Optimal maintenance planning for critical mining and energy infrastructure

关键采矿和能源基础设施的最佳维护计划

• 批准号: FT170100120
• 负责人: Prof Ryan Loxton
• 金额: $ 63.73万
• 依托单位: Curtin University
• 依托单位国家: 澳大利亚
• 项目类别: ARC Future Fellowships
• 财政年份: 2018
• 资助国家: 澳大利亚
• 起止时间: 2018-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/FT170100120
• 关键词: Optimal; maintenance; planning; critical; mining

This project aims to develop cutting-edge mathematical algorithms for optimising maintenance activities in the mining and energy sectors. Such maintenance activities are prone to budget and time overruns due to poor planning - the result of outdated, inefficient manual processes. The project is expected to result in new maintenance planning methods, underpinned by rigorous mathematical theory, for reducing manual intervention and optimising both short- and long-term maintenance based on real-time sensor data. These new methods will be powerful tools for tackling the complexity of large-scale, time-critical maintenance projects, driving productivity in the resources industry and fostering collaboration between mathematicians and engineers.

该项目旨在开发先进的数学算法，以优化采矿和能源部门的维护活动。由于计划不佳，此类维护活动容易造成预算和时间超支——这是过时的、低效的手工流程的结果。该项目预计将产生新的维护计划方法，以严格的数学理论为基础，减少人工干预，并根据实时传感器数据优化短期和长期维护。这些新方法将成为解决大规模、时间紧迫的复杂维护项目的强大工具，推动资源行业的生产力，促进数学家和工程师之间的合作。