches isolate the above two types of models, assuming away the required interaction of inputs and outputs between them. We use a hierarchical design approach that integrates the foregoing two submodels by designing the network in a sequential fashion over a number of stages. The models are tied in a feedback loop that reprocesses the information until a stable design is attained. The result is a comprehensive reduced cost network design that meets all pressure and flow requirements for realistic problems, even under a wide variety of pipe failure modes. For the optimization model, we develop two new algorithms that exploit the special network structure of the problem. In the first approach, the problem is restructured in a manner that facilitates its decomposition into a master control program, and an easy-to-solve convex cost network flow programming subproblem. The master program operates in the space of the structural design variables, while the subproblem determines flows as well as heads via its primal and dual optimal solutions. The coordination between the master program and the subproblems is effected via a suitable penalty term. The theoretical validity of the decomposition scheme is established, and efficient algorithmic implementation strategies are developed. On a standard popular test problem in the literature, this procedure is shown to recover a solution that significantly improves upon a previously best known solution. The second optimization approach is one that guarantees a global optimal solution, and contrasts with previous approaches that at best produce local optimal solutions. This procedure is based on a Reformulation-Linearization Technique that constructs tight linear programming relaxations for the nonlinear problem, and embeds these in a branch-and-bound algorithm. A suitable partitioning strategy is coordinated with this scheme to provably ensure infinite convergence to a global optimum. When this method is applied to the aforementioned test problem, a further improved solution is obtained. It is hoped that with additional enhancements and refinements, our proposed methodologies will serve to provide a useful tool for practitioners to design reliable pipe network water distribution systems. / Ph. D.

Thesis (M. Tech.) -- Central University of Technology, Free State, 2010 / Traditional corrective maintenance is both costly and ineffective. In some situations it is more cost effective to replace a device than to maintain it; however it is far more likely that the cost of the device far outweighs the cost of performing routine maintenance. These device related costs coupled with the profit loss due to reduced production levels, makes this reactive maintenance approach unacceptably inefficient in many situations. Blind predictive maintenance without considering the actual physical state of the hardware is an improvement, but is still far from ideal. Simply maintaining devices on a schedule without taking into account the operational hours and workload can be a costly mistake. The inefficiencies associated with these approaches have contributed to the development of proactive maintenance strategies. These approaches take the device health state into account. For this reason, proactive maintenance strategies are inherently more efficient compared to the aforementioned traditional approaches. Predicting the health degradation of devices allows for easier anticipation of the required maintenance resources and costs. Maintenance can also be scheduled to accommodate production needs. This work represents the design and simulation of an intelligent maintenance management system that incorporates device health prognosis with maintenance schedule generation. The simulation scenario provided prognostic data to be used to schedule devices for maintenance. A production rule engine was provided with a feasible starting schedule. This schedule was then improved and the process was determined by adhering to a set of criteria. Benchmarks were conducted to show the benefit of optimising the starting schedule and the results were presented as proof. Improving on existing maintenance approaches will result in several benefits for an organisation. Eliminating the need to address unexpected failures or perform maintenance prematurely will ensure that the relevant resources are available when they are required. This will in turn reduce the expenditure related to wasted maintenance resources without compromising the health of devices or systems in the organisation.