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Simulation-based analytics for industrial construction

Simulation-based analytics for industrial construction
基于仿真的工业建筑分析
批准号:
492657-2015
负责人:
AbouRizk, Simaan
金额:
$13.11万
依托单位:
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2016
资助国家:
加拿大
项目状态:
已结题
起止时间:
2016-01-01 至 2017-12-31

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中文摘要
翻译
艾伯塔省的工业建筑部门面临许多挑战,尤其是最近全球资源定价压力(Lewis&Jones,2015)。在这种情况下,该部门需要提高其竞争力,特别是通过改善安全、质量和生产率,以及解决供应网络中的低效问题。工业建筑项目的管理主要依赖建筑专业人员的知识和经验(Manyika等人,2011年),并支持企业资源规划(ERP)系统。工业建筑公司和大多数制造公司一样,“没有很好地利用所有生成和收集的数据来提高生产系统的效率”(Dean,2014)。他们很难管理、分析数据并将其转换为有用的信息,以改进决策以提高竞争力。我们的目标是引入新一代量化驱动的分析系统,该系统利用收集的数据,并实时动态地被模拟模型取代,以加强对建筑生产过程的管理。我们建议的研究方法将建立在我们在模拟方面的学术实力和工业合作伙伴的知识基础上。具体地说,拟议的研究旨在开发一个基于模拟的建筑分析(SAC)框架,以支持新一代决策支持系统(DSS),开发模拟环境以部署该框架,并通过与工业合作伙伴在工业部门、在生产率、安全和质量管理领域以及在工业建筑供应链分析中的一系列实施来证明其有效性。
英文摘要
The industrial construction sector in Alberta faces numerous challenges, in particular stemming from recent global pressures on resource pricing (Lewis & Jones, 2015). Under this circumstance, the sector needs to enhance its competitiveness especially through improvements related to safety, quality, and productivity, as well as resolving inefficiencies in the supply network. Industrial construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals (Manyika et al., 2011), and supporting enterprise resource planning (ERP) systems. Industrial construction companies, like most manufacturing companies, "do not make good use of all the generated and collected data to improve production system efficiency" (Dean, 2014). They struggle to manage, analyze, and transform data into useful information for improved decision making to improve their competitiveness. Our goal is to introduce a new generation of quantitatively-driven analytics systems that make use of collected data, and are dynamically supplanted with simulation models in real time to enhance the management of the construction production process. Our proposed research approach will build upon our academic strength in simulation and the knowledge of the industrial partners. Specifically, the proposed research aims to develop a simulation-based analytics for construction (SAC) framework to support a new generation of decision support systems (DSS), develop the simulation environment to deploy the framework, and demonstrate its validity through a number of implementations in the industrial sector with industrial partners, in the areas of productivity, safety and quality management, and in the analysis of the industrial construction supply chain.
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