Abstract
This paper demonstrates how deployment of the Lean Six Sigma (LSS) methodology within the operational management of small- and medium-sized mining companies (mining SMEs) fosters the development of a new assessment method aimed at reducing non-productive times in one or more operations. However, this study only seeks to implement this methodology in the cleaning, hauling, and transportation stages. Even though Lean and Six Sigma methodologies are different tools, they are often combined to reduce waste, non-value-adding activities, and process variability, with the purpose of reaching the desired operational efficiency levels. The LSS methodology traditionally works with a DMA-IC phase structure (Define, Measure, Analyze, Improve, and Control); however, this study uses a variation thereof adapted in the best way to the Operational Assessment method proposed. This variant deploys the first three phases separately while combining the last two to produce a comprehensive improvement and control plan. This papers provides useful and meaningful information to reveal the maximum value obtained from the implementation of the LSS methodology in the development of this new method, as it not only dispenses an exhaustive diagnosis of the operations assessed but also a quantitative estimate of the potential improvement levels that could be reached if correctly implemented at mining SMEs.
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Aguero, F., Ramírez, G., Aramburu, V., Mamani-Macedo, N., Raymundo-Ibañez, C., Dominguez, F. (2020). Lean Six Sigma Operational Assessment Method with a Modified DMA-IC Cycle for Reducing Non-productive Times at Mining SMEs. In: Ahram, T., Taiar, R., Gremeaux-Bader, V., Aminian, K. (eds) Human Interaction, Emerging Technologies and Future Applications II. IHIET 2020. Advances in Intelligent Systems and Computing, vol 1152. Springer, Cham. https://doi.org/10.1007/978-3-030-44267-5_99
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DOI: https://doi.org/10.1007/978-3-030-44267-5_99
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