This paper discusses the design and deployment of low-cost Internet of Things (IoT) in medium-scale open pit mines to optimise the performance of their mining small-scale trucks and surface mining shovels. Low-cost IoT can be implemented in medium-scale operations to automate the collection of process management information that is currently measured manually, replicating part of the results delivered by commercial Fleet Management Systems (FMSs) such as the calculations of the number of truck cycles per shift, the shovel loading time, truck and shovel positioning, tonnes moved per day, truck speed and average fleet efficiency. The process of developing mining benches can also be monitored.

By monitoring these tasks, FMSs in the mining industry allow mine operators to maximise productivity, reduce the number of equipment required to accomplish production targets, minimise material re-handling, supply the plant as planned and meet ore blending objectives for better metallurgical recoveries. In the case of large-scale mines, these mining operations are prepared to invest in the high cost of a typical FMS (of the order of $100,000/month depending on fleet size) because they enable mine operators to ensure that their capital-intensive fleets operate at peak productivity, generating maximum return on investment. By contrast, many medium-scale mines cannot afford the installation and ongoing costs associated with a commercial FMS. Medium-scale mines typically have low capitalization, rented mining fleet and are run on a day-to-day basis, with staff being employed or laid off on an almost continuous basis.

The emergence of low-cost IoT promises widespread and access to sensors and data that can be used for operational decision-making. This paper presents a trial of a low-cost, under $100, IoT-based Fleet Information System (FIS). The system does not attempt to replicate the functionality of a full FMS but delivers key management information to the mine operators while having low capital and running costs and no requirement for IT or technical skills for installation or maintenance.

In a test case in Chile, the FIS was used to inform operational management changes that resulted in a reduction of loading time, optimisation of mining truck routes and truck speed control for better safety without an increase in the mining cost.

The low cost of the solution allows medium-scale mines access to tools that can enable them to mirror the performance improvements of their bigger competitors. For medium-scale mines, that means longer life-of-mine, more local employment and a longer positive impact in the community.

本文讨论了在中型露天矿中设计和部署低成本物联网 (IoT) 以优化其采矿小型卡车和露天矿铲的性能。可以在中等规模运营中实施低成本物联网，以自动收集目前手动测量的流程管理信息，复制商业车队管理系统 (FMS) 提供的部分结果，例如卡车循环次数的计算每个班次、铲子装载时间、卡车和铲子定位、每天移动的吨数、卡车速度和平均车队效率。还可以监控开发采矿台的过程。

通过监控这些任务，采矿业中的 FMS 使矿山经营者能够最大限度地提高生产力，减少实现生产目标所需的设备数量，最大限度地减少材料重​​新处理，按计划供应工厂并满足矿石混合目标，以实现更好的冶金回收。在大型矿山的情况下，这些采矿作业准备投资于典型 FMS 的高成本（大约 100,000 美元/月，取决于车队规模），因为它们使矿山运营商能够确保其资本密集型车队以最高生产力运作，产生最大的投资回报。相比之下，许多中型矿山无法负担与商业 FMS 相关的安装和持续成本。中等规模的矿场通常资本化程度较低，租用采矿车队并且日常运营，

低成本物联网的出现有望普及并访问可用于运营决策的传感器和数据。本文介绍了一种低成本、低于 100 美元、基于物联网的舰队信息系统 (FIS) 的试验。该系统不会尝试复制完整 FMS 的功能，而是向矿山运营商提供关键管理信息，同时具有较低的资本和运行成本，并且不需要 IT 或安装或维护技术技能。

在智利的一个测试案例中，FIS 用于通知运营管理变更，从而减少装载时间、优化矿用卡车路线和卡车速度控制，以在不增加采矿成本的情况下提高安全性。

该解决方案的低成本允许中型矿山使用工具，使他们能够反映更大竞争对手的性能改进。对于中型矿山而言，这意味着更长的矿山寿命、更多的当地就业以及对社区的更持久的积极影响。