Modelling the behaviour of engine assembly workers

Presents a prototype modelling methodology that provides a generic approach to the creation of quantitative models of the relationships between a working environment, the direct workers and their subsequent performance. Once created for an organisation, such models can provide a prediction of how the behaviour of their workers will alter in response to changes in their working environment. The goal of this work is to improve the decision processes used in the design of the working environment. Through improving such processes, companies will gain better performance from their direct workers, and so improve business competitiveness. This paper first presents the need to model the behaviour of direct workers in manufacturing environments. To begin to address this need, a simplistic modelling framework is developed, and then this is expanded to provide a detailed modelling methodology. There then follows a description of an industrial evaluation of this methodology at Ford Motor Company. This modelling methodology has been assessed in this case study and has been found to be valid in this case. There are many challenges that this theme of research needs to address. The work described in this paper has made an important first step in this area, having gone some way to establishing a generic methodology and illustrating its potential value. Our future work will build on this foundation.

Modelling short crack growth behaviour in nickel-base superalloys

This paper provides a description of the features and mechanisms of facetted short crack growth in Ni-base superalloys, and briefly reviews existing short crack growth models in terms of their application to Ni-base alloys. The concept of “soft barriers” is introduced to produce a new two-phase model for local microstructural effects on short crack growth in Waspaloy. This is derived from detailed observations of crack growth through individual grains. The model differs from all previous approaches in highlighting the importance of crack path perturbations within grains. Potential applications of the model in alloy development are discussed.

The challenges of representing human behaviour in simulation models:some case examples from supply chain, evacuation modelling and rail disruption

As more of the economy moves from traditional manufacturing to the service sector, the nature of work is becoming less tangible and thus, the representation of human behaviour in models is becoming more important. Representing human behaviour and decision making in models is challenging, both in terms of capturing the essence of the processes, and also the way that those behaviours and decisions are or can be represented in the models themselves. In order to advance understanding in this area, a useful first step is to evaluate and start to classify the various types of behaviour and decision making that are required to be modelled. This talk will attempt to set out and provide an initial classification of the different types of behaviour and decision making that a modeller might want to represent in a model. Then, it will be useful to start to assess the main methods of simulation in terms of their capability in representing these various aspects. The three main simulation methods, System Dynamics, Agent Based Modelling and Discrete Event Simulation all achieve this to varying degrees. There is some evidence that all three methods can, within limits, represent the key aspects of the system being modelled. The three simulation approaches are then assessed for their suitability in modelling these various aspects. Illustration of behavioural modelling will be provided from cases in supply chain management, evacuation modelling and rail disruption.

An Overview of Modelling Bulgarian Wildland Fire Behaviour by Application of a Mathematical Game Method and WRF-Fire Models

This paper presents the main achievements of the author’s PhD dissertation. The work is dedicated to mathematical and semi-empirical approaches applied to the case of Bulgarian wildland fires. After the introductory explanations, short information from every chapter is extracted to cover the main parts of the obtained results. The methods used are described in brief and main outcomes are listed. ACM Computing Classification System (1998): D.1.3, D.2.0, K.5.1.

Modelling question selection behaviour in online communities

Value of online Question Answering (QandA) communities is driven by the question-answering behaviour of its members. Finding the questions that members are willing to answer is therefore vital to the effcient operation of such communities. In this paper, we aim to identify the parameters that cor- relate with such behaviours. We train different models and construct effective predictions using various user, question and thread feature sets. We show that answering behaviour can be predicted with a high level of success.

A primary care web-based intervention modelling experiment replicated behaviour changes seen in earlier paper-based experiment

Acknowledgements and funding We would like to thank the GPs who took part in this study. We would also like to thank Marie Pitkethly and Gail Morrison for their help and support in recruiting GPs to the study. WIME was funded by the Chief Scientist Office, grant number CZH/4/610. The Health Services Research Unit, University of Aberdeen, is core funded by the Chief Scientist Office of the Scottish Government Health Directorates.

Tracing the behaviour of a bridge using time series modelling

Peer reviewed

Modelling the crush behaviour of thermoplastic composites

Thermoplastic composites are likely to emerge as the preferred solution for meeting the high-volume production demands of passenger road vehicles. Substantial effort is currently being directed towards the development of new modelling techniques to reduce the extent of costly and time consuming physical testing. Developing a high-fidelity numerical model to predict the crush behaviour of composite laminates is dependent on the accurate measurement of material properties as well as a thorough understanding of damage mechanisms associated with crush events. This paper details the manufacture, testing and modelling of self-supporting corrugated-shaped thermoplastic composite specimens for crashworthiness assessment. These specimens demonstrated a 57.3% higher specific energy absorption compared to identical specimen made from thermoset composites. The corresponding damage mechanisms were investigated in-situ using digital microscopy and post analysed using Scanning Electron Microscopy (SEM). Splaying and fragmentation modes were the 2 primary failure modes involving fibre breakage, matrix cracking and delamination. A mesoscale composite damage model, with new non-linear shear constitutive laws, which combines a range of novel techniques to accurately capture the material response under crushing, is presented. The force-displacement curves, damage parameter maps and dissipated energy, obtained from the numerical analysis, are shown to be in a good qualitative and quantitative agreement with experimental results. The proposed approach could significantly reduce the extent of physical testing required in the development of crashworthy structures.  

Analysis and modelling of immune cell behaviour in lymph nodes based on multi-photon imaging

This thesis presents quantitative studies of T cell and dendritic cell (DC) behaviour in mouse lymph nodes (LNs) in the naive state and following immunisation. These processes are of importance and interest in basic immunology, and better understanding could improve both diagnostic capacity and therapeutic manipulations, potentially helping in producing more effective vaccines or developing treatments for autoimmune diseases. The problem is also interesting conceptually as it is relevant to other fields where 3D movement of objects is tracked with a discrete scanning interval. A general immunology introduction is presented in chapter 1. In chapter 2, I apply quantitative methods to multi-photon imaging data to measure how T cells and DCs are spatially arranged in LNs. This has been previously studied to describe differences between the naive and immunised state and as an indicator of the magnitude of the immune response in LNs, but previous analyses have been generally descriptive. The quantitative analysis shows that some of the previous conclusions may have been premature. In chapter 3, I use Bayesian state-space models to test some hypotheses about the mode of T cell search for DCs. A two-state mode of movement where T cells can be classified as either interacting to a DC or freely migrating is supported over a model where T cells would home in on DCs at distance through for example the action of chemokines. In chapter 4, I study whether T cell migration is linked to the geometric structure of the fibroblast reticular network (FRC). I find support for the hypothesis that the movement is constrained to the fibroblast reticular cell (FRC) network over an alternative 'random walk with persistence time' model where cells would move randomly, with a short-term persistence driven by a hypothetical T cell intrinsic 'clock'. I also present unexpected results on the FRC network geometry. Finally, a quantitative method is presented for addressing some measurement biases inherent to multi-photon imaging. In all three chapters, novel findings are made, and the methods developed have the potential for further use to address important problems in the field. In chapter 5, I present a summary and synthesis of results from chapters 3-4 and a more speculative discussion of these results and potential future directions.

Modelling human behaviour and event detection from videos

Automatic analysis of human behaviour in large collections of videos is gaining interest, even more so with the advent of file sharing sites such as YouTube. However, challenges still exist owing to several factors such as inter- and intra-class variations, cluttered backgrounds, occlusion, camera motion, scale, view and illumination changes. This research focuses on modelling human behaviour for action recognition in videos. The developed techniques are validated on large scale benchmark datasets and applied on real-world scenarios such as soccer videos. Three major contributions are made. The first contribution is in the area of proper choice of a feature representation for videos. This involved a study of state-of-the-art techniques for action recognition, feature extraction processing and dimensional reduction techniques so as to yield the best performance with optimal computational requirements. Secondly, temporal modelling of human behaviour is performed. This involved frequency analysis and temporal integration of local information in the video frames to yield a temporal feature vector. Current practices mostly average the frame information over an entire video and neglect the temporal order. Lastly, the proposed framework is applied and further adapted to real-world scenario such as soccer videos. A dataset consisting of video sequences depicting events of players falling is created from actual match data to this end and used to experimentally evaluate the proposed framework.

Modelling and analysing human behaviour in a department store using discrete event and agent based simulation

Discrete Event Simulation (DES) is a very popular simulation technique in Operational Research. Recently, there has been the emergence of another technique, namely Agent Based Simulation (ABS). Although there is a lot of literature relating to DES and ABS, we have found less that focuses on exploring the capabilities of both in tackling human behaviour issues. In order to understand the gap between these two simulation techniques, therefore, our aim is to understand the distinctions between DES and ABS models with the real world phenomenon in modelling and simulating human behaviour. In achieving the aim, we have carried out a case study at a department store. Both DES and ABS models will be compared using the same problem domain which is concerning on management policy in a fitting room. The behaviour of staffs while working and customers’ satisfaction will be modelled for both models behaviour understanding.

Modelling reactive and proactive behaviour in simulation

This research investigated the simulation model behaviour of a traditional and combined discrete event as well as agent based simulation models when modelling human reactive and proactive behaviour in human centric complex systems. A departmental store was chosen as human centric complex case study where the operation system of a fitting room in WomensWear department was investigated. We have looked at ways to determine the efficiency of new management policies for the fitting room operation through simulating the reactive and proactive behaviour of staff towards customers. Once development of the simulation models and their verification had been done, we carried out a validation experiment in the form of a sensitivity analysis. Subsequently, we executed a statistical analysis where the mixed reactive and proactive behaviour experimental results were compared with some reactive experimental results from previously published works. Generally, this case study discovered that simple proactive individual behaviour could be modelled in both simulation models. In addition, we found the traditional discrete event model performed similar in the simulation model output compared to the combined discrete event and agent based simulation when modelling similar human behaviour.

Modelling and simulations of ductile iron solidification-induced variations in mechanical behaviour on component and microstructural level

The mechanical behaviour and performance of a ductile iron component is highly dependent on the local variations in solidification conditions during the casting process. Here we show a framework which combine a previously developed closed chain of simulations for cast components with a micro-scale Finite Element Method (FEM) simulation of the behaviour and performance of the microstructure. A casting process simulation, including modelling of solidification and mechanical material characterization, provides the basis for a macro-scale FEM analysis of the component. A critical region is identified to which the micro-scale FEM simulation of a representative microstructure, generated using X-ray tomography, is applied. The mechanical behaviour of the different microstructural phases are determined using a surrogate model based optimisation routine and experimental data. It is discussed that the approach enables a link between solidification- and microstructure-models and simulations of as well component as microstructural behaviour, and can contribute with new understanding regarding the behaviour and performance of different microstructural phases and morphologies in industrial ductile iron components in service.

Thermal error evaluation and modelling of a CNC cylindrical grinding machine

With the relentless quest for improved performance driving ever tighter tolerances for manufacturing, machine tools are sometimes unable to meet the desired requirements. One option to improve the tolerances of machine tools is to compensate for their errors. Among all possible sources of machine tool error, thermally induced errors are, in general for newer machines, the most important. The present work demonstrates the evaluation and modelling of the behaviour of the thermal errors of a CNC cylindrical grinding machine during its warm-up period.