837 resultados para integrated-process model


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Executive Summary The objective of this report was to use the Sydney Opera House as a case study of the application of Building Information Modelling (BIM). The Sydney opera House is a complex, large building with very irregular building configuration, that makes it a challenging test. A number of key concerns are evident at SOH: • the building structure is complex, and building service systems - already the major cost of ongoing maintenance - are undergoing technology change, with new computer based services becoming increasingly important. • the current “documentation” of the facility is comprised of several independent systems, some overlapping and is inadequate to service current and future services required • the building has reached a milestone age in terms of the condition and maintainability of key public areas and service systems, functionality of spaces and longer term strategic management. • many business functions such as space or event management require up-to-date information of the facility that are currently inadequately delivered, expensive and time consuming to update and deliver to customers. • major building upgrades are being planned that will put considerable strain on existing Facilities Portfolio services, and their capacity to manage them effectively While some of these concerns are unique to the House, many will be common to larger commercial and institutional portfolios. The work described here supported a complementary task which sought to identify if a building information model – an integrated building database – could be created, that would support asset & facility management functions (see Sydney Opera House – FM Exemplar Project, Report Number: 2005-001-C-4 Building Information Modelling for FM at Sydney Opera House), a business strategy that has been well demonstrated. The development of the BIMSS - Open Specification for BIM has been surprisingly straightforward. The lack of technical difficulties in converting the House’s existing conventions and standards to the new model based environment can be related to three key factors: • SOH Facilities Portfolio – the internal group responsible for asset and facility management - have already well established building and documentation policies in place. The setting and adherence to well thought out operational standards has been based on the need to create an environment that is understood by all users and that addresses the major business needs of the House. • The second factor is the nature of the IFC Model Specification used to define the BIM protocol. The IFC standard is based on building practice and nomenclature, widely used in the construction industries across the globe. For example the nomenclature of building parts – eg ifcWall, corresponds to our normal terminology, but extends the traditional drawing environment currently used for design and documentation. This demonstrates that the international IFC model accurately represents local practice for building data representation and management. • a BIM environment sets up opportunities for innovative processes that can exploit the rich data in the model and improve services and functions for the House: for example several high-level processes have been identified that could benefit from standardized Building Information Models such as maintenance processes using engineering data, business processes using scheduling, venue access, security data and benchmarking processes using building performance data. The new technology matches business needs for current and new services. The adoption of IFC compliant applications opens the way forward for shared building model collaboration and new processes, a significant new focus of the BIM standards. In summary, SOH current building standards have been successfully drafted for a BIM environment and are confidently expected to be fully developed when BIM is adopted operationally by SOH. These BIM standards and their application to the Opera House are intended as a template for other organisations to adopt for the own procurement and facility management activities. Appendices provide an overview of the IFC Integrated Object Model and an understanding IFC Model Data.

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Australian and international governments are increasingly adopting social marketing as a social change management tool to deal with complex social problems. Government decision makers typically need to balance the use of business models and management theories whilst maintaining the integrity of government policy. In taking this approach, decision makers experience management tensions between a social mission to equitably deliver social services and the accountability and affordability of providing quality social and health services to citizens. This is a significant challenge as the nature of the ‘social product’ in government is often more service-oriented than goods-based. In this paper the authors examine value creation in government social marketing services. The contribution of this paper is a value creation process model, which considers the nature of governments to create social good. This is particularly important for governments where consumers still expect value and quality in the service delivered, despite that offering being ‘free’.

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This paper explores the possibility of including human factoring in a business process model. The importance of doing so is twofold: (1) The organization becomes transparent in its processes as all participants (human, activities and events) are identifiable. (2) Including human factoring allows organizations to hire accordingly to the process needs. (3) Human factoring alleviates the current work related stress that is being encountered. (4) Enable quicker transition for newer employees into job scope. This was made possible by including a human behaviour layer in between pools within a process to depict human behaviour and feeling. Future work includes having a human thought symbol and a human interaction symbol included into the Business Process Modelling Notation (BPMN).

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Industrial applications of the simulated-moving-bed (SMB) chromatographic technology have brought an emergent demand to improve the SMB process operation for higher efficiency and better robustness. Improved process modelling and more-efficient model computation will pave a path to meet this demand. However, the SMB unit operation exhibits complex dynamics, leading to challenges in SMB process modelling and model computation. One of the significant problems is how to quickly obtain the steady state of an SMB process model, as process metrics at the steady state are critical for process design and real-time control. The conventional computation method, which solves the process model cycle by cycle and takes the solution only when a cyclic steady state is reached after a certain number of switching, is computationally expensive. Adopting the concept of quasi-envelope (QE), this work treats the SMB operation as a pseudo-oscillatory process because of its large number of continuous switching. Then, an innovative QE computation scheme is developed to quickly obtain the steady state solution of an SMB model for any arbitrary initial condition. The QE computation scheme allows larger steps to be taken for predicting the slow change of the starting state within each switching. Incorporating with the wavelet-based technique, this scheme is demonstrated to be effective and efficient for an SMB sugar separation process. Moreover, investigations are also carried out on when the computation scheme should be activated and how the convergence of the scheme is affected by a variable stepsize.

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Though web services offer unique opportunities for the design of new business processes, the assessment of the potential impact of Web services on existing business information systems is often reduced to technical aspects. This paper proposes a four-phase methodology which facilitates the evaluation of the potential use of Web services on business information systems both from a technical and from a strategic viewpoint. It is based on business process models, which are used to frame the adoption and deployment of Web services and to assess their impact on existing business processes. The application of this methodology is described using a procurement scenario.

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Web services are software components designed to support interoperable machine-to-machine interactions over a network, through the exchange of SOAP messages. Since the underlying technology is independent of any specific programming language, Web Services can be effectively used to interconnect business processes across different organizations. However, a standard way of representing such interconnections has not yet emerged and is the subject of an ongoing debate.

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We estimate the parameters of a stochastic process model for a macroparasite population within a host using approximate Bayesian computation (ABC). The immunity of the host is an unobserved model variable and only mature macroparasites at sacrifice of the host are counted. With very limited data, process rates are inferred reasonably precisely. Modeling involves a three variable Markov process for which the observed data likelihood is computationally intractable. ABC methods are particularly useful when the likelihood is analytically or computationally intractable. The ABC algorithm we present is based on sequential Monte Carlo, is adaptive in nature, and overcomes some drawbacks of previous approaches to ABC. The algorithm is validated on a test example involving simulated data from an autologistic model before being used to infer parameters of the Markov process model for experimental data. The fitted model explains the observed extra-binomial variation in terms of a zero-one immunity variable, which has a short-lived presence in the host.

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In recent years several scientific Workflow Management Systems (WfMSs) have been developed with the aim to automate large scale scientific experiments. As yet, many offerings have been developed, but none of them has been promoted as an accepted standard. In this paper we propose a pattern-based evaluation of three among the most widely used scientific WfMSs: Kepler, Taverna and Triana. The aim is to compare them with traditional business WfMSs, emphasizing the strengths and deficiencies of both systems. Moreover, a set of new patterns is defined from the analysis of the three considered systems.

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"This column is distinguished from previous Impact columns in that it concerns the development tightrope between research and commercial take-up and the role of the LGPL in an open source workflow toolkit produced in a University environment. Many ubiquitous systems have followed this route, (Apache, BSD Unix, ...), and the lessons this Service Oriented Architecture produces cast yet more light on how software diffuses out to impact us all." Michiel van Genuchten and Les Hatton Workflow management systems support the design, execution and analysis of business processes. A workflow management system needs to guarantee that work is conducted at the right time, by the right person or software application, through the execution of a workflow process model. Traditionally, there has been a lack of broad support for a workflow modeling standard. Standardization efforts proposed by the Workflow Management Coalition in the late nineties suffered from limited support for routing constructs. In fact, as later demonstrated by the Workflow Patterns Initiative (www.workflowpatterns.com), a much wider range of constructs is required when modeling realistic workflows in practice. YAWL (Yet Another Workflow Language) is a workflow language that was developed to show that comprehensive support for the workflow patterns is achievable. Soon after its inception in 2002, a prototype system was built to demonstrate that it was possible to have a system support such a complex language. From that initial prototype, YAWL has grown into a fully-fledged, open source workflow management system and support environment

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This exhibition engages with one of the key issues facing the fashion textiles industry in terms of future sustainability: that of the well being of fashion industry workers in Australia and New Zealand (people). This collection formed the basis of my honours dissertation (completed in New Zealand in 2008) which examines the contribution that design can make to sustainable manufacturing; particularly design for local production and consumption. An important aspect this work is the discussion of source, the work suggests that the made in China syndrome (in reference to the current state of over-consumerism in Australia and New Zealand) could be bought to a close through design to minimize waste and maximize opportunity for ‘people’: in this case both garment workers and the SMEs that employ them. The garments reflect the possibilities of focusing on a local approach that could be put into practice by a framework of SMEs that already exist. In addition the design process is highly transferrable and could be put into practice almost anywhere with minimal set up costs and a design ethos that progresses at the same pace as the skills of workers. This collection is a physical and conceptual embodiment of a source local/make local/sell local approach. The collection is an example of design that demonstrates that this is not an unrealistic ideal and is in fact possible through the development of a sustainable industry, in the sense of people, profit and planet, through adoption of a design process model that stops the waste at the source, by making better use of the raw materials and labour involved in making fashion garments. Although the focus of this research appears to centre on people and profit, this kind of source local/make local/sell local approach also has great benefits in terms of environmental sustainability.

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Plant biosecurity requires statistical tools to interpret field surveillance data in order to manage pest incursions that threaten crop production and trade. Ultimately, management decisions need to be based on the probability that an area is infested or free of a pest. Current informal approaches to delimiting pest extent rely upon expert ecological interpretation of presence / absence data over space and time. Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis. Markov chain Monte Carlo simulation is used to estimate the probable extent of pests, given the observation and process model conditioned by surveillance data. Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. The model suggests that typical early detection programs provide a moderate reduction in the probability of an area being infested but a dramatic reduction in the expected area of incursions at a given time. Estimates of spiralling whitefly extent are examined at local, district and state-wide scales. The local model estimates the rate of natural spread and the influence of host architecture, host suitability and inspector efficiency. These parameter estimates can support the development of robust surveillance programs. Hierarchical Bayesian models for the human-mediated spread of spiralling whitefly are developed for the colonisation of discrete cells connected by a modified gravity model. By estimating dispersal parameters, the model can be used to predict the extent of the pest over time. An extended model predicts the climate restricted distribution of the pest in Queensland. These novel human-mediated movement models are well suited to demonstrating area freedom at coarse spatio-temporal scales. At finer scales, and in the presence of ecological complexity, exploratory models are developed to investigate the capacity for surveillance information to estimate the extent of red banded mango caterpillar. It is apparent that excessive uncertainty about observation and ecological parameters can impose limits on inference at the scales required for effective management of response programs. The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities. Hierarchical Bayesian modelling is demonstrated as both a useful analytical tool for estimating pest extent and a natural investigative paradigm for developing and focussing biosecurity programs.

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This article examined the relationship between time structure and Macan's process model of time management. This study proposed that time structure—‘appraisal of effective time usage’—would be a more parsimonious mediator than perceived control over time in the relationship between time management behaviours and outcome variables, such as job satisfaction and psychological well-being. Alternative structure models were compared using a sample of 111 university students. Model 1 tested Macan's process model of time management with perceived control over time as the mediator. Model 2 replaced perceived control over time by the construct of time structure. Model 3 examined the possibility of perceived control over time and time structure as being parallel mediators of the relationships between time management and outcomes. Results of this study showed that Model 1 and Model 2 fitted the data equally well. On the other hand, the mediated effects were small and partial in both models. This pattern of results calls for reassessment of the process model.

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This paper proposes a novel approach for identifying risks in executable business processes and detecting them at run time. The approach considers risks in all phases of the business process management lifecycle, and is realized via a distributed, sensor-based architecture. At design-time, sensors are defined to specify risk conditions which when fulfilled, are a likely indicator of faults to occur. Both historical and current execution data can be used to compose such conditions. At run-time, each sensor independently notifies a sensor manager when a risk is detected. In turn, the sensor manager interacts with the monitoring component of a process automation suite to prompt the results to the user who may take remedial actions. The proposed architecture has been implemented in the YAWL system and its performance has been evaluated in practice.