Smart Manufacturing in Mining. Adopting Machine Learning to Improve a Copper Milling Process

Pub Date : 2023-01-01 DOI:10.3844/jmrsp.2023.42.47
Federico Walas Mateo, A. Redchuk, J. Tornillo
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Abstract

: Nowadays industries like mining are focused in the need of improving processes towards net zero emissions and accomplishing with united nations' sustainable development goals. This article presents a case at a copper mine where an artificial intelligence solution is adopted to optimize industrial processes. The paper illustrates the way a software solution using a low code platform framework can democratize the use of advanced analytical tools in the industrial sector to improve production processes. The low code approach is complemented by lean startup methodology to adapt the solution to the industrial domain and establish a co-creation environment among software engineers and industrial processes experts. This study pretends to highlight the use of industrial data and the way traditional industries are migrating towards the industry 5.0 paradigm, empowering people at the plant and achieving more environmentally friendly processes by the use of digital solutions.
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采矿中的智能制造。采用机器学习改进铜铣削工艺
如今,像采矿业这样的行业关注的是改进流程以实现净零排放和实现联合国的可持续发展目标。本文介绍了一个铜矿案例,其中采用人工智能解决方案来优化工业流程。本文说明了使用低代码平台框架的软件解决方案如何使工业部门先进分析工具的使用民主化,以改善生产过程。低代码方法与精益启动方法相辅相成,以使解决方案适应工业领域,并在软件工程师和工业过程专家之间建立共同创造的环境。本研究试图强调工业数据的使用以及传统工业向工业5.0范式迁移的方式,通过使用数字解决方案赋予工厂人员权力并实现更环保的流程。
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