A composite framework for the strategic alignment of information systems development

Information systems are corporate resources, therefore information systems development must be aligned with corporate strategy. This thesis proposes that effective strategic alignment of information systems requires information systems development, information systems planning and strategic management to be united. Literature in these areas is examined, breaching the academic boundaries which separate these areas, to contribute a synthesised approach to the strategic alignment of information systems development. Previous work in information systems planning has extended information systems development techniques, such as data modelling, into strategic planning activities, neglecting techniques of strategic management. Examination of strategic management in this thesis, identifies parallel trends in strategic management and information systems development; the premises of the learning school of strategic management are similar to those of soft systems approaches to information systems development. It is therefore proposed that strategic management can be supported by a soft systems approach. Strategic management tools and techniques frame individual views of a strategic situation; soft systems approaches can integrate these diverse views to explore the internal and external environments of an organisation. The information derived from strategic analysis justifies the need for an information system and provides a starting point for information systems development. This is demonstrated by a composite framework which enables each information system to be justified according to its direct contribution to corporate strategy. The proposed framework was developed through action research conducted in a number of organisations of varying types. This suggests that the framework can be widely used to support the strategic alignment of information systems development, thereby contributing to organisational success.

The evaluation of information systems in the organisational context of the National Health Service. Available in 2 volumes.

This thesis describes a project which has investigated the evaluation of information systems. The work took place in, and is related to, a specific organisational context, that of the National Health Service (NHS). It aims to increase understanding of the evaluation which takes place in the service and the way in which this is affected by the NHS environment. It also investigates the issues which surround some important types of evaluation and their use in this context. The first stage of the project was a postal survey in which respondents were asked to describe the evaluation which took place in their authorities and to give their opinions about it. This was used to give an overview of the practice of IS evaluation in the NHS and to identify its uses and the problems experienced. Three important types of evaluation were then examined in more detail by means of action research studies. One of these dealt with the selection and purchase of a large hospital information system. The study took the form of an evaluation of the procurement process, and examined the methods used and the influence of organisational factors. The other studies are concerned with post-implementation evaluation, and examine the choice of an evaluation approach as well as its application. One was an evaluation of a community health system which had been operational for some time but was of doubtful value, and suffered from a number of problems. The situation was explored by means of a study of the costs and benefits of the system. The remaining study was the initial review of a system which was used in the administration of a Breast Screening Service. The service itself was also newly operational and the relationship between the service and the system was of interest.

A Generic model for the design and analysis of production systems

This dissertation studies the process of operations systems design within the context of the manufacturing organization. Using the DRAMA (Design Routine for Adopting Modular Assembly) model as developed by a team from the IDOM Research Unit at Aston University as a starting point, the research employed empirically based fieldwork and a survey to investigate the process of production systems design and implementation within four UK manufacturing industries: electronics assembly, electrical engineering, mechanical engineering and carpet manufacturing. The intention was to validate the basic DRAMA model as a framework for research enquiry within the electronics industry, where the initial IDOM work was conducted, and then to test its generic applicability, further developing the model where appropriate, within the other industries selected. The thesis contains a review of production systems design theory and practice prior to presenting thirteen industrial case studies of production systems design from the four industry sectors. The results and analysis of the postal survey into production systems design are then presented. The strategic decisions of manufacturing and their relationship to production systems design, and the detailed process of production systems design and operation are then discussed. These analyses are used to develop the generic model of production systems design entitled DRAMA II (Decision Rules for Analysing Manufacturing Activities). The model contains three main constituent parts: the basic DRAMA model, the extended DRAMA II model showing the imperatives and relationships within the design process, and a benchmark generic approach for the design and analysis of each component in the design process. DRAMA II is primarily intended for use by researchers as an analytical framework of enquiry, but is also seen as having application for manufacturing practitioners.

The use of expert systems for decision making in organizations

The research described in this thesis investigates three issues related to the use of expert systems for decision making in organizations. These are the effectiveness of ESs when used in different roles, to replace a human decision maker or to advise a human decision maker, the users' behaviourand opinions towards using an expertadvisory system and, the possibility of organization-wide deployment of expert systems and the role of an ES in different organizational levels. The research was based on the development of expert systems within a business game environment, a simulation of a manufacturing company. This was chosen to give more control over the `experiments' than would be possible in a real organization. An expert system (EXGAME) was developed based on a structure derived from Anthony's three levels of decision making to manage the simulated company in the business game itself with little user intervention. On the basis of EXGAME, an expert advisory system (ADGAME) was built to help game players to make better decisions in managing the game company. EXGAME and ADGAME are thus two expert systems in the same domain performing different roles; it was found that ADGAME had, in places, to be different from EXGAME, not simply an extension of it. EXGAME was tested several times against human rivals and was evaluated by measuring its performance. ADGAME was also tested by different users and was assessed by measuring the users' performance and analysing their opinions towards it as a helpful decision making aid. The results showed that an expert system was able to replace a human at the operational level, but had difficulty at the strategic level. It also showed the success of the organization-wide deployment of expert systems in this simulated company.

Aspects of the design and control of manufacturing systems subject to demand uncertainty

The recent explosive growth in advanced manufacturing technology (AMT) and continued development of sophisticated information technologies (IT) is expected to have a profound effect on the way we design and operate manufacturing businesses. Furthermore, the escalating capital requirements associated with these developments have significantly increased the level of risk associated with initial design, ongoing development and operation. This dissertation has examined the integration of two key sub-elements of the Computer Integrated Manufacturing (CIM) system, namely the manufacturing facility and the production control system. This research has concentrated on the interactions between production control (MRP) and an AMT based production facility. The disappointing performance of such systems has been discussed in the context of a number of potential technological and performance incompatibilities between these two elements. It was argued that the design and selection of operating policies for both is the key to successful integration. Furthermore, policy decisions are shown to play an important role in matching the performance of the total system to the demands of the marketplace. It is demonstrated that a holistic approach to policy design must be adopted if successful integration is to be achieved. It is shown that the complexity of the issues resulting from such an approach required the formulation of a structured design methodology. Such a methodology was subsequently developed and discussed. This combined a first principles approach to the behaviour of system elements with the specification of a detailed holistic model for use in the policy design environment. The methodology aimed to make full use of the `low inertia' characteristics of AMT, whilst adopting a JIT configuration of MRP and re-coupling the total system to the market demands. This dissertation discussed the application of the methodology to an industrial case study and the subsequent design of operational policies. Consequently a novel approach to production control resulted. A central feature of which was a move toward reduced manual intervention in the MRP processing and scheduling logic with increased human involvement and motivation in the management of work-flow on the shopfloor. Experimental results indicated that significant performance advantages would result from the adoption of the recommended policy set.

Neural network enhanced self tuning adaptive control application for non-linear control of dynamic systems

The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

Evaluation and measurement of multiprocessor systems with shared memory

This study is concerned with several proposals concerning multiprocessor systems and with the various possible methods of evaluating such proposals. After a discussion of the advantages and disadvantages of several performance evaluation tools, the author decides that simulation is the only tool powerful enough to develop a model which would be of practical use, in the design, comparison and extension of systems. The main aims of the simulation package developed as part of this study are cost effectiveness, ease of use and generality. The methodology on which the simulation package is based is described in detail. The fundamental principles are that model design should reflect actual systems design, that measuring procedures should be carried out alongside design that models should be well documented and easily adaptable and that models should be dynamic. The simulation package itself is modular, and in this way reflects current design trends. This approach also aids documentation and ensures that the model is easily adaptable. It contains a skeleton structure and a library of segments which can be added to or directly swapped with segments of the skeleton structure, to form a model which fits a user's requirements. The study also contains the results of some experimental work carried out using the model, the first part of which tests• the model's capabilities by simulating a large operating system, the ICL George 3 system; the second part deals with general questions and some of the many proposals concerning multiprocessor systems.

The design of a support department simulator for use in the design of manufacturing systems

Manufacturing firms are driven by competitive pressures to continually improve the effectiveness and efficiency of their organisations. For this reason, manufacturing engineers often implement changes to existing processes, or design new production facilities, with the expectation of making further gains in manufacturing system performance. This thesis relates to how the likely outcome of this type of decision should be predicted prior to its implementation. The thesis argues that since manufacturing systems must also interact with many other parts of an organisation, the expected performance improvements can often be significantly hampered by constraints that arise elsewhere in the business. As a result, decision-makers should attempt to predict just how well a proposed design will perform when these other factors, or 'support departments', are taken into consideration. However, the thesis also demonstrates that, in practice, where quantitative analysis is used to evaluate design decisions, the analysis model invariably ignores the potential impact of support functions on a system's overall performance. A more comprehensive modelling approach is therefore required. A study of how various business functions interact establishes that to properly represent the kind of delays that give rise to support department constraints, a model should actually portray the dynamic and stochastic behaviour of entities in both the manufacturing and non-manufacturing aspects of a business. This implies that computer simulation be used to model design decisions but current simulation software does not provide a sufficient range of functionality to enable the behaviour of all of these entities to be represented in this way. The main objective of the research has therefore been the development of a new simulator that will overcome limitations of existing software and so enable decision-makers to conduct a more holistic evaluation of design decisions. It is argued that the application of object-oriented techniques offers a potentially better way of fulfilling both the functional and ease-of-use issues relating to development of the new simulator. An object-oriented analysis and design of the system, called WBS/Office, are therefore presented that extends to modelling a firm's administrative and other support activities in the context of the manufacturing system design process. A particularly novel feature of the design is the ability for decision-makers to model how a firm's specific information and document processing requirements might hamper shop-floor performance. The simulator is primarily intended for modelling make-to-order batch manufacturing systems and the thesis presents example models created using a working version of WBS/Office that demonstrate the feasibility of using the system to analyse manufacturing system designs in this way.

The application of expert systems techniques in the design of durable concrete

This thesis describes work done exploring the application of expert system techniques to the domain of designing durable concrete. The nature of concrete durability design is described and some problems from the domain are discussed. Some related work on expert systems in concrete durability are described. Various implementation languages are considered - PROLOG and OPS5, and rejected in favour of a shell - CRYSTAL3 (later CRYSTAL4). Criteria for useful expert system shells in the domain are discussed. CRYSTAL4 is evaluated in the light of these criteria. Modules in various sub-domains (mix-design, sulphate attack, steel-corrosion and alkali aggregate reaction) are developed and organised under a BLACKBOARD system (called DEX). Extensions to the CRYSTAL4 modules are considered for different knowledge representations. These include LOTUS123 spreadsheets implementing models incorporating some of the mathematical knowledge in the domain. Design databases are used to represent tabular design knowledge. Hypertext representations of the original building standards texts are proposed as a tool for providing a well structured and extensive justification/help facility. A standardised approach to module development is proposed using hypertext development as a structured basis for expert systems development. Some areas of deficient domain knowledge are highlighted particularly in the use of data from mathematical models and in gaps and inconsistencies in the original knowledge source Digests.

An approach to the development of expert systems within production planning and control

The thesis presents an account of an attempt to utilize expert systems within the domain of production planning and control. The use of expert systems was proposed due to the problematical nature of a particular function within British Steel Strip Products' Operations Department: the function of Order Allocation, allocating customer orders to a production week and site. Approaches to tackling problems within production planning and control are reviewed, as are the general capabilities of expert systems. The conclusions drawn are that the domain of production planning and control contains both `soft' and `hard' problems, and that while expert systems appear to be a useful technology for this domain, this usefulness has by no means yet been demonstrated. Also, it is argued that the main stream methodology for developing expert systems is unsuited for the domain. A problem-driven approach is developed and used to tackle the Order Allocation function. The resulting system, UAAMS, contained two expert components. One of these, the scheduling procedure was not fully implemented due to inadequate software. The second expert component, the product routing procedure, was untroubled by such difficulties, though it was unusable on its own; thus a second system was developed. This system, MICRO-X10, duplicated the function of X10, a complex database query routine used daily by Order Allocation. A prototype version of MICRO-X10 proved too slow to be useful but allowed implementation and maintenance issues to be analysed. In conclusion, the usefulness of the problem-driven approach to expert systems development within production planning and control is demonstrated but restrictions imposed by current expert system software are highlighted in that the abilities of such software to cope with `hard' scheduling constructs and also the slow processing speeds of such software can restrict the current usefulness of expert systems within production planning and control.

Strategic development of transport systems: a study of the physical constraints on planning processes

Investment in transport infrastructure can be highly sensitive to uncertainty. The scale and lead time of strategic transport programmes are such that they require continuing policy support and accurate forecasting. Delay, cost escalation and abandonment of projects often result if these conditions are not present. In Part One the physical characteristics of infrastructure are identified as a major constraint on planning processes. The extent to which strategies and techniques acknowledge these constraints is examined. A simple simulation model is developed to evaluate the effects on system development of variations in the scale and lead time of investments. In Part Two, two case studies of strategic infrastructure investment are analysed. The absence of a policy consensus for airport location was an important factor in the delayed resolution of the Third London Airport issue. In London itself, the traffic and environmental effects of major highway investment ultimately resulted in the abandonment of plans to construct urban motorways. In both cases, the infrastructure implications of alternative strategies are reviewed with reference to the problems of uncertainty. In conclusion, the scale of infrastructure investment is considered the most important of the constraints on the processes of transport planning. Adequate appraisal of such constraints may best be achieved by evaluation more closely aligned to policy objectives.

Drying processess in the United Kingdom:assessment of industrial energy utilisation and efficiency of drying systems and the modelling of drying characters using neural networks (BL)

Drying is an important unit operation in process industry. Results have suggested that the energy used for drying has increased from 12% in 1978 to 18% of the total energy used in 1990. A literature survey of previous studies regarding overall drying energy consumption has demonstrated that there is little continuity of methods and energy trends could not be established. In the ceramics, timber and paper industrial sectors specific energy consumption and energy trends have been investigated by auditing drying equipment. Ceramic products examined have included tableware, tiles, sanitaryware, electrical ceramics, plasterboard, refractories, bricks and abrasives. Data from industry has shown that drying energy has not varied significantly in the ceramics sector over the last decade, representing about 31% of the total energy consumed. Information from the timber industry has established that radical changes have occurred over the last 20 years, both in terms of equipment and energy utilisation. The energy efficiency of hardwood drying has improved by 15% since the 1970s, although no significant savings have been realised for softwood. A survey estimating the energy efficiency and operating characteristics of 192 paper dryer sections has been conducted. Drying energy was found to increase to nearly 60% of the total energy used in the early 1980s, but has fallen over the last decade, representing 23% of the total in 1993. These results have demonstrated that effective energy saving measures, such as improved pressing and heat recovery, have been successfully implemented since the 1970s. Artificial neural networks have successfully been applied to model process characteristics of microwave and convective drying of paper coated gypsum cove. Parameters modelled have included product moisture loss, core gypsum temperature and quality factors relating to paper burning and bubbling defects. Evaluation of thermal and dielectric properties have highlighted gypsum's heat sensitive characteristics in convective and electromagnetic regimes. Modelling experimental data has shown that the networks were capable of simulating drying process characteristics to a high degree of accuracy. Product weight and temperature were predicted to within 0.5% and 5C of the target data respectively. Furthermore, it was demonstrated that the underlying properties of the data could be predicted through a high level of input noise.