Haul Truck Production and Maintenance Data modelling of Traditional, Autonomous and Operator Assist Scenarios

传统、自主和操作员辅助场景的运输卡车生产和维护数据建模

• 批准号: RGPIN-2018-05885
• 负责人: Hall, Robert
• 金额: $ 1.89万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=652856
• 关键词: Haul; Truck; Production; Maintenance; Data

Through recent interactions with various mining companies, equipment suppliers, and researchers it has become apparent the industry is about to be faced with how to ensure it capitalizes on the rapid digitalization currently occurring. Gosine and Warrian (2017) offer this description of digitalization***Disruptive digital technologies, including advanced robotics, artificial intelligence, mobile computing, internet of things (IoT), and autonomous and near-autonomous vehicles, were assessed to be among the top 12 emerging technologies that are expected to transform peoples' lives and the nature of work (Manyika, Chui, Bughin, Dobbs, Bisson, & Marrs, 2013). Variously referred to as digitalization, Industry 4.0, and the Fourth Industrial Revolution, such technologies will likely be ubiquitous, with applications across industrial and consumer markets (BDC, 2017). ***The Mining Industry will be very different 10 years from now than it is today. There will be equipment operating autonomously, as well as tele-operated. They will be communication with each other and making decisions in real time to optimize production while enhancing safety and reducing costs. Some are projecting that the process plant and equipment will be communicating about ore quality needed, required tonnages etc. (GMSG Workshop, 2017).******Depending on the size and life of a particular mine various levels of digitization will be required. The current emerging digitalization technology for Canadian mining operations is autonomous haulage (AHS). However, it not known how this technology will affect how the industry evolves, nor what are the key challenges for wide scale implementation of it. This proposal will present a research program for addressing the unknowns around autonomous haulage as well as looking at the larger implications of digitalization and creating a research pathway for the appropriate and successful integration of emerging/evolving technologies into the industry.******This research will create knowledge around the cost benefits of digitalization of the mining industry and provide a platform for assessing the appropriate level of digitalization to be used based on commodity type, price and size of the mining operation. It will assist in quantifying the real benefits of digitalization and allow the Canadian mining industry to maintain its strong leadership role on the world stage. ***The work on AHS will result in a reduction in greenhouse gasses and lower environmental foot print. The lessons learned in traffic management and mixed fleet operations will create knowledge to support future automation in no-urban environments for potential automated vehicles such as delivery trucks, or ambulances for example. As well, the mining industry the results will be applicable to evolving automation in forestry and agriculture.

通过最近与各种矿业公司，设备供应商和研究人员进行的互动，显然，该行业将面临如何确保其利用当前发生的快速数字化。 Gosine and Warrian（2017）提供了数字化的描述***颠覆性数字技术，包括高级机器人技术，人工智能，移动计算，物联网（IoT）以及自主和近自主工具，并评估了预计将改变人们的工作和birs ungun，Marrie＆marsui，fubin，brib unin，chusui of brib ungin，chusui，bersui，bribin，ubin，bungin，ubin，ubin，ubin，ubin，brib unin，ubin，ubin，ubin，ubin，ubin，ubin，brias unin，ubin，brias ungin＆mar uf， 2013）。这些技术将被称为数字化，工业4.0和第四工业革命，可能会无处不在，并在工业和消费市场之间进行了应用（BDC，2017年）。 ***采矿业将与今天的10年相比大不相同。 将有自主运行的设备以及电视操作。 他们将互相交流，并实时做出决定，以优化生产，同时提高安全性和降低成本。有些人预计过程工厂和设备将传达所需的矿石质量，所需的吨位等（GMSG Workshop，2017年）。******根据特定矿山的规模和寿命，需要各种数字化。 当前针对加拿大采矿业务的新兴数字化技术是自主拖运（AHS）。但是，它不知道该技术将如何影响行业的发展方式，也不知道大规模实施的主要挑战是什么。 该建议将介绍一项研究计划，以解决围绕自主拖运的未知数，并研究数字化的更大含义，并为将新兴/不断发展的技术的适当整合到该行业中创建研究途径。 它将有助于量化数字化的真正好处，并允许加拿大采矿业在世界舞台上保持其强大的领导作用。 *** AHS的工作将导致温室气体减少和较低的环境脚印。在交通管理和混合车队运营中汲取的经验教训将创造知识，以支持潜在的自动化车辆（例如送货卡车）或救护车等潜在的自动化车辆的未来自动化。 同样，采矿业该结果将适用于在林业和农业中发展自动化。