课题基金 / 基金详情

Optimization of systems life-cycle performance

Optimization of systems life-cycle performance
系统生命周期性能优化
批准号:
356664-2008
负责人:
Diallo, Claver
金额:
$1.24万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2010
资助国家:
加拿大
项目状态:
已结题
起止时间:
2010-01-01 至 2011-12-31

项目摘要

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中文摘要
翻译
这项研究计划关注系统在其生命周期中的性能分析和优化:从设计阶段到恢复和重用阶段。在竞争加剧和合理化的背景下,业绩收益可以确保竞争力、盈利能力和增加客户服务。具体地说,本研究计划侧重于在环境友好的背景下对随机故障系统的性能进行建模和优化。系统性能的定义和评估是以下几个指标的一个或组合:可靠性、可用性、可维护性、能耗、质量等。这种性能受系统的设计、生产和组装过程、分配、运行环境、集成物流、维护等影响。因此,需要对系统进行建模,以确定降低其性能的主要因素,并为选择性能改进措施开发决策工具。研究行动将致力于确定业绩因素及其在生命周期不同阶段的评估。这应该有助于随后对系统行为进行分析和建模。本研究计划由6个主要课题组成:1-绩效监测、评估和优化模型的开发。随机故障下多部件系统的可靠性和可用性建模。3-结合连接技术的最新发展的供应战略。4-结合使用新的和翻新的更换部件的维护策略。5.开发决策模型和工具,为退役系统选择最佳恢复方案。6--生命周期工程。
英文摘要
This research proposal is concerned with the analysis and optimization of systems performance over their life-cycle: from the design stage to the recovery and reuse stage. In a context of increased competition and rationalization, performance gains can ensure competitiveness, profitability and increase customer service. Particularly, this research program focuses on modeling and optimizing the performance for systems subjected to random failures in an environment-friendly context. Systems performance is defined and evaluated as one or the combination of several of the following indicators: reliability, availability, maintainability, energy consumption, quality, etc. This performance is affected by the system's design, production and assembly processes, distribution, operating environment, integrated logistics, maintenance, etc. It is therefore required to model the system in order to identify the main factors which reduce its performance and develop decision-tools for the selection of performance improvement actions. Research actions will be dedicated to defining the performance factors and their assessment at different stages in the life-cycle. Which should, subsequently, help analyzing and modeling the system behavior. This research program consists of 6 main topics: 1-Development of performance monitoring, assessment and optimization models. 2- Reliability and availability modeling for multi-components systems subjected to random failures. 3-Provisioning strategies integrating the recent development of connective technologies. 4- Maintenance strategies combining the use of new and reconditioned replacement parts. 5- Development of decision-making models and tools for the selection of optimal recovery options for retired systems. 6- Life Cycle Engineering.
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