The main aim of this thesis is to investigate available techniques and develop a methodology for the fault detection and diagnostics for two engineering systems, namely railway point systems (RPS) and three-phase separators (TPS). The fault detection of the RPS was performed on the measured current from the motor of point operating equipment (POE). The method of One Class Support Vector Machines has been chosen as the fault detection model. Elastic similarity measures, such as edit distance with real penalties and dynamic time warping, were chosen to compare the data of POE operations. A combination of Euclidean distance and elastic similarity measures has been proposed in order to take into account the absolute values and shape properties of the two compared time series. The proposed methodology has been tested on the in-field RPS data. The results indicated that the fault detection model was able to detect abnormal values and/or shape of the time series of measured current. However, not in all cases these changes could be related to a recorded failure of RPS in the database. The fault detection of TPS was performed given the sensor readings of flow and level transmitters of TPS. The method of Bayesian Belief Networks (BBN) has been proposed to overcome the late detection of faults with the threshold based alarm technique. An approach to observe sensor readings of TPS in several adjacent time intervals and to update the prior probabilities in the BBN after inserting the sensor readings as evidence was proposed. The proposed methodology has been tested on the data obtained from a TPS simulation model. The results indicated that the fault detection and diagnostics model was able to detect inconsistencies in sensor readings and link them to corresponding failure modes when single or multiple failures were present in the TPS.

M.Com. (Transport Economics) / In the past, air freight was generally a by-product of passenger orientated airlines in the sense that excess payload and unsold passenger seats were sold as air cargo space. In recent years, this trend has changed and it is observed that the air freight industry is increasingly becoming an industry in itself. The individual market share of scheduled international air freight operations within the air transport industry is currently approximately 35,8%. In South Africa, compared to the rest of the world, the historical development of air freight has been slower and confined primarily to the one national carrier (South African Airways (SAA)). The purpose of this study is, to firstly, determine the potential for growth in the air freight market within and outside South Africa. Secondly, to isolate and describe the factors within SAA which are sub-optimal and therefore have a negative impact on the development of the full potential of the air freight services of the carrier. The overall conclusion of the study is that the market for air freight within and outside of South Africa can be expanded significantly. This conclusion is dependent on the positioning and equipping of the freight division of SAA independently from passenger services, together with the provision of specialist knowledge and systems required for effective air freight management.

This thesis examines the effect of vehicle dynamics on lateral deterioration of the track alignment. As rail traffic runs along a route, the forces imposed upon the track cause the ballast to settle, and hence the track geometry deteriorates. At a specified value of deterioration the track geometry needs to be restored by tamping or other methods. As the deterioration is mainly in the vertical direction, this aspect has been more widely studied and models have been developed to predict vertical track geometry deterioration. On the other hand, lateral track deterioration is not as well understood, and this thesis aims to fill the gap in this knowledge. However, the understanding of the lateral deterioration mechanisms becomes more important as speed and capacity increase. This thesis describes statistical studies of track lateral deterioration, as well as the development and validation of a vehicle-track lateral dynamic interaction model. This work is undertaken to contribute to the fundamental understanding of the mechanisms of track lateral deterioration, therefore making the effective control and reduction of the lateral deterioration achievable. The statistical analysis provides a better understanding of three aspects of track lateral irregularities, namely: the relationship between vertical and lateral irregularities, the relationship between track curvature and track lateral irregularity and the change in track lateral deterioration over time. The vertical and lateral track irregularity magnitudes are clearly correlated. The track quality in the vertical direction is generally worse than in the lateral direction, however the number of track sections with lateral quality significantly worse than the vertical is non-negligible. The lateral irregularities tend to be larger on curves. It is notable that less than ten percent of the track studied has a constant lateral deterioration due to frequent maintenance activities and bidirectional lateral dynamic forces. Unlike vertical settlement, lateral deterioration develops exponentially in both magnitude and wavelength, and the major influences are found from the irregularities with wavelength longer than 10 m. The change in track lateral irregularity with different curve radii and the lateral deterioration rate are described in separate exponential power functions due to the limitation of the available track data. The parameters for these empirical equations do not remain constant due to the change in track conditions. Current track lateral models mainly focus on lateral failures such as buckling and lateral sliding. The development of lateral track irregularities tends to be studied using representative values of net lateral forces and net L/V (Lateral/Vertical) load ratios. Unlike other track lateral deterioration models, the model developed in this thesis focuses on the development of lateral irregularities based on the dynamic interactions between the vehicles and the track system. This model makes it possible to carry out more integrations and analysis of the track lateral deterioration in a realistic dynamic simulation, using vehicle models, contact conditions, track initial irregularities, and traffic mix more close to the reality. The vehicle-track lateral dynamic interaction model was validated against track geometry data measured on the West Coast Mainline (WCML) in England. It has been found that the model gives a reasonably accurate prediction of the development of lateral track irregularities. However, it also tends to predict a short wavelength deterioration that is not seen in the actual track deterioration. Improvements to the model are suggested by either adding more factors or simplifying the model depending on specific target application. Enhancing the model by including more details, such as longitudinal forces, temperature effect, more layered track systems, uneven track bed conditions and more representative wheel-rail contact conditions etc., may help understand the reason of the additional short wavelength. A sensitivity analysis was performed in order to identify the critical factors that influence lateral track deterioration. The track damage caused by specific vehicles can be controlled by understanding different vehicle dynamics behaviour on a particular track section or route. Vehicles with simple suspension design and heavy axle loads tend to cause more lateral track damage. Within a certain speed range, there will be a critical speed that generates the largest lateral deterioration. Vehicles with different dynamic behaviours can generate a potential offset of the lateral deterioration, so it is possible to design the traffic mix to cancel out the peak deterioration. However, it may not be very practical to redesign the traffic mix due to different traffic requirements. Subsequently, actions can be taken to effectively reduce track lateral deterioration, such as optimise the suspension design, vehicle weight, the selection of an optimal operation speed, and enhance the traffic mix design. As the most important interface between vehicle and track, the wheel-rail contact condition has an extremely large influence on lateral deterioration. Wheel and rail profiles with different wear conditions can cause altered vehicle-track lateral dynamic interaction. It is found that increasingly worn wheel/rail profiles within an acceptable tolerance can effectively reduce the lateral deterioration. Lateral deterioration can also be reduced by increasing all the track stiffness values, damping values and the mass of rails and sleepers, or alternatively, by decreasing the sleeper spacing. The sleeper-ballast interface is found to play the most important role in lateral deterioration. The interfaces between the sleeper and ballast shoulder, crib and base determines the non-linear characteristic such as hysteresis and sliding features. Improving the strength of the sleeper-ballast interface can improve the elastic limits and hysteresis characteristics, hence reducing the lateral deterioration. The findings of the investigation indicate that the model provides in-depth knowledge of the mechanisms influencing lateral deterioration and provides effective solutions with consideration of vehicles, wheel-rail contact and the track system. Further work would include track data with sufficient information in order to develop a more comprehensive empirical model that describes the lateral deterioration, inclusion of more potentially influential factors such as: temperature, ground condition, traffic etc. The model can be improved by taking into account additional factors such as the influence of longitudinal forces from the wheels to the rails, different weather and temperatures, subgrade and ground conditions, etc. The reason for the high frequency noise in the deterioration prediction is not understood yet and it should be discussed in terms of more accurate vehicle simulation results and more comprehensive rail and wheel worn profiles measured on the target track and vehicles. Furthermore, the sleeper-ballast lateral characteristics are not well understood and the previous research in this area is quite limited. To improve on the present work it would be useful to carry out laboratory tests in order to capture more accurately track lateral stiffness and damping values as well as the comprehensive non-linear characteristic of track lateral residual resistance behaviour.

It is important to study accidents and their underlying causes, in order to generate recommendations for improving system safety. A range of methods have been developed in various industries, to understand how accidents have occurred, as well as identify potential human errors in systems. Theories of accident causation, and the development of safety models and methods have evolved over the last few decades. However, the majority of accident analysis methods fail to account for the increasing complexity of socio-technical systems (Hollnagel, 2004 and Lindberg et al. 2010). Much of the previous research has taken a safety I perspective, which considers successful performance as reducing the number of adverse outcomes to as low as possible (Hollnagel, 2014). According to Hollnagel (2014) however, it is important to understand how operators actually carry out work (‘work-as-done’), rather than as it should be carried out (‘work-as-imagined’), to understand how normal variabilities and flexibilities in performance contribute towards both successful and unsuccessful performance. Understanding how work is normally carried out is essential for understanding how it can go wrong. This includes understanding how success is obtained, for example how people adjust their performance in the face of changing conditions and demands, and limited resources (such as time and information). Although variability and flexibility in performance are prerequisites for success and productivity, these can also explain why things can go wrong (Hollnagel, 2014). Understanding normal work (or ‘work-as-done’) is the basis of the safety II perspective, which views safety as increasing the number of things that go right. So far however, there seems to be little application of this safety II perspective in the rail industry. Research in this thesis addresses this gap, by examining whether understanding normal performance in rail engineering contexts contributes towards identifying how incidents occur, and measures for improving safety, compared to the use of existing methods. A range of different methods were used to address the aims of this thesis. Rail incident reports were analysed to understand sources of human errors in rail contexts. Observations were also conducted of operators carrying out work, to understand the opportunities for human errors associated with rail engineering processes. To understand cognitive demands and strategies associated with normal work, a cognitive task analysis was carried out. FRAM (Functional Resonance Analysis Method) (Hollnagel, 2012) wasalso used to determine how incidents may develop, and whether everyday performance can contribute towards successful and unsuccessful performance. Participants in semi-structured interviews and workshops were asked to identify strengths and limitations of various human reliability assessment methods, and offer opinions on their practical applicability. Benefits of understanding normal work included a greater understanding of how human errors can occur (by identifying cognitive demands that contribute towards the occurrence of different error types), and how cognitive strategies can reduce human errors and contribute towards acceptable performance. It was demonstrated how variabilities and flexibilities in performance can contribute towards successful and productive performance, as well as explain why things can go wrong (supporting Hollnagel, 2014). This is especially important to consider, since human errors were not easily identified from rail incident reports and observations of operators carrying out work. System safety can therefore be improved by increasing things that can go right, rather than just decreasing the things that can go wrong (Hollnagel, 2014). Participants in a workshop, however, identified that FRAM may be time consuming to apply, especially for more complex systems. Further research is recommended for the development of a toolkit, from which both practitioners and researchers can choose from a range of different methods. To further understand factors affecting acceptable performance, it is recommended that further data are collected to determine whether varying levels of cognitive demands affect performance, and whether these influence the implementation of cognitive strategies.

For many reasons planners in the past have failed to realize the full potential of the market system as a powerful practical and intellectual tool to be used in urban transportation planning. At a time when there is increasing evidence that past approaches to the urban transportation problem have not yielded the long term solutions that were expected, it is urgent that all alternative strategies be explored. This study addresses itself to one policy course: control of urban transportation through the deliberate use of the market mechanism. The objective of the pricing of urban transportation would be to promote a more socially desirable pattern of usage of the system through a structuring of the demand characteristics - by mode, route, time of travel, and amount of travel. Pricing may thus be used to make the trip-maker aware of, and accountable for, the social costs he incurs in the form of delays due to congestion, noise, air pollution, and so forth, and his travel behaviour would alter accordingly. Because these so-called externalities are, at present not quantifiable in monetary terms, and because of differences in individual utilities, the use of the pricing mechanism cannot displace the political decision-making, but can supplement it. This study is an evaluation of the tool of pricing control in urban transportation planning. The theoretical relationships and the rationale for use of the price mechanism are discussed, and the technical and administrative problems of implementation of a pricing scheme are evaluated. The potential impacts are examined. The practical application of the tool is explored in the context of a case study of traffic in the Lions' Gate Bridge Corridor in Vancouver. There are several compelling advantages to the use of the pricing system for achieving both short-run and long-run objectives. It is extremely flexible, adaptable, incremental, reversible, and most schemes can be implemented at very low capital cost. It can be a strategy for restraint or containment of traffic, or more generally a strategy for directing the patterns of use of the transportation system. But there are serious unanswered questions concerning the limitations of the tool - specifically the income redistribution effects and the overall effectiveness of the pricing mechanism in an increasingly affluent society. There are potential long-term impacts which will remain speculative until we have working urban simulation models. Although the direct application of pricing would be practicable in Canada in only a limited number of clearly defined situations, an understanding of the theoretical concepts will assist in the formulation of specific objectives which may then be pursued using alternate tools more suited to each set of circumstances. / Applied Science, Faculty of / Community and Regional Planning (SCARP), School of / Graduate

Considerable attention has been devoted in the past to documenting the impact of prepaid group practices and community health centres on inpatient hospital utilization. The thesis develops and applies a methodology designed to allow estimation of the fiscal implications of such evidence. An equation relating average hospital inpatient costs to a number of explanatory variables is specified. The maximum likelihood estimation technique is employed in a time-series/cross-section analysis to determine parameter estimates for that equation over the period 1966-73. The variables are constructed from data deriving from eighty-seven British Columbia public general hospitals. Empirical results indicate the importance of case mix, average length of inpatient stay, rate of case flow and education-related hospital activities in explaining the variance across the eighty-seven hospitals in average cost per separation. The parameter estimates derived in the unit cost analysis are utilized in a comparative static determination of the implications for unit costs of changes in a hospital's case mix. The impact of case-specific case mix changes on unit (per separation) costs is determined, from which analysis case-specific marginal costs are derived. Finally, the marginal case costs are combined with utilization statistics from matched population studies involving community health centres or prepaid group practices. This allows determination of the expenditure implications of the utilization differentials reported in that literature. A subsequent extrapolative and conjectural analysis considers the cost implications of more widespread use of community health centres as a mode of medical care delivery in British Columbia. The conclusions suggest that the fiscal impact on the overall medical care budget in B.C. would be minimal in the absence of corresponding reductions in numbers of hospital beds. A number of other applications of the case cost derivation methodology are suggested. / Arts, Faculty of / Vancouver School of Economics / Graduate

The objective of this diploma thesis is to design a model of long heat pipeline operation control using Matlab software. The model should simply correspond to real heat pipeline system Melnik – Praha. After this, simulate operation control of sets of pumps. The role is to simulate usual and critical modes of operations. After evaluation of results, optimize the conditions for operation control of this system.

Includes bibliographical references (pages 165-169). / Classical Statistical Process Control Charts are essential in Statistical Control exercises and thus constantly obtained attention for quality improvements. However, the establishment of control charts requires large-sample data (say, no less than I 000 data points). On the other hand, we notice that the small-sample based Grey System Theory Approach is well-established and applied in many areas: social, economic, industrial, military and scientific research fields. In this research, the short time trend curve in terms of GM( I, I) model will be merged into Shewhart and CU SUM two-sided version control charts and establish Grey Predictive Shewhart Control chart and Grey Predictive CUSUM control chart. On the other hand the GM(2, I) model is briefly checked its of how accurate it could be as compared to GM( I, 1) model in control charts. Industrial process data collected from TBF Packaging Machine Company in Taiwan was analyzed in terms of these new developments as an illustrative example for grey quality control charts.

Staff scheduling is one of the most important challenges that every healthcare organization faces. Long wait times due to the lack of care providers, high salary costs, rigorous work regulations, decreasing workforce availability, and other similar difficulties make it necessary for healthcare decision-makers to pay special attention to this crucial part of their management activities. Staff scheduling decisions can be very difficult. At inpatient clinics, there is not always a good estimate of the demand for services and patients can be discharged at any given time, consequently affecting staff requirements. Moreover, there are many other unpredictable factors affecting the decision process. For example, various seasonal patterns or possible staff leaves due to sickness, vacations, etc. This research describes a solution approach for staff scheduling problems at inpatient clinics where demand for services and patient discharges are considered to be stochastic. The approach is comprehensive enough to be generalizable to a wide range of different inpatient settings with different staff requirements, patient types, and workplace regulations. We first classify patients into a number of patient groups with known care-provider requirements and then develop a predictive model that captures patients’ flow and arrivals for each patient category in the inpatient clinic. This model provides a prediction of the number of patients of each type on each specific day of the planning horizon. Our predictive modelling methodology is based on a Discrete Time Markov model with the number of patients of different types as the state of the system. The predictive model generates a potentially large set of possible scenarios for the system utilization over the planning horizon. We use Monte Carlo Simulation to generate samples of these scenarios and a well known Stochastic Optimization algorithm, called the Sample Average Approximation (SAA) to find a robust solution for the problem across all possible scenarios. The algorithm is linked with a Mixed-Integer Programming (MIP) model which seeks to find the optimal staff schedule over the planning horizon while ensuring maximum demand coverage and cost efficiency are achieved. To check the validity of the proposed approach, we simulated a number of scenarios for different inpatient clinics and evaluated the model’s performance for each of them.

Samarbete över gränser / Co-operation across the borders