Integrated performance monitoring and assessment of heavy mobile equipment

大型、复杂、可移动的机器用于许多工业部门（采矿、建筑、林业、农业）。随着此类生产设备的尺寸和复杂性的增加，此类设备的可靠性和生产率变得更加关键。例如，大型移动矿机的运营成本每年可达数百万美元，维护成本可超过每年购买价格的25%，每年运营成本的55%以上。本研究项目的重点是整合监测这些机器的各种功能和子系统的各个方面，以便对其性能进行有意义和有用的评估，包括设备建模和仿真、可靠性分析、生产率分析、维修计划、生产计划、风险分析、本研究将建立在从大型运行设备获取相关信息（而不是原始数据）的既定技术基础上，以便结合故障事件和故障历史评估运行条件和运行历史。将发展处理和分析所获资料的技术，为综合生产力和可靠性估计以及包括生产计划和维修计划在内的整体规划提供基础。相关的嵌入式传感、计算和通信技术，无论是发达的还是新兴的，都将在大型生产设备中遇到的常见子系统的背景下进行评估，例如高压液压和结构元件。将研究操作条件的特征和操作员的影响。将制定解决操作条件和操作人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.