Human performance modelling as an aid in the process of manufacturing system design

Manufacturing system design is an ongoing activity within industry. Modelling tools based on Discrete Event Simulation are often used by practitioners during this design cycle. However, such tools do not adequately model the behaviour of 'direct' workers in manufacturing environments. There is an important need to expand the capability of modelling to include the relationships between human centred factors (demography, attitudes, beliefs, etc), their working environment (physical and organizational), and their subsequent performance in terms of productive routines. Therefore, this paper describes research that has formed a pilot modelling methodology that is an important first step in providing such a capability.

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.

Using process-oriented holonic (PrOH) modelling to increase understanding of information systems

Methodologies for understanding business processes and their information systems (IS) are often criticized, either for being too imprecise and philosophical (a criticism often levied at softer methodologies) or too hierarchical and mechanistic (levied at harder methodologies). The process-oriented holonic modelling methodology combines aspects of softer and harder approaches to aid modellers in designing business processes and associated IS. The methodology uses holistic thinking and a construct known as the holon to build process descriptions into a set of models known as a holarchy. This paper describes the methodology through an action research case study based in a large design and manufacturing organization. The scientific contribution is a methodology for analysing business processes in environments that are characterized by high complexity, low volume and high variety where there are minimal repeated learning opportunities, such as large IS development projects. The practical deliverables from the project gave IS and business process improvements for the case study company.

The antecedents of prosocial service behaviours:an empirical investigation

Frontline employee attitudes and behaviours during service encounters influence customers' perceptions of service quality. For this reason, the identification of variables that influence service behaviours is important. Much remains unknown about the factors affecting service behaviours in service settings. This study investigates service employees' attitudinal (job satisfaction and organisational commitment) and behavioural (prosocial service behaviours) responses to management strategies (internal communication, professional development and empowerment). One hundred and eighty-eight service employees contributed data, which were analysed using a structural modelling methodology. The authors found that management strategies influence service behaviours directly but the mediating role of job attitudes is not supported.

Applying a public policy evaluation methodology for local socio-economic impacts: an exploration in realistic modelling

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Brain oscillations and connectivity in autism spectrum disorders (ASD):new approaches to methodology, measurement and modelling

Although atypical social behaviour remains a key characterisation of ASD, the presence ofsensory and perceptual abnormalities has been given a more central role in recentclassification changes. An understanding of the origins of such aberrations could thus prove afruitful focus for ASD research. Early neurocognitive models of ASD suggested that thestudy of high frequency activity in the brain as a measure of cortical connectivity mightprovide the key to understanding the neural correlates of sensory and perceptual deviations inASD. As our review shows, the findings from subsequent research have been inconsistent,with a lack of agreement about the nature of any high frequency disturbances in ASD brains.Based on the application of new techniques using more sophisticated measures of brainsynchronisation, direction of information flow, and invoking the coupling between high andlow frequency bands, we propose a framework which could reconcile apparently conflictingfindings in this area and would be consistent both with emerging neurocognitive models ofautism and with the heterogeneity of the condition.

Modelling of non-stationary processes using radial basis function networks

This paper reports preliminary progress on a principled approach to modelling nonstationary phenomena using neural networks. We are concerned with both parameter and model order complexity estimation. The basic methodology assumes a Bayesian foundation. However to allow the construction of pragmatic models, successive approximations have to be made to permit computational tractibility. The lowest order corresponds to the (Extended) Kalman filter approach to parameter estimation which has already been applied to neural networks. We illustrate some of the deficiencies of the existing approaches and discuss our preliminary generalisations, by considering the application to nonstationary time series.

Modelling and improving maintenance decisions:Having foresight with simulation and artificial intelligence

Machine breakdowns are one of the main sources of disruption and throughput fluctuation in highly automated production facilities. One element in reducing this disruption is ensuring that the maintenance team responds correctly to machine failures. It is, however, difficult to determine the current practice employed by the maintenance team, let alone suggest improvements to it. 'Knowledge based improvement' is a methodology that aims to address this issue, by (a) eliciting knowledge on current practice, (b) evaluating that practice and (c) looking for improvements. The methodology, based on visual interactive simulation and artificial intelligence methods, and its application to a Ford engine assembly facility are described. Copyright © 2002 Society of Automotive Engineers, Inc.

Modelling and improving human decision making with simulation

Modelling human interaction and decision-making within a simulation presents a particular challenge. This paper describes a methodology that is being developed known as 'knowledge based improvement'. The purpose of this methodology is to elicit decision-making strategies via a simulation model and to represent them using artificial intelligence techniques. Further to this, having identified an individual's decision-making strategy, the methodology aims to look for improvements in decision-making. The methodology is being tested on unplanned maintenance operations at a Ford engine assembly plant

A note on the modelling the efficiency of top Arab banks

The major aim of this research is benchmarking top Arab banks using Data Envelopment Analysis (DEA) technique and to compare the results with that of published recently in Mostafa (2007a,b) [Mostafa, M. M. (2007a). Modeling the efficiency of top Arab banks: A DEA–neural network approach. Expert Systems with Applications, doi:10.1016/j.eswa.2007.09.001; Mostafa M. M. (2007b), Benchmarking top Arab banks’ efficiency through efficient frontier analysis, Industrial Management & Data Systems, 107(6) 802–823]. Data for 85 Arab banks used to conduct the analysis of relative efficiency. Our findings indicate that (1) the efficiency of Arab banks reported in Mostafa (2007a,b) is incorrect, hence, readers should take extra caution of using such results, (2) the corrected efficiency scores suggest that there is potential for significant improvements in Arab banks. In summary, this study overcomes with some data and methodology issues in measuring efficiency of Arab banks and highlights the importance of encouraging increased efficiency throughout the banking industry in the Arab world using the new results.

Modelling the relationship between local logistics management decisions and overall supply chain performance:A research agenda

Supply chains are advocated widely as being the new units for commercial competition and developments have made the sharing of supply chain wide information increasingly common. Most organisations however still make operational decisions intended to maximise local organisational performance. With improved information sharing a holistic focus for operational decisions should now be possible. The development of a pan supply chain performance framework requires an examination of the conditions under which holistic-decisions provide benefits to either the individual enterprise or the complete supply chain. This paper presents the background and supporting methodology for a study of the impact of an overall supply chain performance metric framework upon local logistics decisions and the conditions under which such a framework would improve overall supply chain performance. The methodology concludes a simulation approach using a functionally extended Gensym's e-SCOR model, together with case based triangulation, to be optimum. Copyright © 2007 Inderscience Enterprises Ltd.

A methodology for the generation and evaluation of biorefinery process chains, in order to identify the most promising biorefineries for the EU

The topic of bioenergy, biofuels and bioproducts remains at the top of the current political and research agenda. Identification of the optimum processing routes for biomass, in terms of efficiency, cost, environment and socio-economics is vital as concern grows over the remaining fossil fuel resources, climate change and energy security. It is known that the only renewable way of producing conventional hydrocarbon fuels and organic chemicals is from biomass, but the problem remains of identifying the best product mix and the most efficient way of processing biomass to products. The aim is to move Europe towards a biobased economy and it is widely accepted that biorefineries are key to this development. A methodology was required for the generation and evaluation of biorefinery process chains for converting biomass into one or more valuable products that properly considers performance, cost, environment, socio-economics and other factors that influence the commercial viability of a process. In this thesis a methodology to achieve this objective is described. The completed methodology includes process chain generation, process modelling and subsequent analysis and comparison of results in order to evaluate alternative process routes. A modular structure was chosen to allow greater flexibility and allowing the user to generate a large number of different biorefinery configurations The significance of the approach is that the methodology is defined and is thus rigorous and consistent and may be readily re-examined if circumstances change. There was the requirement for consistency in structure and use, particularly for multiple analyses. It was important that analyses could be quickly and easily carried out to consider, for example, different scales, configurations and product portfolios and so that previous outcomes could be readily reconsidered. The result of the completed methodology is the identification of the most promising biorefinery chains from those considered as part of the European Biosynergy Project.

A systems methodology for analysing and simulating manufacturing systems

The Systems Engineering Group (SEG) at De Montfort University are developing the Boardman Soft Systems Methodology (BSSM) which allows complex human systems to be modelled, this work builds upon Checkland's Soft Systems Methodology (1981). The BSSM has been applied to the modelling of the systems engineering process as used in design and manufacturing companies. The BSSM is used to solicit information from a company and this data is then transformed into systemic diagrams (systemigrams). These systemigrams are posited to be accurate and concise representations of the system which has been modelled. This paper describes the collaboration between SEG and a manufacturing company (MC) in Leicester, England. The purpose of this collaboration was twofold. First, it was to create an objective view of the MC's processes, in the form of systemigrams. It was important to get this modelled by a source outside of the company, as it is difficult for people within a system being modelled to be unbiased. Secondly, it allowed a series of systemigrams to be produced which can then be subjected to simulation, for the purpose of aiding risk management decisions and to reduce the project cycle time