Using system dynamics in a discrete-event simulation study of a manufacturing plant

Purpose - To provide an example of the use of system dynamics within the context of a discrete-event simulation study. Design/methodology/approach - A discrete-event simulation study of a production-planning facility in a gas cylinder-manufacturing plant is presented. The case study evidence incorporates questionnaire responses from sales managers involved in the order-scheduling process. Findings - As the project progressed it became clear that, although the discrete-event simulation would meet the objectives of the study in a technical sense, the organizational problem of "delivery performance" would not be solved by the discrete-event simulation study alone. The case shows how the qualitative outcomes of the discrete-event simulation study led to an analysis using the system dynamics technique. The system dynamics technique was able to model the decision-makers in the sales and production process and provide a deeper understanding of the performance of the system. Research limitations/implications - The case study describes a traditional discrete-event simulation study which incorporated an unplanned investigation using system dynamics. Further, case studies using a planned approach to showing consideration of organizational issues in discrete-event simulation studies are required. Then the role of both qualitative data in a discrete-event simulation study and the use of supplementary tools which incorporate organizational aspects may help generate a methodology for discrete-event simulation that incorporates human aspects and so improve its relevance for decision making. Practical implications - It is argued that system dynamics can provide a useful addition to the toolkit of the discrete-event simulation practitioner in helping them incorporate a human aspect in their analysis. Originality/value - Helps decision makers gain a broader perspective on the tools available to them by showing the use of system dynamics to supplement the use of discrete-event simulation. © Emerald Group Publishing Limited.

Cause, effect and benefits of a standardised corporate visual identity system of UK companies operating in Malaysia

Investigates the degree of global standardisation of a corporate visual identity system (CVIS) in multinational operations. A special emphasis of this research is accorded to UK companies operating in Malaysia. In particular, the study seeks to reveal the reasons for developing a standardised CVIS; the behavioural issues associated with CVIS; and the determination in selecting a graphic design agency. The findings of the research revealed that multinational corporations in an increasingly corporate environment adopted a standardised CVIS for several reasons, including, aiding the sale of products and services, creating an attractive environment for hiring employees, and increasing the company’s stature and presence. Further findings show that the interest in global identity was stimulated by global restructuring, merger or acquisition. The above trends help explain why increased focus has been accorded to CVIS over the past five years by many UK companies operating in Malaysia. Additional findings reveal that both the UK design agencies and in-house design department are used in the development of the firms’ CVIS.

Designing a methodology for an office communication and information system:for executives in the Malaysian public sector : the Prime Minister's office

Modern managers are under tremendous pressure in attempting to fulfil a profoundly complex managerial task, that of handling information resources. Information management, an intricate process requiring a high measure of human cognition and discernment, involves matching a manager's lack of information processing capacity against his information needs, with voluminous information at his disposal. The nature of the task will undoubtedly become more complex in the case of a large organisation. Management of large-scale organisations is therefore an exceedingly challenging prospect for any manager to be faced with. A system that supports executive information needs will help reduce managerial and informational mismatches. In the context of the Malaysian public sector, the task of overall management lies with the Prime Minister and the Cabinet. The Prime Minister's Office is presently supporting the Prime Minister's information and managerial needs, although not without various shortcomings. The rigid formalised structure predominant of the Malaysian public sector, so opposed to dynamic treatment of problematic issues as faced by that sector, further escalates the managerial and organisational problem of coping with a state of complexity. The principal features of the research are twofold: the development of a methodology for diagnosing the problem organisation' and the design of an office system. The methodological development is done in the context of the Malaysian public sector, and aims at understanding the complexity of its communication and control situation. The outcome is a viable model of the public sector. `Design', on the other hand, is developing a syntax or language for office systems which provides an alternative to current views on office systems. The design is done with reference to, rather than for, the Prime Minister's Office. The desirable outcome will be an office model called Office Communication and Information System (OCIS).

Analysis of magnetoencephaoographic data as a nonlinear dynamical system

This thesis presents the results from an investigation into the merits of analysing Magnetoencephalographic (MEG) data in the context of dynamical systems theory. MEG is the study of both the methods for the measurement of minute magnetic flux variations at the scalp, resulting from neuro-electric activity in the neocortex, as well as the techniques required to process and extract useful information from these measurements. As a result of its unique mode of action - by directly measuring neuronal activity via the resulting magnetic field fluctuations - MEG possesses a number of useful qualities which could potentially make it a powerful addition to any brain researcher's arsenal. Unfortunately, MEG research has so far failed to fulfil its early promise, being hindered in its progress by a variety of factors. Conventionally, the analysis of MEG has been dominated by the search for activity in certain spectral bands - the so-called alpha, delta, beta, etc that are commonly referred to in both academic and lay publications. Other efforts have centred upon generating optimal fits of "equivalent current dipoles" that best explain the observed field distribution. Many of these approaches carry the implicit assumption that the dynamics which result in the observed time series are linear. This is despite a variety of reasons which suggest that nonlinearity might be present in MEG recordings. By using methods that allow for nonlinear dynamics, the research described in this thesis avoids these restrictive linearity assumptions. A crucial concept underpinning this project is the belief that MEG recordings are mere observations of the evolution of the true underlying state, which is unobservable and is assumed to reflect some abstract brain cognitive state. Further, we maintain that it is unreasonable to expect these processes to be adequately described in the traditional way: as a linear sum of a large number of frequency generators. One of the main objectives of this thesis will be to prove that much more effective and powerful analysis of MEG can be achieved if one were to assume the presence of both linear and nonlinear characteristics from the outset. Our position is that the combined action of a relatively small number of these generators, coupled with external and dynamic noise sources, is more than sufficient to account for the complexity observed in the MEG recordings. Another problem that has plagued MEG researchers is the extremely low signal to noise ratios that are obtained. As the magnetic flux variations resulting from actual cortical processes can be extremely minute, the measuring devices used in MEG are, necessarily, extremely sensitive. The unfortunate side-effect of this is that even commonplace phenomena such as the earth's geomagnetic field can easily swamp signals of interest. This problem is commonly addressed by averaging over a large number of recordings. However, this has a number of notable drawbacks. In particular, it is difficult to synchronise high frequency activity which might be of interest, and often these signals will be cancelled out by the averaging process. Other problems that have been encountered are high costs and low portability of state-of-the- art multichannel machines. The result of this is that the use of MEG has, hitherto, been restricted to large institutions which are able to afford the high costs associated with the procurement and maintenance of these machines. In this project, we seek to address these issues by working almost exclusively with single channel, unaveraged MEG data. We demonstrate the applicability of a variety of methods originating from the fields of signal processing, dynamical systems, information theory and neural networks, to the analysis of MEG data. It is noteworthy that while modern signal processing tools such as independent component analysis, topographic maps and latent variable modelling have enjoyed extensive success in a variety of research areas from financial time series modelling to the analysis of sun spot activity, their use in MEG analysis has thus far been extremely limited. It is hoped that this work will help to remedy this oversight.

The interaction between the implementation of an occupational health and safety management system and safety culture:a case study in the rubber industry

A prominent theme emerging in Occupational Health and Safety (OSH) is the development of management systems. A range of interventions, according to a prescribed route detailed by one of the management systems, can be introduced into an organisation with some expectation of improved OSH performance. This thesis attempts to identify the key influencing factors that may impact upon the process of introducing interventions, (according to B88800: 1996, Guide to Implementing Occupational Health and Safety Management Systems) into an organisation. To help identify these influencing factors a review of possible models from the sphere of Total Quality Management (TQM) was undertaken and the most suitable TQM model selected for development and use in aSH. By anchoring the aSH model's development in the reviewed literature a range ofeare, medium and low level influencing factors were identified. This model was developed in conjunction with the research data generated within the case study organisation (rubber manufacturer) and applied to the organisation. The key finding was that the implementation of an OSH intervention was dependant upon three broad vectors of influence. These are the Incentive to introduce change within an organisation which refers to the drivers or motivators for OSH. Secondly the Ability within the management team to actually implement the changes refers to aspects, amongst others, such as leadership, commitment and perceptions of OSH. Ability is in turn itself influenced by the environment within which change is being introduced. TItis aspect of Receptivity refers to the history of the plant and characteristics of the workforce. Aspects within Receptivity include workforce profile and organisational policies amongst others. It was found that the TQM model selected and developed for an OSH management system intervention did explain the core influencing factors and their impact upon OSH performance. It was found that within the organisation the results that may have been expected from implementation of BS8800:1996 were not realised. The OSH model highlighted that given the organisation's starting point, a poor appreciation of the human factors of OSH, gave little reward for implementation of an OSH management system. In addition it was found that general organisational culture can effectively suffocate any attempts to generate a proactive safety culture.

General features of Multiple System Atrophy

Multiple system atrophy (MSA) is a rare movement disorder and a member of a group of neurodegenerative diseases referred to collectively as the ‘parkinsonian syndromes’. Characteristic of these syndromes is that the patient exhibits symptoms of ‘parkinsonism’, viz., a range of problems involving movement, most typically manifest in Parkinson’s disease (PD) itself1, but also seen in progressive supranuclear palsy (PSP), and to some extent in dementia with Lewy bodies (DLB). MSA is a relatively ‘new’ descriptive term and is derived from three previously described diseases, viz., olivopontocerebellar atrophy, striato-nigral degeneration, and Shy-Drager syndrome. The classical symptoms of MSA include parkinsonism, ataxia, and autonomic dysfunction.6 Ataxia describes a gross lack of coordination of muscle movements while autonomic dysfunction involves a variety of systems that regulate unconscious bodily functions such as heart rate, blood pressure, bladder function, and digestion. Although primarily a neurological disorder, patients with MSA may also develop visual signs and symptoms that could be useful in differential diagnosis. The most important visual signs may include oculomotor dysfunction and problems in pupil reactivity but are less likely to involve aspects of primary vision such as visual acuity, colour vision, and visual fields. In addition, the eye-care practitioner can contribute to the management of the visual problems of MSA and therefore, help to improve quality of life of the patient. Hence, this first article in a two-part series describes the general features of MSA including its prevalence, signs and symptoms, diagnosis, pathology, and possible causes.

Visual signs and symptoms of Multiple System Atrophy

Multiple system atrophy (MSA) is a rare movement disorder and a member of a group of neurodegenerative diseases, which include Parkinson’s disease (PD) and progressive supranuclear palsy (PSP), and referred to as the ‘parkinsonian syndromes’. Although primarily a neurological disorder, patients with MSA may also develop visual signs and symptoms that could be useful in differential diagnosis. In addition, the eye-care practitioner may contribute to the management of visual problems of MSA patients and therefore, help to improve quality of life. This second article in the series considers the visual signs and symptoms of MSA with special reference to those features most useful in differential diagnosis of the parkinsonian syndromes.

Clinical decision support system for point of care use: ontology driven design and software implementation

OBJECTIVES: The objective of this research was to design a clinical decision support system (CDSS) that supports heterogeneous clinical decision problems and runs on multiple computing platforms. Meeting this objective required a novel design to create an extendable and easy to maintain clinical CDSS for point of care support. The proposed solution was evaluated in a proof of concept implementation. METHODS: Based on our earlier research with the design of a mobile CDSS for emergency triage we used ontology-driven design to represent essential components of a CDSS. Models of clinical decision problems were derived from the ontology and they were processed into executable applications during runtime. This allowed scaling applications' functionality to the capabilities of computing platforms. A prototype of the system was implemented using the extended client-server architecture and Web services to distribute the functions of the system and to make it operational in limited connectivity conditions. RESULTS: The proposed design provided a common framework that facilitated development of diversified clinical applications running seamlessly on a variety of computing platforms. It was prototyped for two clinical decision problems and settings (triage of acute pain in the emergency department and postoperative management of radical prostatectomy on the hospital ward) and implemented on two computing platforms-desktop and handheld computers. CONCLUSIONS: The requirement of the CDSS heterogeneity was satisfied with ontology-driven design. Processing of application models described with the help of ontological models allowed having a complex system running on multiple computing platforms with different capabilities. Finally, separation of models and runtime components contributed to improved extensibility and maintainability of the system.

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 analysis of users' reactions to an expert advisory system

Ignorance of user factors can be seen as one of the nontechnical issues contributing to expert system failure. An expert advisory system is built for nonexpert users; the users' acceptance is a very important factor for its successful implementation. If an expert advisory system satisfactorily represents the expertise in the domain, there still remains the question: "Will the end-users use the system?" This paper aims to address users' issues by analysing their reactions towards an expert advisory system called ADGAME, developed to help its users make better decisions in playing a competitive business game. Two experiments with ADGAME have been carried out. The research results show that, when the use of the expert advisory system is optional, there is considerable reluctance to use it, particularly amongst the "worst" potential users. Users also doubt the potential benefits in terms of improved learning and confidence in decisions made. Strangely, the one positive expectation that users had, that the system would save them time, proved not to be the case in practice; ADGAME appears to improve the users' effectiveness rather than their efficiency. © 1995.

Decision support system for vendor managed inventory supply chain:a case study

Vendor-managed inventory (VMI) is a widely used collaborative inventory management policy in which manufacturers manages the inventory of retailers and takes responsibility for making decisions related to the timing and extent of inventory replenishment. VMI partnerships help organisations to reduce demand variability, inventory holding and distribution costs. This study provides empirical evidence that significant economic benefits can be achieved with the use of a genetic algorithm (GA)-based decision support system (DSS) in a VMI supply chain. A two-stage serial supply chain in which retailers and their supplier are operating VMI in an uncertain demand environment is studied. Performance was measured in terms of cost, profit, stockouts and service levels. The results generated from GA-based model were compared to traditional alternatives. The study found that the GA-based approach outperformed traditional methods and its use can be economically justified in small- and medium-sized enterprises (SMEs).

Integrating service user and practitioner expertise within a web-based system for collaborative mental-health risk and safety management

Objectives: To develop a decision support system (DSS), myGRaCE, that integrates service user (SU) and practitioner expertise about mental health and associated risks of suicide, self-harm, harm to others, self-neglect, and vulnerability. The intention is to help SUs assess and manage their own mental health collaboratively with practitioners. Methods: An iterative process involving interviews, focus groups, and agile software development with 115 SUs, to elicit and implement myGRaCE requirements. Results: Findings highlight shared understanding of mental health risk between SUs and practitioners that can be integrated within a single model. However, important differences were revealed in SUs' preferred process of assessing risks and safety, which are reflected in the distinctive interface, navigation, tool functionality and language developed for myGRaCE. A challenge was how to provide flexible access without overwhelming and confusing users. Conclusion: The methods show that practitioner expertise can be reformulated in a format that simultaneously captures SU expertise, to provide a tool highly valued by SUs. A stepped process adds necessary structure to the assessment, each step with its own feedback and guidance. Practice Implications: The GRiST web-based DSS (www.egrist.org) links and integrates myGRaCE self-assessments with GRiST practitioner assessments for supporting collaborative and self-managed healthcare.

High resolution demodulation platform for large capacity hybrid WDM/FDM microstructures sensing system assisted by tunable FP filter

In this paper we proposed a demodulation scheme based on tunable FP filter for the WDM/FDM sensing system of the microstructure mentioned in the previous work. Simulation is done to prove the feasibility of demodulating the microstructure with the tunable FP filter. The experiments result showed high consistence with the simulation. And with the help of the high speed FPGA module and a high resolution AD/DA card, the system has achieved a very high resolution, up to 2.5 pm, and wavelength ranges 1520nm to 1590 nm.

Modulating membership grades to gain consensus for fuzzy set uncertainty values in a clinical decision support system

This paper deals with a very important issue in any knowledge engineering discipline: the accurate representation and modelling of real life data and its processing by human experts. The work is applied to the GRiST Mental Health Risk Screening Tool for assessing risks associated with mental-health problems. The complexity of risk data and the wide variations in clinicians' expert opinions make it difficult to elicit representations of uncertainty that are an accurate and meaningful consensus. It requires integrating each expert's estimation of a continuous distribution of uncertainty across a range of values. This paper describes an algorithm that generates a consensual distribution at the same time as measuring the consistency of inputs. Hence it provides a measure of the confidence in the particular data item's risk contribution at the input stage and can help give an indication of the quality of subsequent risk predictions. © 2010 IEEE.