Integrated performance monitoring and assessment of heavy mobile equipment

大型、复杂、可移动的机器被用于许多工业部门(采矿、建筑、林业、农业)。随着这种生产设备的尺寸和复杂性的增加，这种设备的可靠性和生产率变得更加关键。例如，一台大型移动采矿机的运营成本每年可能高达数百万美元，维护成本可能超过每年采购价格的25%，超过每年运营成本的55%。该研究项目侧重于集成监控这类机器中的各种功能和子系统的不同方面，以实现对其性能的有意义和有用的评估，涉及设备建模和仿真、可靠性分析、生产率分析、维护计划、生产计划、风险分析、运营管理。该研究将建立在从大型运营设备获取相关信息(而不是原始数据)的既定技术的基础上，以便结合故障事件和故障历史来评估运营条件和运营历史。将开发处理和分析所获得信息的技术，以便为综合生产率和可靠性估计以及包括生产规划和维护规划在内的全面规划提供基础。相关的嵌入式传感、计算和通信技术，无论是已开发的还是正在出现的，都将在大型生产设备中遇到的公共子系统的背景下进行评估，例如高压液压和结构元件。将调查操作条件和操作员影响的特征。将制定同时考虑操作条件和操作员影响的生产率和可靠性指标。

Large, complex, mobile machines are used in many industrial sectors (mining, construction, forestry, agriculture). As the size and complexity of such production equipment has increased, the reliability and productivity of such equipment has become even more critical. For example, operating costs on a large mobile mining machine can amount to several million dollars per year, and maintenance costs can exceed 25% per annum of purchase price, and over 55% per annum of operating cost. This research project focuses on integrating the diverse aspects of monitoring the various functions and subsystems in such machines, in order to achieve meaningful and useful assessments of their performance, with respect to Equipment Modelling and Simulation, Reliability Analysis, Productivity Analysis, Maintenance Planning, Production Planning, Risk Analysis, Operations Management This research will build on established techniques for acquiring relevant information (as opposed to raw data) from large operating equipment in order to evaluate operational conditions and operating histories in conjunction with failure events and failure histories. Techniques for processing and analyzing the acquired information will be developed, to provide a basis for integrated productivity and reliability estimates, as well as holistic planning encompassing both production planning and maintenance planning. Relevant embedded sensing, computing, and communications technologies, both developed and emerging, will be evaluated in the context of common subsystems encountered in large production equipment, e.g. high pressure hydraulics and structural elements. Characterization of operational conditions and operator influence will be investigated. Productivity and reliability metrics which address both operational conditions and operator influence will be formulated.