5 resultados para Project Quality

em Cambridge University Engineering Department Publications Database


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This report is a product of close industry-academia collaboration between British Aerospace and the Cambridge Engineering Design Centre (EDC). British Aerospace designs and integrates some of the most complex systems in the world, and its expertise in this field has enabled the company to become the United Kingdom's largest exporter. However, to stay at the forefront of the highly competitive aerospace industry it is necessary to seek new ways to work more effectively and more efficiently. The Cambridge EDC has played a part in supporting these needs by providing access to the methods and tools that it has developed for improving the process of designing mechanical systems. The EDC has gained an international reputation for the quality of its work in this subject. Thus, the collaboration is between two organisations each of whom are leaders in their respective fields. The central aim of the project has been to demonstrate how a systematic design process can be applied to a real design task identified by industry. The task selected was the design of a flight refuelling probe which would enable a combat aircraft to refuel from a "flying tanker". However, the systematic approach, methods and tools described in this report are applicable to most engineering design tasks. The findings presented in this report provide a sound basis for comparing the recommended systematic design process with industrial practice. The results of this comparison would enable the company to define ways in which its existing design process can be improved. This research project has a high degree of industrial relevance. The value of the work may be judged in terms of the opportunities it opens up for positive changes to the company's engineering operations. Several members of the EDC have contributed to the project. These include Dr Lucienne Blessing, Dr Stuart Burgess, Dr Amaresh Chakrabarti, Major Mark Nowack, Aylmer Johnson and Dr Paul Weaver. At British Aerospace special thanks must go to Alan Dean and David Halliday for their interest and the support they have given. The project has been managed by Dr Nigel Upton of British Aerospace during a 3 year secondment to the EDC.

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Water service providers (WSPs) in the UK have statutory obligations to supply drinking water to all customers that complies with increasingly stringent water quality regulations and minimum flow and pressure criteria. At the same time, the industry is required by regulators and investors to demonstrate increasing operational efficiency and to meet a wide range of performance criteria that are expected to improve year-on-year. Most WSPs have an ideal for improving the operation of their water supply systems based on increased knowledge and understanding of their assets and a shift to proactive management followed by steadily increasing degrees of system monitoring, automation and optimisation. The fundamental mission is, however, to ensure security of supply, with no interruptions and water quality of the highest standard at the tap. Unfortunately, advanced technologies required to fully understand, manage and automate water supply system operation either do not yet exist, are only partially evolved, or have not yet been reliably proven for live water distribution systems. It is this deficiency that the project NEPTUNE seeks to address by carrying out research into 3 main areas; these are: data and knowledge management; pressure management (including energy management); and the associated complex decision support systems on which to base interventions. The 3-year project started in April of 2007 and has already resulted in a number of research findings under the three main research priority areas (RPA). The paper summarises in greater detail the overall project objectives, the RPA activities and the areas of research innovation that are being undertaken in this major, UK collaborative study. Copyright 2009 ASCE.

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Choosing a project manager for a construction project—particularly, large projects—is a critical project decision. The selection process involves different criteria and should be in accordance with company policies and project specifications. Traditionally, potential candidates are interviewed and the most qualified are selected in compliance with company priorities and project conditions. Precise computing models that could take various candidates’ information into consideration and then pinpoint the most qualified person with a high degree of accuracy would be beneficial. On the basis of the opinions of experienced construction company managers, this paper, through presenting a fuzzy system, identifies the important criteria in selecting a project manager. The proposed fuzzy system is based on IF-THEN rules; a genetic algorithm improves the overall accuracy as well as the functions used by the fuzzy system to make initial estimates of the cluster centers for fuzzy c-means clustering. Moreover, a back-propagation neutral network method was used to train the system. The optimal measures of the inference parameters were identified by calculating the system’s output error and propagating this error within the system. After specifying the system parameters, the membership function parameters—which by means of clustering and projection were approximated—were tuned with the genetic algorithm. Results from this system in selecting project managers show its high capability in making high-quality personnel predictions