In order to produce products and services, companies are using various tangible assets such as production equipment and facilities. The goal of the maintenance function is to maintain these assets so they operate safely, efficiently and economically. This function includes technical, administrative and management activities, carried out in order to keep company’s assets in a state, or restore these to a state, in which they can perform the required functions. The activities should be planned and carried out in a way that allows for obtaining the required technical condition, availability, meets the safety requirements for humans and the environment, ensures quality of delivered products and services, and secures the anticipated service life of individual devices. Both effectiveness and efficiency of the maintenance function are very important to each company trying to operate with profit. As follows from the recent research, the performance of maintenance functions in most of the studied companies around the world is in general unsatisfactory, and the underlying reasons of the subnormal behavior are not sufficiently identified, understood and described.   The result of research presented in this thesis is an improvement support system based on an explanatory model of the maintenance function. This model shows the mechanisms interconnecting the motivations, intents and rationale behind the involved actors, entities and maintenance activities, and in this way gains understanding of how, and in what way the total performance of the maintenance function is affected, thereby supporting improvement decisions. As maintenance cost is a sharply increasing part of the operational costs, it is an evident target for operational and managerial improvement. This research area is strongly encouraged by industry, and is becoming a topic of increasing interest in the academia. / <p>QC 20151117</p>

Thesis (MEng)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: The railway transportation system is fundamental in sustaining the economic activities of a country, by providing a safe, reliable and relatively affordable means of transporting people and goods; hence, the need to ensure its ongoing reliability is of paramount importance. The principle and applications of rail reliability have been reviewed, and reliability improvement in rail infrastructure has been investigated using failure mode and effect analysis (FMEA). Reliability improvement is a continuous process that is geared to meeting dynamic changes in operation and stakeholders’ expectations. Recently, growth has occurred in the amount of rail transport traffic utilisation undertaken, together with the degradation of the infrastructure involved. Such deterioration has amplified the operating risks, leading to an inadequacy in rail track maintenance and inspection that should have kept abreast with the changes. The result has been increased rail failures, and subsequent derailments. A case study of the Passenger Rail Agency of South Africa (PRASA) Metrorail maintenance policy was reviewed to evaluate its maintenance strategy and identifying the potential critical failure modes, so as to be able to recommend improvement of its reliability, and, thus, its availability. On the basis of the case study of PRASA Metrorail maintenance strategy and its performance, it is recommended that PRASA Metrorail change its maintenance policy through employing a cluster maintenance strategy for each depot. / AFRIKAANSE OPSOMMING: Die spoorwegvervoerstelsel is fundamenteel om die ekonomiese bedrywighede van ’n land te ondersteun deur die voorsiening van ’n veilige, betroubare en betreklik bekostigbare manier om mense en goedere te vervoer. Dus is dit van die allergrootste belang om die voortgesette betroubaarheid daarvan te verseker. Die beginsels en toepassings van spoorbetroubaarheid is hersien en die betroubaarheidsverbetering van spoorinfrastruktuur met behulp van foutmodus-eneffekontleding (“FMEA”) ondersoek. Betroubaarheidsverbetering is ’n voortdurende proses om tred te hou met dinamiese bedryfsveranderinge sowel as verskuiwings in belanghebbendes se verwagtinge. Die hoeveelheid spoorvervoerverkeer het onlangs beduidend toegeneem, terwyl die betrokke infrastruktuur agteruitgegaan het. Dié agteruitgang het die bedryfsrisiko’s verhoog, en lei tot ontoereikende spoorweginstandhouding en -inspeksie, wat veronderstel was om met die veranderinge tred te gehou het. Dit gee aanleiding tot ’n toename in spoorwegfoute en gevolglike ontsporing. ’n Gevallestudie is van die instandhoudingsbeleid van die Passasierspooragentskap van Suid- Afrika (PRASA) Metrorail onderneem om dié organisasie se instandhoudingstrategie te beoordeel en die moontlike kritieke foutmodusse te bepaal. Die doel hiermee was om verbeteringe in stelselbetroubaarheid en dus ook stelselbeskikbaarheid voor te stel. Op grond van die gevallestudie van die PRASA Metrorail-instandhoudingstrategie en -prestasie, word daar aanbeveel dat PRASA Metrorail sy instandhoudingsbeleid verander deur ’n klusterinstandhoudingsplan vir elke depot in werking te stel.

The needs of contemporary electric utility customers and expectations regarding energy supply require dramatic changes in the way energy is transmitted and delivered. A smart grid is a concept by which the existing and aging electrical grid infrastructure is being upgraded with integration of multiple applications and technologies; such as two way power transfer, two way communication, renewable distributed generation, automated sensors, automated & advanced controls, central control, forecasting system and microgrids. This enables the grid to be more secure, reliable, efficient, self-healing, while reducing greenhouse gases. In addition, it will provide new products & services and fully optimize asset utilization. Also, integration of these innovative technologies to establish a smart grid poses new challenges. There will be need for new tools to assess and predict reliability issues. The goal of this research is both to demonstrate these new electrical system tools and to monitor and analyze the relationship of weather and electrical infrastructure interruptions. This goal will be accomplished by modeling weather and distribution system reliability issues, by developing forecasting tools and finally developing mathematical models for system availability with smart grid functionality. Expected results include the ability to predict and determine the number of interruptions in a defined region; a novel method for calculating a smart grid system’s availability; a novel method for normalizing reliability indices; and to determine manpower needs, inventory needs, and fast restoration strategies. The reliability of modern power distribution systems is dependent on many variables such as load capacity, renewable distributed generation, customer base, maintenance, age, and type of equipment. This research effort attempts to study these areas and in the process, has developed novel models and methods to calculate and predict the reliability of a smart grid distribution system. A smart grid system, along with variable weather conditions, poses new challenges to existing grid systems in terms of reliability, grid hardening, and security. The modern grid is comprised of various distributed generation systems. New methods are required to understand and calculate availability of a smart grid system. One such effort is demonstrated in this research. The method that was developed for modeling smart grid dynamic reconfigurations under variable weather conditions combines three modeling techniques: Markov modeling, Boolean Logic Driven Markov Process (BDMP) and the modeling of variable weather condition. This approach has advantages over conventional models because it allows complex dynamic models to be defined, while maintaining its easy readability.

This dissertation is a systematic study of electric power distribution system reliability evaluation and improvement. Reliability evaluation of electric power systems has traditionally been an integral part of planning and operation. Changes in the electric utility coupled with aging electric apparatus create a need for more realistic techniques for power system reliability modeling. This work presents a reliability evaluation technique that combines set theory and Graph Trace Analysis (GTA). Unlike the traditional Markov approach, this technique provides a fast solution for large system reliability evaluation by managing computer memory efficiently with iterators, assuming a single failure at a time. A reconfiguration for restoration algorithm is also created to enhance the accuracy of the reliability evaluation, considering multiple concurrent failures. As opposed to most restoration simulation methods used in reliability analysis, which convert restoration problems into mathematical models and only can solve radial systems, this new algorithm seeks the reconfiguration solution from topology characteristics of the network itself. As a result the new reconfiguration algorithm can handle systems with loops. In analyzing system reliability, this research takes into account time-varying load patterns, and seeks approaches that are financially justified. An exhaustive search scheme is used to calculate optimal locations for Distributed Generators (DG) from the reliability point of view. A Discrete Ascent Optimal Programming (DAOP) load shifting approach is proposed to provide low cost, reliability improvement solutions. As weather conditions have an important effect on distribution component failure rates, the influence of different types of storms has been incorporated into this study. Storm outage models are created based on ten years' worth of weather and power outage data. An observer is designed to predict the number of outages for an approaching or on going storm. A circuit corridor model is applied to investigate the relationship between power outages and lightning activity. / Ph. D.