8 resultados para integrated coastal zone management

em Aston University Research Archive


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Integrated vehicle health management (IVHM) is a collection of data relevant to the present and future performance of a vehicle system and its transformation into information can be used to support operational decisions. This design and operation concept embraces an integration of sensors, communication technologies, and artificial intelligence to provide vehicle-wide abilities to diagnose problems and recommend solutions. This article aims to report the state-of-the-art of IVHM research by presenting a systematic review of the literature. The literature from different sources is collated and analysed, and the major emerging themes are presented. On this basis, the article describes the IVHM concept and its evolution, discusses configurations and existing applications along with main drivers, potential benefits and barriers to adoption, summarizes design guidelines and available methods, and identifies future research challenges.

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Cranfield University in collaboration with The Boeing Company have set up a Centre of Excellence in IVHM on the University?s technology park. Sponsored by the East of England Development Agency (EEDA), the Centre carries out pre-competitive research and development of IVHM technologies for the benefit of industrial partners. In addition, the dedicated facilities and university staff provide an unparalleled educational environment for learning and applying IVHM technologies. Boeing is actively involved in the creation and work of the Centre through its enterprise-wide Phantom Works technology organization. This paper will describe the organisation and operation of the Centre and will illustrate its activities by describing a research project being carried out in the Centre. This project is a demonstration of an end to end IVHM system beginning with cost/benefit analysis and extending to maintenance, logistics and operations decision support.

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In supply chain management literature, there has been little empirical research investigation on purchasing consortium issues focusing on a detailed analysis of information and communication (ICT) based procurement strategies. Based on the exploration of academic literature and two surveys among purchasing organisations as well as e-Marketplaces / procurement service providers (PSPs) in the automotive and electronics industry sectors, the research methodology follows a positivistic approach in order to assess the overall statement: ‘Effective participation in electronic purchasing consortia (EPC) can have the potential to enhance competitive advantage. Implementation therefore requires a clear and detailed understanding of the major process structures and drivers, based upon thetechnology-organisation-environment framework.’ Key factors and structures that affect the adoption and diffusion of EPC and the performance impact of adoption are investigated. The empirically derived model for EPC can be a valuable starting point to EPC research.

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This paper describes how dimensional variation management could be integrated throughout design, manufacture and verification, to improve quality while reducing cycle times and manufacturing cost in the Digital Factory environment. Initially variation analysis is used to optimize tolerances during product and tooling design and also results in the creation of a simplified representation of product key characteristics. This simplified representation can then be used to carry out measurability analysis and process simulation. The link established between the variation analysis model and measurement processes can subsequently be used throughout the production process to automatically update the variation analysis model in real time with measurement data. This ‘live’ simulation of variation during manufacture will allow early detection of quality issues and facilitate autonomous measurement assisted processes such as predictive shimming. A study is described showing how these principles can be demonstrated using commercially available software combined with a number of prototype applications operating as discrete modules. The commercially available modules include Catia/Delmia for product and process design, 3DCS for variation analysis and Spatial Analyzer for measurement simulation. Prototype modules are used to carry out measurability analysis and instrument selection. Realizing the full potential of Metrology in the Digital Factory will require that these modules are integrated and software architecture to facilitate this is described. Crucially this integration must facilitate the use of realtime metrology data describing the emerging assembly to update the digital model.

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The Indian Petroleum Industry is passing through a very dynamic business environment due to liberalization. Effective project management for developing new infrastructures and maintaining the existing facilities has been considered as one of the means for remaining competitive but these practices suffer from many shortcomings, as time, cost and quality non-achievements are part and parcel of almost every project. This study focuses on identifying the specific causes of project failure by demonstrating first the characteristics of projects in Indian Petroleum industry and suggests some remedial measures for resolving these issues. The suggested project management model is integrated through information management system and demonstrated through a case study.

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In Great Britain and Brazil healthcare is free at the point of delivery and based study only on citizenship. However, the British NHS is fifty-five years old and has undergone extensive reforms. The Brazilian SUS is barely fifteen years old. This research investigated the middle management mediation role within hospitals comparing managerial planning and control using cost information in Great Britain and Brazil. This investigation was conducted in two stages entailing quantitative and qualitative techniques. The first stage was a survey involving managers of 26 NHS Trusts in Great Britain and 22 public hospitals in Brazil. The second stage consisted of interviews, 10 in Great Britain and 22 in Brazil, conducted in four selected hospitals, two in each country. This research builds on the literature by investigating the interaction of contingency theory and modes of governance in a cross-national study in terms of public hospitals. It further builds on the existing literature by measuring managerial dimensions related to cost information usefulness. The project unveils the practice involved in planning and control processes. It highlights important elements such as the use of predictive models and uncertainty reduction when planning. It uncovers the different mechanisms employed on control processes. It also depicts that planning and control within British hospitals are structured procedures and guided by overall goals. In contrast, planning and control processes in Brazilian hospitals are accidental, involving more ad hoc actions and a profusion of goals. The clinicians in British hospitals have been integrated into the management hierarchy. Their use of cost information in planning and control processes reflects this integration. However, in Brazil, clinicians have been shown to operate more independently and make little use of cost information but the potential signalled for cost information use is seen to be even greater than that of their British counterparts.

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This paper presents for the first time the concept of measurement assisted assembly (MAA) and outlines the research priorities of the realisation of this concept in the industry. MAA denotes a paradigm shift in assembly for high value and complex products and encompasses the development and use of novel metrology processes for the holistic integration and capability enhancement of key assembly and ancillary processes. A complete framework for MAA is detailed showing how this can facilitate a step change in assembly process capability and efficiency for large and complex products, such as airframes, where traditional assembly processes exhibit the requirement for rectification and rework, use inflexible tooling and are largely manual, resulting in cost and cycle time pressures. The concept of MAA encompasses a range of innovativemeasurement- assisted processes which enable rapid partto- part assembly, increased use of flexible automation, traceable quality assurance and control, reduced structure weight and improved levels of precision across the dimensional scales. A full scale industrial trial of MAA technologies has been carried out on an experimental aircraft wing demonstrating the viability of the approach while studies within 140 smaller companies have highlighted the need for better adoption of existing process capability and quality control standards. The identified research priorities for MAA include the development of both frameless and tooling embedded automated metrology networks. Other research priorities relate to the development of integrated dimensional variation management, thermal compensation algorithms as well as measurement planning and inspection of algorithms linking design to measurement and process planning. © Springer-Verlag London 2013.

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In the Light Controlled Factory part-to-part assembly and reduced weight will be enabled through the use of predictive fitting processes; low cost high accuracy reconfigurable tooling will be made possible by active compensation; improved control will allow accurate robotic machining; and quality will be improved through the use of traceable uncertainty based quality control throughout the production system. A number of challenges must be overcome before this vision will be realized; 1) controlling industrial robots for accurate machining; 2) compensation of measurements for thermal expansion; 3) Compensation of measurements for refractive index changes; 4) development of Embedded Metrology Tooling for in-tooling measurement and active tooling compensation; and 5) development of Software for the Planning and Control of Integrated Metrology Networks based on Quality Control with Uncertainty Evaluation and control systems for predictive processes. This paper describes how these challenges are being addressed, in particular the central challenge of developing large volume measurement process models within an integrated dimensional variation management (IDVM) system.