Thesis--M. Phil., University of Hong Kong, 1979. / Xeorx copy of typescript.

Thesis (MTech (Business Administration))--Peninsula Technikon, 2001 / Maintenance of locomotives is the main function of Bellville Locomotive Traction Depot in the Western Cape. Therefore, it is important to have a sound maintenance plan in place, to prevent a negative impact on the availability and reliability of locomotive supply for hauling power to train services. The purpose of the research is to determine the causes of the increased frequency of maintenance through a case study relating to 35-class locomotives. The abnormal increased frequency of wheel change and inter-bogie control repairs on 35-class diesel locomotives is investigated. A research survey was adopted, which included questionnaires and personal interviews based on the literature search. The target group is L&N section, which includes below-deck maintenance, overhaul and change out, repairs to locomotive bogies, frames, wheels, snubbers, inter-bogie control and traction motors. Sixteen people are responsible for all below-deck repairs and service of 52 locomotives. The results of the research will expose the shortcomings of the maintenance plan and propose solutions. This will be achieved by testing the effectiveness of the existing maintenance plan at Spoornet through the identification of the causes for the abnormal increase in wheel changes and inter-bogie control repairs on 35-class diesel locomotives. The outcome from this case study research will be to quantify the benefits arising from the effective application of a maintenance plan.

A model which helps system designers to jointly evaluate a repairable equipment population system and its associated logistics support subsystem is developed. The modeled system consists of a deployed population of repairable equipment and a logistics support subsystem consisting of repair channels and an inventory of consumable components. In the system, a population of identical repairable equipment is procured and deployed to meet a known and constant demand. As the equipment fails, it is repaired and returned to service. Equipment repair generates secondary demands for consumable components and spares. Backorders within the inventory support subsystem add to the time failed equipment is not in service. The model returns optimal values for the number of equipment units to deploy, the number of maintenance channels, the retirement age of deployed units, the procurement level, and the procurement quantity. These values are optimal in that they minimize the expected equivalent annual life-cycle cost of the system. The best system design may then be selected from among candidate designs on the basis of minimum life-cycle cost. Previous attempts at integrated logistic system evaluation have led to suboptimal results because evaluation of the repairable equipment population system was disconnected from the evaluation of the inventory subsystem. Where inventory backorders are allowed, there are tradeoffs between system-level shortage costs and the cost of procuring and holding inventory.The backordered consumable components contribute to equipment repair times by increasing the time spent in repair. Furthermore, the procurement of additional repairable equipment to offset shortage penalties may result in increased logistics support costs which must be accounted for when evaluating system design alternatives. This thesis presents a model for a repairable equipment population system with its associated logistics support subsystem. The evaluation function is developed along with assumptions and definitions of the cost elements. A numerical example which illustrates some basic aspects of the model is given. Finally, an optimization routine is presented which returns an optimal set of system design variables for a given set of design and source dependent parameters in the face of design and source independent parameters. / Master of Science

A concept for the mathematical modeling of multiple repairable equipment and logistic systems (MREAL systems) is developed; These systems consist of multiple populations of repairable equipment, and their associated design, procurement, maintenance, and supply support. MREAL systems present management and design problems which parallel the·management and design of multiple, consumable item inventory systems. However, the MREAL system is more complex since it has a repair component. The MREAL system concept is described in a classification hierarchy which attempts to categorize the components of such systems. A specific mathematical model (MREAL1) is developed for a subset of these components. Included in MREAL1 are representations of the equipment reliability and maintainability design problem, the maintenance capacity problem, the retirement age problem, and the population size problem, for each of the multiple populations. MREAL1 models the steady state stochastic behavior of the equipment repair facilities using an approximation which is based upon the finite source, multiple server queuing system. System performance measures included in MREAL1 are: the expected MREAL total system life cycle cost (including a shortage cost penalty); the steady state expected number of shortages; the probability of catastrophic failure in each equipment population; and two budget based measures of effectiveness. Two optimization methods are described for a test problem developed for MREAL1. The first method computes values of the objective function and the constraints for a specified subset of the solution space. The best feasible solution found is recorded. This method can also examine all possible solutions, or can be used in a manual search. The second optimization method performs an exhaustive enumeration. of the combinatorial programming portion of MREAL1, which represents equipment design. For each enumerated design combination, an attempt is made to find the optimal solution to the remaining nonlinear discrete programming problem. A sequential unconstrained minimization technique is used which is based on an augmented Lagrangian penalty function adapted to the integer nature of MREAL1. The unconstrained minimization is performed by a combination of Rosenbrock's search technique, the steepest descent method, and Fibonacci line searches, adapted to the integer nature of the search. Since the model contains many discrete local minima, the sequential unconstrained minimization is repeated from different starting solutions, based upon a heuristic selection procedure. A gradient projection method provides the termination criteria for each unconstrained minimization. / Ph. D.

A thesis submitted in fulfillment of the requirements for the Degree of Doctor of Philosophy, School of Statistics and Actuarial Science, Faculty of Science University of Witwatersrand, Johannesburg. February 2017. / The work done in this thesis on finite planning horizon inspection models has demonstrated that with the advent of powerful computers these days it is possible to easily find an optimal inspection schedule when the lifetime distribution is known. For the case of system time to failure following a uniform distribution, a result for the maximum number of inspections for the finite planning models has been derived. If the time to failure follows an exponential distribution, it has been noted that periodically carrying out inspections may not result in maximization of expected profit. For the Weibull distributions family (of which the exponential distribution is a special case), evenly spreading the inspections over a given finite planning horizon may not lead to any serious prejudice in profit. The case of inspection models where inspections are of non-negligible duration has also been explored. The conditions necessary for inspections that are evenly spread over the entire planning horizon to be near-optimal when system time to failure either follows a uniform distribution or exponential distribution have been explored. Finite and infinite planning horizon models where inspections are imperfect have been researched on. Interesting observations on the impact of Type I and Type II errors in inspection have been made. These observations are listed on page 174. A clear and easy to implement road map on how to get an optimal inspection permutation in problems first discussed by Zuckerman (1989) and later reviewed by Qiu (1991) for both the undiscounted and discounted cases has been given. The only challenge envisaged when a system has a large number of components is that of computer memory requirements - which nowadays is fast being overcome. In particular, it has been clearly demonstrated that the impact of repair times and per unit of time repair costs on the optimal inspection permutation cannot be ignored. The ideas and procedures of determining optimal inspection permutations which have been developed in this thesis will no doubt lead to huge cost savings especially for systems where the cost of inspecting components is huge. / XL2018

M.Ing. (Mechanical Engineering) / Considering the high cost of maintenance, effective maintenance management have the potential to contribute to the profit of a petrochemical business. The complexity of the maintenance domain in the petrochemical business demands the use of information systems for the management of maintenance. The availability of correct, easily interpretable information about maintenance can therefore contribute to the profit of a petrochemical business. Management decisions are based on available information. The quality (accuracy and timeliness) of the information create more room for creative decisions in the maintenance department. A computerized information management system is a tool employed in the optimization of maintenance cost and a requirement for world class maintenance. This system depends on information of a high quality. It should be kept in mind that this systems is an aid to maintenance management and would never be able to replace the maintenance manager. The role played by high quality information in the success of a computerized maintenance management system point towards the importance of the personnel that maintain the system and those that provide input to the system. These personnel need to be highlytrained and should have the most recent technology available. Continuing development of the computerized maintenance management system within a company is necessary for the system to succeed.

M.Phil. / In the modern world maintenance organisations are exposed to rapid changes in equipment complexity and the maintenance thereof. Maintenance people have to adopt completely new ways of thinking and managing. If organisations and their management do not adapt to these changes and challenges they are destined to oblivion. Moubray (1991:1) states that: "Managers everywhere are looking for a new approach in maintenance. They want to avoid the false starts and dead ends which always accompany major upheavals. Instead they seek a strategic framework which synthesizes the new developments into a coherent pattern, so that they can evaluate them sensibly and apply those likely to be of most value to them and their companies" One of the viable alternative business strategies and maintenance approaches in dealing with equipment complexity and hence the management thereof, is by means of maintenance outsourcing and contract setting. If done correctly it reduces the risk of organisations and increases flexibility. During outsourcing initiatives organisations will look for benefits such as improvement of its profit margins by means of inventory reductions, improved reliability, maintenance efficiency and expert skills maintaining their assets. Coetzee (1997:24) explain that the task of the maintenance function is "to support the production process with adequate levels of availability, reliability and operability at an acceptable cost". The same principles apply in adherence to the maintenance contracts where the Original Equipment Manufacturer (OEM) or contractor also needs to support the customer with the adequate levels of availability, reliability and operability at defined costs. This can only be achieved by quality maintenance; "the right level of maintenance performed at the right time to the right equipment by workmen able and willing to deliver quality workmanship and using correct task specifications" (Coetzee, 2000a). The method used in maintenance outsourcing negotiation and binding agreements between the organisation and the contractor is a Repair and Olivier-2008 Department of Mechanical and Manufacturing Engineering - UJ Maintenance Contract; commonly known as R+M or MARC contracts. Essentially a Repair and Maintenance contract is the outsourcing of a long term Service Level Agreement (SLA) or maintenance project, normally to the OEM, or its authorised service organisation. "A maintenance and repair contract is a contractual agreement between the OEM (original equipment manufacturer), or contractor, and the equipment owner or user, where the OEM or contractor carries out all maintenance and repair activities at a guaranteed rate per hour" (Lugtigheid, et al. 2007). When organisations adapt outsourcing as a business strategy, it creates a framework of uncertainty and risk to Original Equipment Manufactures and/or maintenance contractors who has to perform the maintenance services. The focus of manufacturing and selling is thus disrupted by the challenge of the unknown playgrounds of competitiveness

There is a world-wide drive to optimize maintenance decisions in an increasingly competitive manufacturing industry. Preventive maintenance if often the most organized and cost efficient strategy to follow, but a decision still has to be made on the optimal instant to perform preventive maintenance. Use based preventive maintenance decisions have been optimized through statistical analysis of failure date while predictive preventive maintenance (condition monitoring) has been optimized by utilizing more sophisticated technology. Very little work has however been done to combine the advantages of the two schools of thought. This thesis originated from a realization of the potential improvement in maintenance practice by combining use based preventive maintenance optimization techniques with high technology condition monitoring. In this thesis an approach is developed to estimate residual life of industrial equipment dynamically by combining statistical failure analysis and sophisticated condition monitoring technology. The approach is based on failure intensity proportions determined from historic survival time information and corresponding diagnostic information such as condition monitoring. Combined Proportional Intensity Models (PIMs) for non-repairable and repairable systems, containing the majority of conventional PIM enhancements as special cases, with numerical optimization techniques to solve for the regression coefficients, are derived. In addition to the residual life estimation approach, a user-friendly graphical method with which residual life estimates can be presented was also developed. This method is natural and easy to comprehend, even by inexperienced data analysts. The residual life estimation approach is applied to a typical data set from a South African industry and results are compared to those obtained from a similar, established maintenance decision support tool. This comparison showed that the approach developed in this thesis is relevant, practical and marginally better than the established decision support tool for certain criteria. / Thesis (PhD (Industrial Engineering))--University of Pretoria, 2006. / Industrial and Systems Engineering / unrestricted

This treatise investigates the underlying factors that are hindering the improvement of Overall Equipment Effectiveness at the Ford Struandale Engine Plant. In January of 2008 the Ford Motor Company announced plans to invest more than R1.5 billion to expand operations for the production of Ford's next-generation compact pickup truck and the PUMA diesel engine. Ford will use the investment to expand operations both in Silverton for the production of 75 000 units of a new bakkie and in Port Elizabeth for 220 000 units of its new-generation PUMA diesel engines (http://www.autoblog.com /2008/01/31/ford-to-invest-209m-in-south-africa-for-new-ranger-pickup/). Only five Ford plants globally will be producing the PUMA engine (Turkey, UK, Thailand, Argentina and South Africa – Ford Struandale Engine Plant). The Ford Struandale Engine Plant will be the only plant which will have the I4 assembly, I5 assembly and 3C (Crank, Cylinder Block, and Cylinder Head) machining and the expectations of operating in a lean environment is high. The management team at the Ford Struandale Engine Plant needs to understand what the underlying factors that are hindering the improvement of Overall Equipment Effectiveness of the plant or, in other words, they need to be informed of the total benefits of TPM. A literature review was conducted to determine what the theory reveals about Overall Equipment Effectiveness, the three factors of OEE (Availability, Performance Efficiency, and Quality), the influence of Six Big Losses on each of the factors and the role of Total Productive Maintenance in improving OEE by eliminating these Six Big Losses. A Ford literature study was conducted to reveal the current literature being applied at Ford. This was then followed by an empirical survey conducted within the Ford Struandale Engine Plant. In addition, a task team formed to analyse the current maintenance operating strategy. Finally, the findings from discussions with the task team, the empirical survey, Ford Struandale Engine Plant literature survey and a general literature survey were amalgamated to draw conclusions relating to the Ford Struandale Engine Plant. These conclusions indicate what the underlying factors are that are hindering the improvement of Overall Equipment Effectiveness of the Ford Struandale Engine Plant facilities and equipment. Then recommendations are made as to how the Ford Struandale Engine Plant can improve the Overall Equipment Effectiveness of its facilities and equipment.

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.