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DESIGN AND PROTOTYPING OF MINE MIND: A PRODUCT DEVELOPMENT APPROACH TO AI-DRIVEN MINING PERFORMANCE MANAGEMENT

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dc.contributor.author Simamora, Panji Anugrah
dc.date.accessioned 2026-02-25T06:01:12Z
dc.date.available 2026-02-25T06:01:12Z
dc.date.issued 2025
dc.identifier.uri http://repository.president.ac.id/xmlui/handle/123456789/13737
dc.description.abstract The mining industry still finds it difficult to turn large streams of operational data into decisions that are both fast and useful. At times the reports or dashboards arrive too late. By the time the numbers are available, the people on site may already need to act. This delay can bring production losses, extra safety concerns, and higher costs (Rojas et al., 2025). Artificial intelligence seems to help in some areas, such as predictive maintenance and equipment reliability (Sahoo et al., 2019; Abdi et al., 2008). Even so, its role in mining is not very broad. In many cases the data is noisy, systems fail to connect smoothly, and the models can be difficult for people to trust or explain (Landre Júnior et al., 2022). In this study we put forward MineMind, an AI-based model for performance management in mining. The idea is not only to monitor or report but also to support decisions that should be more proactive and adaptive. To develop the model, the work follows two paths. One path looks at benchmarking. It reviews how AI has been used in other industries, with energy being the main point of reference, and pulls out lessons that could make sense for mining. The other path turns to product development. Here the focus is on building MineMind with elements like real-time monitoring, natural language interaction, and AI-driven recommendations. For guidance, the research makes use of the Digital Transformation Pyramid (Westerman et al., 2014). Yet the framework is not taken as is. It is adapted to fit the mining setting. The results suggest that combining benchmarking with product development may help MineMind support mining companies in strengthening control, improving safety, and running operations more efficiently. On a wider note, this study also adds to technology management by showing one possible way to apply AI to mining performance management. It does not aim to close the discussion but rather to provide direction. en_US
dc.language.iso en en_US
dc.publisher President University en_US
dc.relation.ispartofseries Master of Technology Management;023202405044
dc.subject Mining en_US
dc.subject Artificial Intelligence en_US
dc.subject Performance Management en_US
dc.subject Benchmarking en_US
dc.subject Product Development en_US
dc.subject Digital Transformation en_US
dc.title DESIGN AND PROTOTYPING OF MINE MIND: A PRODUCT DEVELOPMENT APPROACH TO AI-DRIVEN MINING PERFORMANCE MANAGEMENT en_US
dc.type Thesis en_US


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