Energy is a resource of fundamental importance and if there is one thing that the world is going to need more in the future, it's energy. Increased energy demand is a major factor for the energy industry to invest in innovative technologies by developing processes and products that deliver improved efficiency and environmental performance. With oil continues to satisfy a major part of the energy needs, it is important for oil companies to invest wisely in Research and Development (R&D) projects. Literature is full of methods that address the problem of R&D portfolio selection. Despite their availability, R&D portfolio selection methods are not used widely. This is due to lacking several issues identified by researchers and practitioners. As a result, R&D portfolio selection is still an important area of concern. This research proposes a multi-attribute decision making methodology for selecting R&D portfolios with a case study of implementation of the methodology in the Saudi oil refining industry. Driven by the research question and some gaps identified in the related literature review, the methodology has been modified and improved. The methodology includes methods and techniques that aim to give insights to decision makers to evaluate individual projects and select the R&D portfolio. The methodology is divided into three stages with different steps in each stage by combining and modifying two well-known multi-attribute decision making methods: the Simple Multi-Attribute Rating Technique (SMART) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The case study describes further methods such as Integer Linear Programming (ILP) and Monte Carlo simulation for generating data to test the validation and operationality of the methodology. It is designed in a step-by-step, easy to apply way and considers the decision making type in a national oil company. It includes the preferences of the decision makers and takes into consideration the multiple, monetary and non- monetary, attributes that ought to be considered to satisfy not only the objectives of the Saudi national company (Aramco), but the strategic goals of the Saudi government as well.

Office Space Allocation (OSA) is the task of efficient usage of spatial resources of an organisation. A common goal in a typical OSA problem is to minimise the wastage of space either by limiting the overuse or underuse of the facilities. The problem also contains a myriad of hard and soft constraints based on the preferences of respective organisations. In this thesis, the OSA variant usually encountered in academic institutions is investigated. Previous research in this area is rather sparse. This thesis provides a definition, extension, and literature review for the problem as well as a new parametrised data instance generator. In this thesis, two main algorithmic approaches for tackling the OSA are proposed: The first one is integer linear programming. Based on the definition of several constraints and some additional variables, two different mathematical models are proposed. These two models are not strictly alternatives to each other. While one of them provides more performance for the types of instances it is applicable, it lacks generality. The other approach provides less performance; however, it is easier to apply this model to different OSA problems. The second algorithmic approach is based on metaheuristics. A three step process in heuristic development is followed. In the first step, general local search techniques (descent methods, threshold acceptance, simulated annealing, great deluge) traverse within the neighbourhood via random relocation and swap moves. The second step of heuristic development aims to investigate large sections of the whole neighbourhood greedily via very fast cost calculation, cost update, and search for best move procedures within an evolutionary local search framework. The final step involves refinements and hybridisation of best performing (in terms of solution quality) mathematical programming and meta-heuristic techniques developed in prior steps. This thesis aims to be one of the pioneering works in the research area of OSA. The major contributions are: the analysis of the problem, a new parametrised data instance generator, mathematical programming models, and meta-heuristic approaches in order to extend the state-of-the art in this area.

Process improvement has been identified as a central topic of operations management, being relevant to the different functional areas and assisting in providing the benefits operations management aims to realise. While extensive research has been conducted on specific process improvement methodologies, high resource requirement of specific process improvement methodologies make them inappropriate for many Small and Medium Sized Enterprises (SMEs). Compared to specific improvement methodologies, organisational learning was identified as an appropriate theoretical perspective from which to analyse process improvement activities within SMEs, leading to the presentation of the following three research questions: How do engineering-oriented SMEs undertake process improvement? What is the applicability of the three models of organisational learning within engineering-oriented SMEs? How does organisational learning contribute to understanding of process improvement within engineering-oriented SMEs? The research questions were addressed through in-depth, interpretive, interview based case studies with 14 Engineering Oriented SMEs. The six exploratory cases studies enabled the identification of specific process improvement practices that related isolated problems or opportunities with organisational level changes. These activities appeared to require management to implement formalised operational processes to ensure changes were captured within operational procedures and subsequently used by operational staff. Management support and culture then appeared to affect the ability of process improvement practices to provide firm level benefits to the case companies. Without directions by management or acceptance by operational staff, efforts directed towards process improvement tended to have limited impact on the benefits companies were able to realise from process improvement. Findings were then analysed from three conceptualisations of organisational learning identified within operations management literature. This provided theoretically underpinned insight to the exploration of process improvement, emphasising the importance of experience, involvement with external parties and the multi-level nature of organisational culture. Following the analysis of the exploratory phase, the findings were confirmed within 6 additional engineering-oriented SMEs (2 were excluded). The confirmatory case companies allowed the further exploration of the relationships between the emergent themes in order for the third research question to be addressed. Organisational learning provided justification for the interaction and bidirectional relationship between process improvement and culture. Organisational learning also provided justification for the important role of management, in relation to interpreting the operating environment and adapting how they provided resources to process improvement. The research thus contributes to operations management theory, by building upon organisational learning theory, in terms of how process improvement is conceptualised, factors affecting the benefits realised from process improvement and the importance of management to provide resources and direction to process improvement activities. Within all the case companies, this involved both providing sufficient resources in terms of training and time to engage in process improvement, but also selecting work that provided firms with sufficient process improvement opportunities. By effectively engaging in process improvement, firms appeared better equipped to compete against larger firms and low cost economies.

This research studies Mass Customization as an operations strategy and model. Opinions differ over whether MC should be a label for a specific business model in which customers select from pre-engineered product options, or whether it should be interpreted as a performance goal that has wider relevance. In this research it is viewed as the latter and a manufacturing enterprise is considered to be a mass customizer if it gives its customers the opportunity to have a product any time they want it, anywhere they want it, any way they want it and in any volume they want it, and at the same time brings the benefits that are associated with mass operations, in particular those of price and quality. In the literature MC is not one operations strategy but a family of sub-strategies and there are several classification schemes, most of which delineate the sub-strategies by the point along the value chain that customization takes place. Other than for one scheme for which correlations between technologies and MC types has been sought by means of a survey, no progress has been made in developing operations configurations models. Through the study of primary and secondary case studies several classification schemes are appraised and a new framework of five fundamental operations Modes is developed. The Modes are the kernel of a theory of MC, with the other elements being: - A model for Mode selection that uses four factors to determine when a Mode is suitable; - Indicative models of the information infrastructures of two Modes that demonstrate the Modes to be different and that they can be a foundation for configurations models; - A set of product customizable attributes that reveals the multifaceted nature of customization and extends the terminology of customization; - The delta Value concept that links the motivation for customizing attributes to differences between customers. A theory of MC is proposed, which postulates: - An MC strategy is relevant when there are differences across customers in how they value the configurations of customizable attributes; - There are five operational sub-strategies of MC; - The choice of sub-strategy for an enterprise is contingent on its organisation and its business environment. One of the five modes, Catalogue MC, is the Mode that is commonly associated with MC. It is the Mode in which all product variants are fully engineered before being ordered. A diverse set of order fulfilment models of relevance to this Mode are reviewed and organised into four types: fulfilment from stock; fulfilment from a single decoupling point; fulfilment from several decoupling points; and fulfilment from a floating decoupling point. The term floating decoupling point is coined to describe systems that can allocate a product to a customer wherever the product lies, whether it be a finished product in stock, a part processed product or a product that does not yet exist but is in the production plan. In the automotive sector this system has been called Virtual-Build-to-Order (VBTO) and in this research the generic characteristics of VBTO systems are described and key concepts developed, in particular the concept of reconfiguration flexibility. Discrete event simulation and Markov models are developed to study the behaviour of the VBTO fulfilment model. The non-dimensional ratio of product variety / pipeline length is identified to be a fundamental indicator of performance. By comparing the VBTO system to a conventional system that can fulfil a customer from stock or by BTO only, the role of pipeline fulfilment is identified and a surprising observation is that it can cause stock levels and average customer waiting time to be higher than in a conventional system. The study examines also how customer differences, in particular their willingness to compromise and their aversion to waiting, affect fulfilment and how fulfilment is dependent on reconfiguration flexibility.

The present thesis designs, implements and evaluates a channel for interaction between office and field users through a collaborative mixed reality system. This channel is aimed to be used for civil engineering purposes and is thus oriented toward the design and construction phases. Its application should contribute to the reduction of the challenges faced by those involved in a civil engineering project dealing with communication, collaboration and mutual understanding. Such challenges can become real problems for multidisciplinary teams of architects, engineers and constructors when working on the same project. In the context of this thesis, outdoor users are equipped with a real-time kinematic global positioning system receiver, a notebook, a head-mounted display, a tilt sensor and a compass. A virtual environment representing components of a civil engineering project is displayed before their eyes. Outdoor users share this collaborative virtual environment with indoor ones. They can talk to and see each other through an avatar. Indoor users can take part from any location where Internet is available. The goal of this thesis is to show that a networked solution of at least two users (In this case, indoor and outdoor users) is an opportunity for outdoor users to perform complex tasks whilst experiencing an immersive augmented reality application. Indoor users interact with outdoor ones when handling and navigating the virtual environment, guiding their counterpart through the scene and making clear common points of understanding. The thesis evaluates how users interact within a prototype system using a formative approach. Users are introduced to the system and motivated to “talk loudly”, thus verbalising what they are experiencing during the tests. All users are video-recorded while performing the exercises and interviewed immediately after. The evaluation reveals that users end up experiencing a system that is too immersive, which ends up narrowing their “attentional spotlight” to the virtual environment and not, as desired, experiencing an augmented reality system. The evaluation also makes clear that the design of the virtual environment is eventually more important for users than the system itself, and it is completely the kind of application that it is being used to and who the users are.

This research considers the role of ergonomics in consumer safety. The aim was to encourage and improve the input of ergonomics, and thus safety, into the design process. The research has resulted in a series of publications targeted specifically at designers and producers of consumer goods, with the aim of encouraging their adoption of ergonomics principles, data and methods. These publications have been produced and distributed to industry by the Department of Trade and Industry (DTI) Consumer Safety Unit: CHILDATA: The Handbook of Child Measurement and Capabilties - Data for Design Safety Designing Safety into Products: Making ergonomics evaluation a part of the design process (presented as an appendix to this thesis). The background to the research is a review of the influences on consumer safety, and the exploration of a role for ergonomics. European consumer legislation states that to be safe a product must meet the expectations of the user, hence the title of this thesis. This user-centred premise indicates the importance of product design and ergonomics in consumer safety, within the context of the other influences on safety such as safe-guarding, mitigation of accidents and education. Theoretically this places ergonomics as a central influence on safety. A review of the existing contributors to safety, such as governance, standards and education was undertaken and again design was found to be central. With the potential contribution of ergonomics to safety demonstrated, evidence of a formal relationship between ergonomics and the design process was sought from the literature. Despite many years of calls for improvements in the input of ergonomics to design, little evidence was found in the ergonomics literature of support or guidance for designers of consumer products on either of these aspects. Two main routes to improving this input of ergonomics to design were identified: the use of ergonomics data and guidelines, and the use of ergonomics evaluation methods. This research focuses on these two routes to product design safety with the hypothesis that these inputs could be improved, eventually allowing better design safety to be realised. The aims of the research were therefore to investigate and improve these inputs. The first stage of the research considered the use of ergonomics data and guidelines in design. The limitations of ergonomics data and the barriers to effective knowledge transfer were identified. Work was undertaken to address these problems, in the first instance specifically for designers of children's products. This resulted in the production of "Childata”, a handbook of ergonomics data on children, and its production and content are described. Four thousand copies of this handbook have been published and distributed free of charge to industry by the DTI. The success of Childata has resulted in sibling publications on adults (now published) and the elderly (in preparation). The next stage of the research was to consider the use of ergonomics evaluation methods by designers. A review of the literature on ergonomics methods and on guidance for their use found that there was a dearth of practical advice for designers. Also, that most guidance on evaluation methods concentrates on usability with very little reference specifically to safety. The feasibility of producing guidance for designers to encourage their use of evaluation was therefore considered. A series of four product safety evaluations were undertaken, presented here as case studies, and these form the major experimental part of the research. The aim of the case studies was to investigate the most useful and common methods for evaluating product safety and to generalise these into guidance for designers ,as well as producing formal reports and recommendations for improvements in the safety of the individual products. The products investigated were swimming pool covers, carbonated drinks bottles, all terrain bicycles and stepladders. The case studies showed however that a diversity of methods were needed to carry out the evaluations, many of which were novel methods or which drew on a mixture of ergonomics, technical and market research expertise T he only commonality found was in the sequence of stages that each evaluation followed, namely the identification of the products' users and hazards, the setting of performance criteria and selection of measurement variables, and the subsequent choice of methods. T he initial concept behind the fundamental research to producing prescriptive advice on methods was therefore rejected. Instead a framework for a generic evaluation process was developed, based on the findings from the case studies and with reference to the literature. This framework formed the basis of a guidance document for designers: ‘Designing Safety Into Products'. This was also published and distributed to industry by the DTI. The publication establishes and encourages a generic evaluation process, but also concentrates on embedding ergonomics principles into the design process by exploring the relationship between evaluation and safety and stressing the need to move past the use of ergonomics data, as well as providing methodological guidance. The research reported in this thesis has shown that the problems with the transfer of knowledge and methods from the ergonomics discipline are long standing. The reasons for this are discussed and recommendations are made to improve the link between design and ergonomics, including furthering this pragmatic approach to empowering designers by the production of similar design tools. The research programme has been a pragmatic approach to improving ergonomics and safety in design: improving the accessibility of ergonomics data for designers and promoting ergonomics evaluation methods during the product development process. The publications that have resulted from the research represent pragmatic steps which it is hoped may make some contribution to the realisation of safety.

This dissertation contributes to the empirical literature on the effects of international technology transfer on firms' productivity and employment in developing and transition countries. It combines three empirical essays which provide evidence on how participation in international activities affects firms' productivity, how it interacts with firms' absorptive capacity and how it affects firms' demand for skilled labour in 26 transition countries in Europe and Central Asia (ECA) region. The first study investigates whether foreign ownership, supplying multinationals (MNEs) located in the same country, foreign direct investment (FDI) horizontal spillovers, exporting and importing are conduits of international technology transfer and their relative importance for firms in 26 transition economies in ECA region using Business Enterprise and Environment Performance Survey (BEEPS) 2002- 2005. It contributes to the literature by analyzing the impact of all main channels of international technology transfer simultaneously and by using a firm specific measure for supply linkages with MNEs, unlike previous studies that used industry level measures. The main results suggest that foreign ownership, supplying MNEs, exporting and importing are robustly associated with higher firm productivity and we cannot reject the hypothesis that these channels are equally important. The second study examines whether international technology transfer through foreign ownership, supplying MNEs, exporting and importing depends on firm and country absorptive capacity in 26 transition economies in ECA region using the BEEPS 2002 and 2005 waves. The main contributions of this paper are that it uses firm specific measures of access to foreign technology and measures of absorptive capacity (workforce education, personnel training and R&D activities) which are closely related to the concept of absorptive capacity and less prone to measurement errors than productivity gap measures used in previous studies. Our results suggest that access to foreign technology and absorptive capacity are associated with higher productivity, but, contrary to our hypothesis, there is no evidence of an interaction effect between absorptive capacity and access to foreign technology. The third study investigates how participation in international activities affects firms' demand for skilled labour and the ways in which firms respond to changes in demand for skilled labour in 26 transition economies in ECA during the period 2002-2005 using BEEPS 2002 and 2005 waves. It contributes to the literature by studying different ways in which firms respond to changes in the demand for skilled labour (hiring employees from outside the firm or training existing employees) and by studying whether there is a causal relationship between participation in international activities and demand for skilled labour. Our results suggest that firms engaged in international activities have a better educated labour force and are more likely to train their employees than domestic firms. However, this happens because firms with better skilled workforces and with formal training programmes select into participating in international activities, and not because these firms upgrade the skills of their workforces after starting to participate in international activities.

The present study was undertaken to investigate issues concerned with the endurance to muscular loads created by the holding of static postures, without the presence of any other form of muscular effort. Its main aim was to explore the possibilities for the development of models which are expected to account for the capacity to endure such kind of exertion. Upright standing postures, with both arms abducted, were held by young male and female subjects (age 18-24 yr.) for as long as they could, until sensations of physical discomfort, rated on a scale with marks between 0 and 10 (Borg, 1982), became unbearable and forced them to abandon the posture. The study was constituted by two main experimental stages. In the first one, a posture as described above, with arms abducted at 60°, was used to submit to the test a model developed in 1985 by N. P. Milner (Milner's model). Although this model was originally proposed as a means to predict the remaining proportion of the maximum endurance (or 'recovery') left to the subject after a single sequence of work and rest, where work consisted of the holding of a stooped posture, its author affirmed it could be applied to any posture. The results of the testing, performed on six female subjects, demonstrated that Milner's model cannot predict with reasonable accuracy the 'recovery' for the upright standing posture with abduction of both arms. Apparently, the assumptions made by Milner concerning the relationships between the endurance capacity and the length of work and rest in a stooped posture did not apply to the test posture. The second experimental stage had three aims. The first was to test the repeatability of the endurance to standing postures with abduction of both arms. The maximum holding time for postures with arms abducted at 30°, 60° and 90° was measured on three occasions on a sample of five male and five female subjects. The maximum holding time for each of the three postures exhibited a wide variability between subjects, but when compared between the repeated measurements, the average value for the whole sample did not exhibit a significant difference. Also, male subjects had, on average, longer holding times than females, but there was a substantial overlap of the individual values. The second aim was to investigate the pattern of growth of the discomfort ratings over the length of the maximum holding time. This was found to be of a very strong linear nature, evident in all three postures studied and very similar for men and women. The strength and consistency of this relationship suggest that it may be used as a model to predict either the endurance capacity in function of the rate of growth of discomfort ratings, or the degree of discomfort that a certain length of holding will provoke. The third aim was to establish whether pure postural loads will provoke changes in the myoelectric activity which indicate the presence of heavy localised muscular fatigue. Mean power frequency (MPF) and RMS amplitude of the EMG signal were monitored throughout the 90 trials of posture holding. Significant changes were evident, with MPF decreasing and RMS amplitude increasing in most of the trials. This means that the posture, even at the lowest angle did provoke muscular fatigue. Another finding, rarely documented, was the presence of electromyographic changes that went in the reversed direction, i. e., MPF increased whilst RMS amplitude decreased. Finally, no well-defined pattern could be established for the time course of those changes or for their relationship with the discomfort ratings.

This study explores the usage of linear programming (LP) as a tool to optimise the parameters of time series forecasting models. LP is the most well-known tool in the field of operational research and it has been used for a wide range of optimisation problems. Nonetheless, there are very few applications in forecasting and all of them are limited to causal modelling. The rationale behind this study is that time series forecasting problems can be treated as optimisation problems, where the objective is to minimise the forecasting error. The research topic is very interesting from a theoretical and mathematical prospective. LP is a very strong tool but simple to use; hence, an LP-based approach will give to forecasters the opportunity to do accurate forecasts quickly and easily. In addition, the flexibility of LP can help analysts to deal with situations that other methods cannot deal with. The study consists of five parts where the parameters of forecasting models are estimated by using LP to minimise one or more accuracy (error) indices (sum of absolute deviations – SAD, sum of absolute percentage errors – SAPE, maximum absolute deviation – MaxAD, absolute differences between deviations – ADBD and absolute differences between percentage deviations – ADBPD). In order to test the accuracy of the approaches two samples of series from the M3 competition are used and the results are compared with traditional techniques that are found in the literature. In the first part simple LP is used to estimate the parameters of autoregressive based forecasting models by minimising one error index and they are compared with the method of the ordinary least squares (OLS minimises the sum of squared errors, SSE). The experiments show that the decision maker has to choose the best optimisation objective according to the characteristic of the series. In the second part, goal programming (GP) formulations are applied to similar models by minimising a combination of two accuracy indices. The experiments show that goal programming improves the performance of the single objective approaches. In the third part, several constraints to the initial simple LP and GP formulations are added to improve their performance on series with high randomness and their accuracy is compared with techniques that perform well on these series. The additional constraints improve the results and outperform all the other techniques. In the fourth part, simple LP and GP are used to combine forecasts. Eight simple individual techniques are combined and LP is compared with five traditional combination methods. The LP combinations outperform the other methods according to several performance indices. Finally, LP is used to estimate the parameters of autoregressive based models with optimisation objectives to minimise forecasting cost and it is compared them with the OLS. The experiments show that LP approaches perform better in terms of cost. The research shows that LP is a very useful tool that can be used to make accurate time series forecasts, which can outperform the traditional approaches that are found in forecasting literature and in practise.

Manufacturing companies must invest in new technologies and processes to succeed in a rapidly changing global environment. Managers have the difficulty of justifying capital investment in adopting new, state-of-the-art technology. Technology investment accounts for a large part of capital spending and is a key form of improving competitive advantage. Typical approaches focus on the expected return of investment and financial reward gained from the implementation of such equipment. With an increasingly dynamic market environment and global economic model, forecasting of financial payback can be argued to become increasingly less accurate. Subsequently, less quantifiable factors are becoming increasingly important. For example, the alignment of a technology with an organisations objective to fulfil future potential and gain competitive advantage is becoming as crucial as economic evaluation. In addition, the impact on human operators and skill level required must be considered. This research was motivated by the lack of decision methodologies that understand why a technology is more successful within an environment rather than re-examining the underlying performance attributes of a technology. The aim is to create a common approach where both experts and non-experts can use historical decision information to support the evaluation and selection of an optimal manufacturing technology. This form of approach is based on the logic in which a decision maker would irrationally recall previous decisions to identify relationships with new problem cases. The work investigates data mining and machine learning techniques to discover the underlying influences to improve technology selection under a set of dynamic factors. The approach initially discovers the practices to which an expert would conduct the selection of a manufacturing technology within industry. A defined understanding of the problem and techniques was subsequently concluded. This led to an understanding of the structure by which historical decision information is recalled by an expert to support new selection problems. The key attributes in the representation of a case were apparent and a form of characterising tangible and intangible variables was justified. This led to the development of a novel, experience-based manufacturing technology selection framework using fuzzy-decision-trees. The methodology is an iterative approach of learning from previously implemented technology cases. Rules and underlying knowledge of the relationships in past cases predicts the outcome of new decision problems. The link of information from a multitude of historical cases may identify those technologies with technical characteristics that perform optimally for projects with unique requirements. This also indicates the likeliness of technologies performing successfully based on the project requirements. Historical decision cases are represented through original project objectives, technical performance attributes of the chosen technology and judged project performance. The framework was shown to provide a comprehensive foundation for decision support that reduces the uncertainty and subjective influence within the selection process. The model was developed with industrial guidance to represent the actions of a manufacturing expert. The performance of the tool was measured by industrial experts. The approach was found to represent well the decision logic of a human expert based on their developed experience through cases. The application to an industrial decision case study demonstrated encouraging results and use by decision makers feasible. The model reduces the subjectivity in the process by using case information that is formed from multiple experts of a prior decision case. The model is applied in a shorter time period than existing practices and the ranking of potential solutions is well aligned to the understanding of a decision maker. To summarise, this research highlights the importance of focusing on less quantifiable factors and the performance of a technology to a specific problem/environment. The arrangement of case information thus represents the experience an expert would acquire and recall as part of the decision process.