Smart Manufacturing in Mining. Adopting Machine Learning to Improve a Copper Milling Process
- 1 Department of Industrial Engineering, Universidad Nacional de Lomas de Zamora, Ingeniería Industrial, Facultad de Ingeniería, Lomas de Zamora, Buenos Aires, Argentina
- 2 ETSII, Universidad Rey Juan Carlos, Móstoles, Madrid, Spain
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.
Copyright: © 2023 Federico Walas Mateo, Andrés Redchuk and Julian Eloy Tornillo. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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- Lean Startup Methodology
- Smart Production
- Low Code Solution
- UN SDG
- Industry 5.0