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M. Tech. Business Administration / The research reviews how the implementation of total productive maintenance (TPM), as a maintenance strategy, can be adopted at DCD Wind Towers (Pty) Ltd., a wind tower manufacturing company in South Africa. It also focuses on maintenance management programmes, identifies obstacles, barriers and challenges to the implementation of maintenance management programmes.

Orientador: Gabriel Alves da Costa Lima / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica e Instituto de Geociências / Made available in DSpace on 2018-08-21T23:40:04Z (GMT). No. of bitstreams: 1 Cesca_IgorGimenes_M.pdf: 2631356 bytes, checksum: 457c322ac2cc3cffc8315b485825f863 (MD5) Previous issue date: 2012 / Resumo: No setor energético (mineração, energia elétrica e petróleo), o conhecimento do comportamento dos custos dos equipamentos em seus ciclos de vida se torna muito importante devido a: (1) alto custo de aquisição e (2) elevadas despesas de manutenção. Dessa maneira, a aquisição de um ativo físico não deve ser decidida somente com base no custo inicial, mas sim por meio do custo do ciclo de vida desse ativo. Para esta dissertação foi elaborado um modelo matemático para encontrar a vida econômica e realizar previsões de custos de manutenção de um grupo de ativos físicos empregados no setor energético. Sendo assim, isso ocorre por meio de: (1) programação dinâmica, utilizando o modelo clássico de Bellman para reposição de equipamentos; (2) engenharia econômica, de tal forma que a vida econômica dos equipamentos é modelada por meio da função W de Lambert e (3) técnicas econométricas de previsão, tal que a relação entre os custos de manutenção e a idade dos equipamentos é testada por formas funcionais de regressões lineares simples. Com isso, para modelagem de vida econômica, foi possível estabelecer teoremas e, para previsão de custos de manutenção, foi possível perceber que as variáveis possuem uma relação não linear entre elas. Portanto, foi possível concluir que os equipamentos podem ser utilizados de maneira mais eficiente e com menores custos de ciclo de vida incorporados, uma vez que seja aplicada uma gestão econômica com base no modelo proposto nesta dissertação e, consequentemente, também possibilitar obter melhores indicadores financeiros para as empresas do setor energético / Abstract: In the energy sector (mining, oil and electricity), the knowledge of the asset's behavior in their life-cycle costs becomes very important because of: (1) the high cost of acquisition and (2) the high maintenance expenses. Thus, the acquisition of a physical asset should not be decided only on the basis of its initial cost, but through the consideration of its entire life cycle cost. In this dissertation a mathematical model of economic life and maintenance costs forecasts of a group of physical assets is developed and employed in the analysis of problems in the energy sector. The model considers the following: (1) dynamic programming, using the classical Bellman model for equipment replacement; (2) engineering economics, using to model the economic life of the equipment the equivalent cost theory and Lambert W-function and (3) econometric forecasting techniques, such that the relationship between the maintenance costs and equipment age are tested for functional forms of linear regressions. Therefore, on economic life modeling, it was possible to establish theorems and on maintenance costs forecasting. It was revealed that the variables have a nonlinear relationship between them. To conclude, physical assets can be used more efficiently and at lower life-cycle costs incorporated with the application of models developed in this dissertation and, consequently, contribute to obtain better financial indicators for companies in the energy sector / Mestrado / Reservatórios e Gestão / Mestre em Ciências e Engenharia de Petróleo

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.