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Failure of pipes in water distribution systems is a common occurrence especially in large cities. The failure of a pipe results in: loss of water; property damage; interruption of service; decreased system performance; and the financial cost of restoring the failed pipe. The cost of replacement and rehabilitation in the United States is estimated at 23 plus billion dollars. It is virtually impossible to replace all vulnerable pipes at the same time. As a result, there is a need for methods that can help in progressive system rehabilitation and replacement subject to budgetary constraints. If delaying is considered a good strategy due to the time value of money then, the timing of preventive maintenance becomes a crucial element for system maintenance and operation. The central under pinning element in the decision process for scheduling preventive maintenance is the deteriorating nature of a pipe under a given surrounding. By planning to replace pipes before they fail, proper planning can be put in place for securing of finances and labor force needed to rehabilitate the pipes. With this approach, service interruptions are minimized as the loss of service time is limited to the time used in replacing the pipe. In this research, a mechanistic model for assessing the stage of deterioration of an underground pipe is developed. The developed model consists of three sub-models namely, the Pipe Load Model (PLM), the Pipe Deterioration Model (PDM), and the Pipe Break Model (PBM). The PLM simulates the loads and stresses exerted on a buried water main. These loads include the earth load, traffic load, internal pressure, expansive soil loads, thermal, and frost loads. The PDM simulates the deterioration of the pipe due to corrosion resulting from the physical characteristics of the pipe environment. The pipe deterioration effect is modeled in two stages. First, the thinning of the pipe wall is modeled using a corrosion model. Second, the localized pit growth is used to determine the residual strength of the pipe based on the fracture toughness and the initial design strength of the pipe. The PBM assesses the vulnerability of a pipe at any time in terms of a critical safety factor. The safety factor is defined as the ratio of residual strength to applied stress. For a conservative estimate the multiplier effect due to thermal and frost loads are considered. For a chosen analysis period, say 50 years, the pipes with safety factors less than the critical safety factor are selected and ordered by their rank. Aided by the prioritized list of failure prone pipes, utilities can organize a replacement schedule that minimizes cost over time. Additionally a physically based regression model for determining the optimal replacement time of pipe is also presented. A methodology for assessing the consequences of accelerated and delayed replacement is also provided. The methodologies developed in this dissertation will enable utilities to formulate future budgetary needs compatible with the intended level of service. An application of the model and results are included in the dissertation. / Ph. D.

TEAMDEC is a Group Decision Support System (GDSS). The development of a GDSS is supported by a broad spectrum of theories and techniques. Two major aspects of GDSS development were considered in TEAMDEC design: HCI and decision-making assistance. These two aspects interact to promote an interactive group decision support system with high quality. Decision guidance using a script-based knowledge representation improves the GDSS's efficiency, effectiveness, and flexibility. The traditional script, however, is relatively inflexible. The proposed application, TEAMDEC, provides a set of solutions to support customization in a script system to enhance the decision guidance utilization. The user interface design plays an important role in the overall system design. Two software development models (lifecycle model and V-model with backtracking) are adopted for TEAMDEC development. The user interface design of TEAMDEC is considered from three perspectives: functional, aesthetic, and structural. Quality is emphasized in the development of the interactive system. It can be measured from two perspectives: those of the user and the designer. The quality measures of TEAMDEC are categorized into external properties and internal properties, corresponding to the two perspectives. / Master of Science

Informed decision making is part of any successful organization. Decision support systems help organizations to make more educated decisions by assisting decision makers in consolidating and analyzing information. Successfully introducing decision support systems is very challenging and risky because many factors need to be taken into account. In this thesis, structured and semi-structured interviews are carried out with employees at a Nordic construction company to discuss critical success factors in connection to introduction of decision support systems. The identified critical success factors are grouped into the following categories: organizational, project, technical, information quality, system quality, service quality and net benefits.

In the automotive industry, assembly lines are used to produce vehicles. These assembly lines improve throughput, and need to be carefully planned. Planning, or balancing, an assembly line constitutes identifying precedence relationships between tasks in the assembly line, and assigning tasks to stations to fit some criteria. This procedure is costly to do by hand, and is well-suited for some level of automation. The problem of balancing assembly lines has been researched since the 1950’s, but modern assembly lines largely rely on engineers to balance the line by hand. This thesis proposes that the work flow of engineers planning the assembly line would be improved by a group decision support system. This group decision support system could supply engineers with proposals for assembly lines, which the engineers can choose to modify further, either by hand or with the decision support system. The group decision support system is realized with a distributed system, consisting of a front-end, a back-end, an application programming interface to balance assembly lines, and two databases. The front-end is a website, where the users can create problems with a precedence graph. The back-end allows data to be permanently stored in the two databases, and allows communication with the application programming interface. The contribution of this thesis is a proof of concept of a group decision support system that can solve two basic types of assembly line balancing problems, SALBP-1 and SALBP-2. During development it was found that the developed system was generic enough to support different types of tasks, such as planning cooking. Further development is needed to use the system in an industrial setting, as real assembly lines need more complex models than the current version support.

Internal audit departments strive to control risk within an organization. To do this they choose specific audit areas to include in an audit plan. In order to select areas, they usually focus on those areas with the highest risk. Even though high risk areas are considered, there are various other restrictions such as resource constraints (in terms of funds, manpower and hours) that must also be considered. In some cases, management might also have special requirements. Traditionally this area selection process is conducted using manual processes and requires significant decision maker experience. This makes it difficult to take all possibilities into consideration while also catering for all resource constraints and special management requirements. In this study, mathematical techniques used in capital budgeting problems are explored to solve the IT audit area selection problem. A DSS is developed which implements some of these mathematical techniques such as a linear programming model, greedy heuristic, improved greedy heuristic and evolutionary heuristic. The DSS also implements extensions to the standard capital budgeting model to make provision for special management requirements. The performance of the mathematical techniques in the DSS is tested by applying different decision rules to each of the techniques and comparing those results. The DSS, empirical experiments and results are also presented in this research study. Results have shown that in most cases a binary 0-1 model outperformed the other techniques. Internal audit management should therefore consider this model to assist with the construction of an IT internal audit plan. / MSc (Computer Science), North-West University, Potchefstroom Campus, 2015

Internal audit departments strive to control risk within an organization. To do this they choose specific audit areas to include in an audit plan. In order to select areas, they usually focus on those areas with the highest risk. Even though high risk areas are considered, there are various other restrictions such as resource constraints (in terms of funds, manpower and hours) that must also be considered. In some cases, management might also have special requirements. Traditionally this area selection process is conducted using manual processes and requires significant decision maker experience. This makes it difficult to take all possibilities into consideration while also catering for all resource constraints and special management requirements. In this study, mathematical techniques used in capital budgeting problems are explored to solve the IT audit area selection problem. A DSS is developed which implements some of these mathematical techniques such as a linear programming model, greedy heuristic, improved greedy heuristic and evolutionary heuristic. The DSS also implements extensions to the standard capital budgeting model to make provision for special management requirements. The performance of the mathematical techniques in the DSS is tested by applying different decision rules to each of the techniques and comparing those results. The DSS, empirical experiments and results are also presented in this research study. Results have shown that in most cases a binary 0-1 model outperformed the other techniques. Internal audit management should therefore consider this model to assist with the construction of an IT internal audit plan. / MSc (Computer Science), North-West University, Potchefstroom Campus, 2015

This thesis reports the research efforts conducted in order to develop the Dynamic Response Recovery Tool. The DRRT was developed as a decision support tool under a holistic approach considering both emergency management research and transportation studies. The proposed system was assessed by a series of case studies in order to identify its efficiency and suitability for roading organisations. Knowledge developed from two novel research approaches are comprehensively described throughout the thesis. Initially, we report on the observation of three emergency exercises and two real events in New Zealand. This set of activities indicated the complex and dynamic environment in which emergency management takes place as well as organisational settings and management structures implemented to better respond and recover from disasters events. Additionally, a secondary approach was designed to overcome limitations identified in the observation method. In this context, a game-based scenario simulation was developed and conducted with twelve participants. With a focus in resource deployment decisions during emergencies, the game simulated an earthquake scenario in which participants had to allocate physical resources to fix damage created in a road network. Simulations indicated that Naturalistic Decision-making processes were used to respond to the scenario. Thus, resource allocation followed planning priorities defined previously the simulation, which further considered individual experiences and knowledge. Taking advantage from the findings achieved and knowledge developed by the observations and game simulations, the DRRT was designed using the conceptual background identified in the literature review. The DRRT was conceptualised as a logistics sub-system as part of the broad field of Disaster Management. In particular, the DRRT was geared towards supporting decision-making by providing procedural recommendations and identifying optimum physical deployment strategies. In order to assess the proposed system, an Information Technology application was built according to the DRRT’s specifications. A series of eleven individual and three group simulations was performed in order to assess the DRRT. Data collected through the application indicated that the DRRT enhanced decision-making during extreme events. In specific, case study participants using the system at greater levels achieved better decision-making accuracy than those disregarding completely or partially the system. Case studies also indicated that emergency management knowledge was represented by the application and its logistics model provided participants with vital information to optimise resource allocation.

Project risk management is a crucial activity in project management. Nowadays, projects are facing a growing complexity and are thus exposed to numerous and interdependent risks. However, existing classical methods have limitations for modeling the real complexity of project risks. For example, some phenomena like chain reactions and loops are not properly taken into account. This Ph.D. thesis aims at analyzing propagation behavior in the project risk network through modelling risks and risk interactions. An integrated framework of decision support system is presented with a series of proposed methods. The construction of the project risk network requires the involvement of the project manager and the team of experts using the Design Structure Matrix (DSM) method. Simulation techniques are used and several network theory-based methods are developed for analyzing and prioritizing project risks, with respect to their role and importance in the risk network in terms of various indicators. The proposed approach serves as a powerful complement to classical project risk analysis. These novel analyses provide project managers with improved insights on risks and risk interactions under complexity and help them to design more effective response actions. Considering resource constraints, a greedy algorithm and a genetic algorithm are developed to optimize the risk response plan and the allocation of budget reserves dedicated to the risk management. Two examples of application, 1) to a real musical staging project in the entertainment industry and 2) to a real urban transportation system implementation project, are presented to illustrate the utility of the proposed decision support system.

Land is a finite natural resource that is increasingly getting exhausted as a result of land contamination. Land is made up of soil and groundwater, both of which have many functions for which we depend on, including provision of food and water, supporting shelter, natural flood defence, carbon sequestration, etc. Contaminants in land also pose a number of threats to public health and the environment; other natural resources; and have detrimental effects on property such as buildings, crops and livestock. The most effective method of dealing with these contaminants is to cleanup and return the sites to beneficial use. The cleanup process involves making a choice from amongst competing remediation technologies, where the wrong choice may have disastrous economic, environmental and/or social impacts. Contaminated land management is therefore much broader than the selection and implementation of remedial solutions, and requires extensive data collection and analysis at huge costs and effort. The need for decision support in contaminated land management decision-making has long been widely recognised, and in recent years a large number of Decision Support Systems (DSS) have been developed. This thesis presents the development of a Web-based knowledge-based DSS as an integrated management framework for the risk assessment of human health from, and sustainable management of, contaminated land. The developed DSS is based on the current UK contaminated land regime, published guidelines and technical reports from the UK Environment Agency (EA) and Department for Environment, Food and Rural Affairs (DEFRA) and other Government agencies and departments. The decision-making process of the developed DSS comprises of key stages in the risk assessment and management of contaminated land: (i) preliminary qualitative risk assessment; (ii) generic quantitative risk assessment; and (iii) options appraisal of remediation technologies and remediation design. The developed DSS requires site specific details and measured contaminant concentrations from site samples as input and produces a site specific report as output. The DSS output is intended to be used as information to support with contaminated land management decision-making.