This thesis describes the development of a framework for a systematic approach to risk management in construction projects, whose application in construction practice would lead to changes and improvements in the construction industry. To verify and apply the framework in future construction projects, the author developed the PPRisk computer programme as IT support. Before showing how the framework was developed, there is a survey of what has been written on the subject and a systematic analysis of risk management, risk in construction and process in construction. This led to the conclusion that realising a construction project is a process and that the risk management process should be subordinated to the construction process. A new approach was therefore introduced to managing risks: process-driven risk management. This approach will give all the participants in the project better understanding of the construction process, enable changes in the construction industry, and contribute to improvement of quality and efficiency in construction. An analysis of published plans of work showed that the Construction Process Protocol, developed at the University of Salford under the leadership of Professor R. Cooper, is suitable and appropriate as a construction process in which the framework for process-driven risk management can be placed. Process-driven risk management implies a cyclical risk management process in all the phases through which the construction project passes according to Process Protocol. Key risks are identified in the framework, which are independent of the size, type and purpose of the project being realized. Project related risks should be separately identified for each specific project. Depending on available data, quantitative and qualitative analysis is carried out for the identified risks, their risk probability and risk impact determined, and the corresponding risk exposure calculated. Then the adequate risk response is given for each identified risk, depending on its exposure. As the process unfolds new risks appear in each phase and the risk management process begins a new.

The thesis develops the application of delay time analysis to the area of mathematical modelling of planned maintenance and inspection of industrial systems. Chapter 1 gives an introduction to the history and techniques in use of maintenance modelling and surveys appropriate literature in the field. A section is devoted to papers published on delay time analysis. Chapter 2 introduces and develops mathematical models for modelling the reliability, maintenance and inspection of repairable systems. Chapter 3 gives an account of parameter estimation and model updating techniques in the light of subjective and observational data sets collected over a period of system operation. Chapter 4 addresses a bias in the probability distribution function of delay time when the data available over an operating survey is censored. Parameter estimation methods for this situation are then proposed. Chapter 5 gives an account of a simulation study of the delay time models and verifies the theory and parameter estimation techniques. Chapter 6 reports on research supported by the Science and Engineering Research Council on the application of delay , time analysis to concrete structures. Finally, Chapter 7 collates the conclusion drawn on each chapter and recommends areas for further research.

In the literature on inspection modelling, the failure distribution traditionally plays a fundamental role in model construction in that it is assumed that system failures occur instantly at random time points from new with a known pdf. of time to failure. Numerous models have been built on this basis. However, Professor Christer challenged this traditional idea and proposed the concept of delay time. The idea, which is an essential part of most engineers' experience, assumes that defects do not just appear as failures, but are present for a while before becoming sufficiently obvious to be noticed and declared as failures. The time lapse from when a defect could first be identified at an inspection to consequential failure has been termed the "delay time". It is this idea which can be captured to reveal the nature and scope for preventive maintenance or inspection. It appears that the concept is now being taken up by many other authors. In this thesis, various models for condition monitoring inspection are built on the basis of delay time analysis. Extensions and further developments are made here to enrich the delay-time modelling. Since the distribution of the delay time is important to delay time modelling, a new approach to estimate the delay time distribution is proposed. This technique, which contrasts with the previous subjective data estimation technique, is based upon objective data. Assuming the distribution of the delay time is known, models of condition monitoring inspection are fully discussed for both perfect and imperfect inspections, and for infinite and finite time horizons. Based upon the models for perfect inspection, algorithms are presented to find the optimal solution. Numerical examples are presented in each Chapter to illustrate how models and algorithms work.

This thesis is concerned with modelling inspection policies of facilities which Qraduallv deteriorate in time. The context of inspection policies lends itself readily to probabilistic modelling. Indeed, many of the published theoretical models to be found in the literature adopt a Markov approach, where states are usually 'operating', 'operating but fault present', and 'failed'. However, most of these models fail to discuss the 'fit' of the model to data,a nd virtually no exampleso f actual applications or case-studiesa re to be found. hi a series of recent papers dating from 1984, a robust approach to solve these problems has been introduced and developed as the Delay Time Model (DTM). The central concept for this model is the delay time, h, of a fault which is the time lapse from when a fault could first be noticed until the time when its repair can be delayed no longer because of unacceptable consequences. The bottle neck in delay time modelling is how to estimate the delay time distribution parameters. Two methods for estimating these parameters have been developed. namely the subjective method and the objective method. Markov models have the advantage of an extensive body of theory. 'fliere are, however. difficulties of definition, measurement, and calculation when applying Markov models to real-world situations within a maintenance context. Indeed. this problem has motivated the current research which ainis to explore the two modelling methodologies in cases where comparison is valid, and also to gain an insight as to how robust Markov inspection models can be as decision-aids where Markovian properties are not strictly satisfied. It Nvill be seen that a class of inspection problems could be solved by a serni- Markov model using the delay time concept. In this thesis, a typical senii-i%Ia, rkov inspection model based upon the delay time concept is presented for a complex repairable systein that may fail during the course of its service lifetime and the results are compared. Finally, a case study of the senii-Markov inspection model and the delay time model is discussed.

This thesis is concerned with predicting the transient response performance of an exhaust gas turbocharger under pulsating and non-pulsating flow conditions. Using the measured steady state characteristics of the turbocharger compressor and turbine, theoretical procedures are developed to predict its transient response during rapid variations in the turbine inlet conditions. A computer program has been written for non-pulsating and two other programs for pulsating flow conditions. Each of these programs used a different method of predicting the response. The programs, with their subroutines and the organization of the calculations, and experimental data are presented. To enable the computer predicted results to be compared with experimental results, an experimental program was carried out on a Holset 3LD turbocharger. The layout and the principal features of the experimental test rig, which is designed to operate the turbocharger from a compressed air supply, are described. The rig may be used to simulate engine exhaust conditions. The computer predicted results are compared with the experimental ones obtained from tests, during pulsating and non-pulsating operation of the turbocharger. The experimental results and theoretical predictions are found to compare favourably, and the possible causes of discrepancies are suggested. Suggestions are made for further work.

Stressed skin design has now been developed into an important tool for designing buildings. In developing stressed skin theory, it has been shown that the inherent inplane stiffness of the materials considered is of predominate importance in the distribution of lateral forces within a structure. The materials that have been incorporated in the theory so far are profiled steel and aluminium sheeting. Lately, work on multi-storey buildings has shown the advantage of using infill panels in the vertical plane to control the sway deflection of the building. No account, however, has been taken of the horizontal floors acting as diaphragms. Incorporating the floor into the sway analysis would clearly model the building more realistically. A typical floor construction commonly adopted in steel framed buildings is the composite slab. This consists of trapezoidally profiled steel sheeting fastened to the structure and overlain by concrete. Design formulae are derived for the shear strength and flexibility of the above floor construction and verified by experimental work. In the basic stressed skin concept the shear distortional flexibility of profiled sheeting has been shown to be dependent on the overall dimensions of the diaphragm, the shape of the profile and the fastener arrangement. At present the analysis considers a typical corrugation to lie within a large "field or corrugations" and so edge effects are neglected. A Finite Strip program has been written to analyse these fields of corrugations under the action of a shear flow and to investigate the effect of edge members on the shear flexibility. The large end distortions of the profiled sheeting, that arise as a result of the action of the shear flow on the profile, can cause failure of the sheeting and fasteners in this region. A study has been undertaken to investigate the possible failure modes, as a result of which three modes have been identified, namely, failure of the sheet / purlin fasteners, buckling of the profile web and a sideways collapse of the profile. Numerical expressions are developed for these failures and compared with experimental results.

In recent years, many researchers have proposed different iterative learning controllers, which unfortunately mostly require that the plants under control be regular. Therefore, in order to remove this limitation, various analogue and digital iterative learning controllers are proposed in this thesis. Indeed, it is shown that analogue iterative learning controllers can be designed for plants with any order of irregularity using initial state shifting or initial impulsive action. However, such analogue controllers have to be digitalised for purpose of implementation. In addition, in the synthesis of their control laws, such controllers require some knowledge of the plants' Markov parameters. Ilerefore, new digital iterative learning controllers are proposed. Such digital controllers circumvent the need for detailed mathematical models of the plants in any form. Indeed, the proposed digital iterative learning controllers rely on input/output data in the synthesis of their control laws. It is shown that digital iterative learning controllers can be readily designed for multivariable plants of any order or irregularity using only such input/output data in the form of step-responsem atrices. The learning rates achievable in both the analogue and digital iterative learning control of linear multivariable plants are investigated. It is shown that the irregularity and stability characteristics of the plants under control impose severe constrains on the achievable learning rates. Indeed, it is shown that the learning parameter in the case of digital iterative learning controllers increases as the order of plant irregularity increases. This increase in the learning parameter affects the learning performance and the speed of convergence adversely. This discovery led to the introduction of compensators in the design of digital iterative learning controllers for irregular plants which help to improve the learning performance and convergence by reducing the effective learning parameter. Since such digital iterative learning controllers use stepresponse matrices in the synthesis of their control laws and since the step-response characteristics can be identified in real time, it is shown in this thesis that iterative learning controllers can readily be rendered adaptive in case plant dynamics are initially unknown or time-varying. In order to demonstrate the applicability of these results to the control of robotic manipulators, both analogue and digital iterative learning controllers are designed for a two-link manipulator in both joint and task spaces. Finally, digital iterative learning controllers are designed and practically implemented in the real-time positional control of a dc servo actuator.

This thesis is concerned with investigating and understanding the role and consequence of different modelling options and parameter estimation options for modelling a complex plant. As systems become more complicated and required new technologies and methodologies, more sophisticated maintenance models and control policies are need to solve the maintenance problems. The initial chapter introduces the review of previous work on a single component system and multi-component system. Although in recent years there has been a shift in the maintenance literature from consideration of single items to systems composed of several components, so far only a few papers have tackled the modelling of actual multi-component plant. In the third chapter, delay time concept and analysis technique have been presented. Of particularly importance are parameter estimation methods, namely the objective method and the subjective methods. In the fourth chapter the component PM model and the system PM model for downtimes and costs based upon various PM policies are discussed. The key options within maintenance modelling are to determine regular Minspection periods for the system modelled as a whole, and to determine the periods for the plant as a set of separate component models. An extension to the downtime model is presented for the case when the downtime due to failures within system is not small, and impacts upon the estimate of the number of failures arising over a specified time zone. In the following chapter, we address parameter estimation methods using simulated data, and assess the ability of estimation techniques to capture the true parameter values. Particular attention is paid to the problem arising during the parameter estimating process because of the inadequate recording of PM data and implied correlation between model parameters. Finally, a case study is presented of maintenance modelling of production plant in a local company with view to improving current practice. The model developed is based upon the delay time concept where because of an absence of PM data, using the results of earlier chapters, the process parameters and the delay time distribution were estimated from failure data only using the method of maximum likelihood. The modelling was repeated based upon subjective assessmentosf parameter,a nd considerablec onsistencyw ith the objectively based case obtained. For the plant study, modelling indicated the current PM inspection program was ineffective. A snap-shot approach is then applied to assess other ways of reducing the downtime, and the possibility of improving the PM inspection practice. This leads to readily adapted improvements.

This thesis describes the development of a suite of computer programs designed to evaluate the optimum operating strategy for turbine-generators installed in a proposed tidal power barrage. The computer models are of the single-tide type but have been extended to incorporate detailed models of the turbine performance characteristics and operating constraints. The computer programs have been extensively used for studies of the Severn and Mersey barrage proposals in the UK, for one of the proposed barrage schemes in the Bay of Fundy, Canada and for the now-operating scheme at Annapolis Royal, Canada. One of the most important features of these programs is their ability to simulate, using appropriate characteristics, all the different turbine types suitable for tidal power generation. Results are presented of particular studies showing in each case the conclusions reached.

This thesis investigated Supply Chain Management (SCM), a relatively new area of study in Facilities Management (FM) in the UK, where a research gap was identified by the researcher. This study explored SCM in other industries, relating the benefits derived to FM. It identified that SCM is fundamental to FM, as business performance (which FM supports) is influenced by supply chain performance, creating a link between FM supply chain performance and business performance. Furthermore, competitive advantage and cost savings amongst others were found to be driving forces for SCM in FM, from client and supplier perspectives. This thesis focused on the application of models in SCM in FM. Although a comprehensive examination of available supply chain models was not undertaken, an evaluation of three identified the Integrate to Innovate (i2i) m odel relevant f or application in FM. The action research approach adopted by this thesis enabled the researcher gain a deeper understanding of the applicability of the model, and build on knowledge acquired throughout the period of study. To support this methodology, a philosophical stance between positivism and phenomenology, viewing 'reality as a contextual field of information', was adopted. An explanatory case study approach was employed to undertake a contextual analysis of Gestalten, and understand the real world dynamics of SCM in FM. i2i is a five-level model and three-part framework that evaluates supply chain relationships. Three case studies were undertaken in this thesis, which applied and evaluated the model and framework using a variety of research tools. Each was a learning process for the researcher, adding to the overall outcomes of the research. The thesis identified that the i2i model represented a framework for 'good practice' in SCM in FM. Further development is however required to make it a robust tool, and deliver consistency in its application.