Creating and sustaining competitive advantage in collaborative systems:the what and the how

Initially this paper asks two questions: In order to create and sustain competitive advantage through collaborative systems WHAT should be managed? and HOW should it be managed? It introduces the competitive business structure and reviews some of the global trends in manufacturing and business, which leads to focus on manage processes, value propositions and extended business processes. It then goes on to develop a model of the collaborative architecture for extended enterprises and demonstrates the validity of this architecture through a case study. It concludes that, in order to create and sustain competitive advantage, collaborative systems should facilitate the management of: the collaborative architecture of the extended enterprise; the extended business processes and the value proposition for each extended enterprise through a meta level management process. It also identifies areas for further research, such as better understanding of: the exact nature and interaction of multiple strategies within an enterprise; how to manage people/teams working along extended business processes; and the nature and prerequisites of the manage processes.

Reliability:its implications in production systems design

Research on production systems design has in recent years tended to concentrate on ‘software’ factors such as organisational aspects, work design, and the planning of the production operations. In contrast, relatively little attention has been paid to maximising the contributions made by fixed assets, particularly machines and equipment. However, as the cost of unproductive machine time has increased, reliability, particularly of machine tools, has become ever more important. Reliability theory and research has traditionally been based in the main on electrical and electronic equipment whereas mechanical devices, especially machine tools, have not received sufficiently objective treatment. A recently completed research project has considered the reliability of machine tools by taking sample surveys of purchasers, maintainers and manufacturers. Breakdown data were also collected from a number of engineering companies and analysed using both manual and computer techniques. Results obtained have provided an indication of those factors most likely to influence reliability and which in turn could lead to improved design and selection of machine tool systems. Statistical analysis of long-term field data has revealed patterns of trends of failure which could help in the design of more meaningful maintenance schemes.

Inference by belief propagation in composite systems

We devise a message passing algorithm for probabilistic inference in composite systems, consisting of a large number of variables, that exhibit weak random interactions among all variables and strong interactions with a small subset of randomly chosen variables; the relative strength of the two interactions is controlled by a free parameter. We examine the performance of the algorithm numerically on a number of systems of this type for varying mixing parameter values.

Estimating parameters in stochastic systems:a variational Bayesian approach

This work is concerned with approximate inference in dynamical systems, from a variational Bayesian perspective. When modelling real world dynamical systems, stochastic differential equations appear as a natural choice, mainly because of their ability to model the noise of the system by adding a variation of some stochastic process to the deterministic dynamics. Hence, inference in such processes has drawn much attention. Here a new extended framework is derived that is based on a local polynomial approximation of a recently proposed variational Bayesian algorithm. The paper begins by showing that the new extension of this variational algorithm can be used for state estimation (smoothing) and converges to the original algorithm. However, the main focus is on estimating the (hyper-) parameters of these systems (i.e. drift parameters and diffusion coefficients). The new approach is validated on a range of different systems which vary in dimensionality and non-linearity. These are the Ornstein–Uhlenbeck process, the exact likelihood of which can be computed analytically, the univariate and highly non-linear, stochastic double well and the multivariate chaotic stochastic Lorenz ’63 (3D model). As a special case the algorithm is also applied to the 40 dimensional stochastic Lorenz ’96 system. In our investigation we compare this new approach with a variety of other well known methods, such as the hybrid Monte Carlo, dual unscented Kalman filter, full weak-constraint 4D-Var algorithm and analyse empirically their asymptotic behaviour as a function of observation density or length of time window increases. In particular we show that we are able to estimate parameters in both the drift (deterministic) and the diffusion (stochastic) part of the model evolution equations using our new methods.

Transport phenomena in hydrogel membranes

In this thesis the factors surrounding the permeation of alkali and alkaline earth metal salts through hydrogel membranes are investigated. Although of relevance to aqueous separations in general, it was with their potential application in sensors that this work was particularly concerned. In order to study the effect that the nature of the solute has on the transport process, a single polymer matrix, poly (2-hydroxyethyl methacrylate), was initially studied. The influence of cation variation in the presence of a fixed anion was looked at, followed by the effect of the anion in the presence of a fixed cation. The anion was found to possess the dominant influence and tended to subsume any influence by the cation. This is explained in terms of the structure-making and structure-breaking characteristics of the ions in their solute-water interactions. Analogies in the transport behaviour of the salts are made with the Hofmeister series. The effect of the chemical composition of the polymer backbone on the water structuring in the hydrogel and, consequently, transport through the membrane, was investigated by preparing a series of poly (2-hydroxyethyl methacrylate) copolymer membranes and determining the permeability coefficient of salts with a fixed anion. The results were discussed in terms of the `free-volume' model of permeation and the water structuring of the polymer backbone. The ability of ionophores to selectively modulate the permeation of salts through hydrogel membranes was also examined. The results indicated that a dualsorption model was in operation. Finally, hydrogels were used as membrane overlays on coated wire ion-selective electrodes that employed conventional plasticised-PVC-valinomycin based sensing membranes. The hydrogel overlays were found to affect the access of the analyte but not the underlying electrochemistry.

Localized waves in optical systems with periodic dispersion and nonlinearity management

We overview our recent developments in the theory of dispersion-managed (DM) solitons within the context of optical applications. First, we present a class of localized solutions with a period multiple to that of the standard DM soliton in the nonlinear Schrödinger equation with periodic variations of the dispersion. In the framework of a reduced ordinary differential equation-based model, we discuss the key features of these structures, such as a smaller energy compared to traditional DM solitons with the same temporal width. Next, we present new results on dissipative DM solitons, which occur in the context of mode-locked lasers. By means of numerical simulations and a reduced variational model of the complex Ginzburg-Landau equation, we analyze the influence of the different dissipative processes that take place in a laser.