Modelling human performance within manufacturing systems design:from a theoretical towards a practical framework

Computer-based simulation is frequently used to evaluate the capabilities of proposed manufacturing system designs. Unfortunately, the real systems are often found to perform quite differently from simulation predictions and one possible reason for this is an over-simplistic representation of workers' behaviour within current simulation techniques. The accuracy of design predictions could be improved through a modelling tool that integrates with computer-based simulation and incorporates the factors and relationships that determine workers' performance. This paper explores the viability of developing a similar tool based on our previously published theoretical modelling framework. It focuses on evolving this purely theoretical framework towards a practical modelling tool that can actually be used to expand the capabilities of current simulation techniques. Based on an industrial study, the paper investigates how the theoretical framework works in practice, analyses strengths and weaknesses in its formulation, and proposes developments that can contribute towards enabling human performance modelling in a practical way.

Improving the design process for factories:modelling human performance variation

Theprocess of manufacturing system design frequently includes modeling, and usually, this means applying a technique such as discrete event simulation (DES). However, the computer tools currently available to apply this technique enable only a superficial representation of the people that operate within the systems. This is a serious limitation because the performance of people remains central to the competitiveness of many manufacturing enterprises. Therefore, this paper explores the use of probability density functions to represent the variation of worker activity times within DES models.

Towards a theoretical framework for human performance modelling within manufacturing systems design

The performance of direct workers has a significant impact on the competitiveness of many manufacturing systems. Unfortunately, system designers are ill equipped to assess this impact during the design process. An opportunity exists to assist designers by expanding the capabilities of popular simulation modelling tools, and using them as a vehicle to better consider human factors during the process of system design manufacture. To support this requirement, this paper reports on an extensive review of literature that develops a theoretical framework, which summarizes the principal factors and relationships that such a modelling tool should incorporate.

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.

Human performance modelling as an aid to manufacturing system design

Once the factory worker was considered to be a necessary evil, soon to be replaced by robotics and automation. Today, many manufacturers appreciate that people in direct productive roles can provide important flexibility and responsiveness, and so significantly contribute to business success. The challenge is no longer to design people out of the factory, but to design factory environment that help to get the best performance from people. This paper describes research that has set out to help to achieve this by expanding the capabilities of simulation modeling tools currently used by practitioners.

An evaluation of human performance in a risk environment

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Perception of concurrent sentences with harmonic or frequency-shifted voiced excitation:performance of human listeners and of computational models based on autocorrelation

Keyword identification in one of two simultaneous sentences is improved when the sentences differ in F0, particularly when they are almost continuously voiced. Sentences of this kind were recorded, monotonised using PSOLA, and re-synthesised to give a range of harmonic ?F0s (0, 1, 3, and 10 semitones). They were additionally re-synthesised by LPC with the LPC residual frequency shifted by 25% of F0, to give excitation with inharmonic but regularly spaced components. Perceptual identification of frequency-shifted sentences showed a similar large improvement with nominal ?F0 as seen for harmonic sentences, although overall performance was about 10% poorer. We compared performance with that of two autocorrelation-based computational models comprising four stages: (i) peripheral frequency selectivity and half-wave rectification; (ii) within-channel periodicity extraction; (iii) identification of the two major peaks in the summary autocorrelation function (SACF); (iv) a template-based approach to speech recognition using dynamic time warping. One model sampled the correlogram at the target-F0 period and performed spectral matching; the other deselected channels dominated by the interferer and performed matching on the short-lag portion of the residual SACF. Both models reproduced the monotonic increase observed in human performance with increasing ?F0 for the harmonic stimuli, but not for the frequency-shifted stimuli. A revised version of the spectral-matching model, which groups patterns of periodicity that lie on a curve in the frequency-delay plane, showed a closer match to the perceptual data for frequency-shifted sentences. The results extend the range of phenomena originally attributed to harmonic processing to grouping by common spectral pattern.

Introduction: improving manufacturing performance through technology diffusion, implementation and management

The role of technology management in achieving improved manufacturing performance has been receiving increased attention as enterprises are becoming more exposed to competition from around the world. In the modern market for manufactured goods the demand is now for more product variety, better quality, shorter delivery and greater flexibility, while the financial and environmental cost of resources has become an urgent concern to manufacturing managers. This issue of the International Journal of Technology Management addresses the question of how the diffusion, implementation and management of technology can improve the performance of manufacturing industries. The authors come from a large number of different countries and their contributions cover a wide range of topics within this general theme. Some papers are conceptual, others report on research carried out in a range of different industries including steel production, iron founding, electronics, robotics, machinery, precision engineering, metal working and motor manufacture. In some cases they describe situations in specific countries. Several are based on presentations made at the UK Operations Management Association's Sixth International Conference held at Aston University at which the conference theme was 'Achieving Competitive Edge: Getting Ahead Through Technology and People'. The first two papers deal with questions of advanced manufacturing technology implementation and management. Firstly Beatty describes a three year longitudinal field study carried out in ten Canadian manufacturing companies using CADICAM and CIM systems. Her findings relate to speed of implementation, choice of system type, the role of individuals in implementation, organization and job design. This is followed by a paper by Bessant in which he argues that a more a strategic approach should be taken towards the management of technology in the 1990s and beyond. Also considered in this paper are the capabilities necessary in order to deploy advanced manufacturing technology as a strategic resource and the way such capabilities might be developed within the firm. These two papers, which deal largely with the implementation of hardware, are supplemented by Samson and Sohal's contribution in which they argue that a much wider perspective should be adopted based on a new approach to manufacturing strategy formulation. Technology transfer is the topic of the following two papers. Pohlen again takes the case of advanced manufacturing technology and reports on his research which considers the factors contributing to successful realisation of AMT transfer. The paper by Lee then provides a more detailed account of technology transfer in the foundry industry. Using a case study based on a firm which has implemented a number of transferred innovations a model is illustrated in which the 'performance gap' can be identified and closed. The diffusion of technology is addressed in the next two papers. In the first of these, by Lowe and Sim, the managerial technologies of 'Just in Time' and 'Manufacturing Resource Planning' (or MRP 11) are examined. A study is described from which a number of factors are found to influence the adoption process including, rate of diffusion and size. Dahlin then considers the case of a specific item of hardware technology, the industrial robot. Her paper reviews the history of robot diffusion since the early 1960s and then tries to predict how the industry will develop in the future. The following two papers deal with the future of manufacturing in a more general sense. The future implementation of advanced manufacturing technology is the subject explored by de Haan and Peters who describe the results of their Dutch Delphi forecasting study conducted among a panel of experts including scientists, consultants, users and suppliers of AMT. Busby and Fan then consider a type of organisational model, 'the extended manufacturing enterprise', which would represent a distinct alternative pure market-led and command structures by exploiting the shared knowledge of suppliers and customers. The three country-based papers consider some strategic issues relating manufacturing technology. In a paper based on investigations conducted in China He, Liff and Steward report their findings from strategy analyses carried out in the steel and watch industries with a view to assessing technology needs and organizational change requirements. This is followed by Tang and Nam's paper which examines the case of machinery industry in Korea and its emerging importance as a key sector in the Korean economy. In his paper which focuses on Venezuela, Ernst then considers the particular problem of how this country can address the problem of falling oil revenues. He sees manufacturing as being an important contributor to Venezuela's future economy and proposes a means whereby government and private enterprise can co-operate in development of the manufacturing sector. The last six papers all deal with specific topics relating to the management manufacturing. Firstly Youssef looks at the question of manufacturing flexibility, introducing and testing a conceptual model that relates computer based technologies flexibility. Dangerfield's paper which follows is based on research conducted in the steel industry. He considers the question of scale and proposes a modelling approach determining the plant configuration necessary to meet market demand. Engstrom presents the results of a detailed investigation into the need for reorganising material flow where group assembly of products has been adopted. Sherwood, Guerrier and Dale then report the findings of a study into the effectiveness of Quality Circle implementation. Stillwagon and Burns, consider how manufacturing competitiveness can be improved individual firms by describing how the application of 'human performance engineering' can be used to motivate individual performance as well as to integrate organizational goals. Finally Sohal, Lewis and Samson describe, using a case study example, how just-in-time control can be applied within the context of computer numerically controlled flexible machining lines. The papers in this issue of the International Journal of Technology Management cover a wide range of topics relating to the general question of improving manufacturing performance through the dissemination, implementation and management of technology. Although they differ markedly in content and approach, they have the collective aim addressing the concepts, principles and practices which provide a better understanding the technology of manufacturing and assist in achieving and maintaining a competitive edge.

Edge coding in human vision: a psychophysical and computational investigation

This thesis presents a study of how edges are detected and encoded by the human visual system. The study begins with theoretical work on the development of a model of edge processing, and includes psychophysical experiments on humans, and computer simulations of these experiments, using the model. The first chapter reviews the literature on edge processing in biological and machine vision, and introduces the mathematical foundations of this area of research. The second chapter gives a formal presentation of a model of edge perception that detects edges and characterizes their blur, contrast and orientation, using Gaussian derivative templates. This model has previously been shown to accurately predict human performance in blur matching tasks with several different types of edge profile. The model provides veridical estimates of the blur and contrast of edges that have a Gaussian integral profile. Since blur and contrast are independent parameters of Gaussian edges, the model predicts that varying one parameter should not affect perception of the other. Psychophysical experiments showed that this prediction is incorrect: reducing the contrast makes an edge look sharper; increasing the blur reduces the perceived contrast. Both of these effects can be explained by introducing a smoothed threshold to one of the processing stages of the model. It is shown that, with this modification,the model can predict the perceived contrast and blur of a number of edge profiles that differ markedly from the ideal Gaussian edge profiles on which the templates are based. With only a few exceptions, the results from all the experiments on blur and contrast perception can be explained reasonably well using one set of parameters for each subject. In the few cases where the model fails, possible extensions to the model are discussed.

Effects of pixel noise and stimulus structure on visual detection performance

This thesis consisted of two major parts, one determining the masking characteristics of pixel noise and the other investigating the properties of the detection filter employed by the visual system. The theoretical cut-off frequency of white pixel noise can be defined from the size of the noise pixel. The empirical cut-off frequency, i.e. the largest size of noise pixels that mimics the effect of white noise in detection, was determined by measuring contrast energy thresholds for grating stimuli in the presence of spatial noise consisting of noise pixels of various sizes and shapes. The critical i.e. minimum number of noise pixels per grating cycle needed to mimic the effect of white noise in detection was found to decrease with the bandwidth of the stimulus. The shape of the noise pixels did not have any effect on the whiteness of pixel noise as long as there was at least the minimum number of noise pixels in all spatial dimensions. Furthermore, the masking power of white pixel noise is best described when the spectral density is calculated by taking into account all the dimensions of noise pixels, i.e. width, height, and duration, even when there is random luminance only in one of these dimensions. The properties of the detection mechanism employed by the visual system were studied by measuring contrast energy thresholds for complex spatial patterns as a function of area in the presence of white pixel noise. Human detection efficiency was obtained by comparing human performance with an ideal detector. The stimuli consisted of band-pass filtered symbols, uniform and patched gratings, and point stimuli with randomised phase spectra. In agreement with the existing literature, the detection performance was found to decline with the increasing amount of detail and contour in the stimulus. A measure of image complexity was developed and successfully applied to the data. The accuracy of the detection mechanism seems to depend on the spatial structure of the stimulus and the spatial spread of contrast energy.