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Mobile crane selection, modular rigging optimization and on-site utilization for heavy industrial projects

Mobile crane selection, modular rigging optimization and on-site utilization for heavy industrial projects
重工业项目的移动式起重机选型、模块化索具优化和现场利用
批准号:
461528-2013
负责人:
Bouferguene, Ahmed
金额:
$7.13万
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:
2015
资助国家:
加拿大
项目状态:
已结题
起止时间:
2015-01-01 至 2016-12-31

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中文摘要
翻译
加拿大是主要的能源生产国,石油储量位居世界第三,油砂生产是该国的主要经济驱动力。随着世界原油价格逐步上涨,艾伯塔省的石油公司正在扩大业务,投入数十亿美元用于新的生产、维护、维修和运营。由于油砂生产厂通常是拥挤的地区,新的组装作业需要在设备位置和操作方面仔细规划,以确保最佳生产率。就起重机而言,设计良好的操作包括选择、支撑系统设计、运动规划和3D验证。因此,这项研究的目的有三个;它建议(I)制定一种方法,以便能够有效地规划起重机的运行;(Ii)设计适当的支撑系统和创新的索具机构;以及(Iii)利用流体动力学原理分析风速和风向对起重机稳定性的影响。 研究的多学科性质将为来自行业合作伙伴的学生、教职员工和管理人员提供一个相互学习和合作实现研究目标的独特机会。该项目还为行业合作伙伴和石油行业的其他参与者提供了一个机会,让他们进一步了解项目的有效调度和管理。拟议研究的后续结果将作为(I)降低起重机故障风险;(Ii)改善起重机作业安全;(Iii)提高调度准确性;以及(Iv)提高起重机作业效率的基础。预计拟议研究的结果也将对加拿大社会产生积极影响。制定的预防设备故障的措施将降低停工或设备故障的可能性,并有助于优化重工业建筑工地的起重机利用率,从而显著节省成本。这项研究还旨在提高起重机作业的安全性和效率,同时减少排放。
英文摘要
Canada is a leading energy producer, with the third-largest oil reserves in the world, and oil sands production as a major economic driver for the country. With world crude oil prices gradually rising, oil companies in Alberta are expanding their operations, devoting billions of dollars toward new production, maintenance, repair, and operations. Because oil sands production plants are generally congested areas, new assembly operations need to be carefully planned with regards to equipment location and operation in order to ensure optimal productivity. In the case of cranes, a well-designed operation includes selection, support system design, motion planning, and 3D validation. The objective of the research is thus threefold; it proposes to (i) elaborate a methodology which enables efficient planning of crane operations; (ii) design an appropriate support system and an innovative rigging mechanism; and (iii) analyze the impact of wind speed and direction on crane stability using the principles of fluid dynamics. The multi-disciplinary nature of the research will provide a unique opportunity for students, faculty, and managerial staff from the industrial partner to learn from each other and collaborate to achieve the research goal. This project also provides an opportunity for the industry partner and other players in the oil industry to further their insight into efficient scheduling and management of projects. The ensuing findings of the proposed research will serve as a basis for (i) reducing the risk of crane failure; (ii) improving safety of crane operation; (iii) increasing scheduling accuracy; and (iv) improving the efficiency of crane operations. The outcomes of the proposed research are also expected to make a positive impact on Canadian society. The developed measures to prevent equipment failure will result in significant savings by reducing the likelihood of work stoppage or equipment failure, and by contributing to the optimization of crane utilization on heavy industrial construction sites. This research also seeks to improve the safety and efficiency of crane operations, while reducing emissions.
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Using machine learning-based automation process to improve the productivity of CCTV inspections of municipal drainage systems
  • 批准号:
    RGPIN-2020-05384
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.89万
  • 财政年份:
    2022
  • 负责人:
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  • 依托单位:
Using machine learning-based automation process to improve the productivity of CCTV inspections of municipal drainage systems
  • 批准号:
    RGPIN-2020-05384
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.89万
  • 财政年份:
    2021
  • 负责人:
    Bouferguene, Ahmed
  • 依托单位:
Crane operation assisted planning and optimization
  • 批准号:
    561098-2020
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $7.85万
  • 财政年份:
    2021
  • 负责人:
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  • 依托单位:
Design, selection, and management of modular crane rigging for heavy industrial projects
  • 批准号:
    518160-2017
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $7.3万
  • 财政年份:
    2020
  • 负责人:
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  • 依托单位:
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