Conference Agenda

The research conducted at the Los Alisos mining prospect aimed to evaluate its mining potential and was carried out in three phases: pre-field, field, and post-field. In the pre-field phase, a literature review and historical documentation were performed, data collection forms were designed, and an 11-hectare area was delimited. Additionally, geochemical and petrographic sampling was planned, along with a geophysical survey to evaluate the resistivity and chargeability of the lithology for a better interpretation of the deposit. Furthermore, the Selective Rock Chip sampling method was defined, collecting samples within a 3-meter radius to obtain representative data from areas with potential. During the field phase, a 1:1,000 scale geological map was created, and eight samples were collected for geochemical analysis for gold and silver, along with six for thin sections as part of the petrographic study. Simultaneously, a 50-meter NE-SW geophysical line was established using the resistivity method with a PQWT resistivity meter. Finally, in the post-field phase, the data obtained were processed using specialized software such as ArcGIS 10.8, Excel, and AutoCAD 20.1. The samples for the petrographic study were analyzed in the UPN Geology Laboratory using a Keysell Universal Petrographic Stereoscope, followed by an OPTIKA B-510POL-I petrographic microscope with a 4K/8 MP CMOS HDMI/USB camera. The results indicate that the area is a prospectable zone, even suitable for detailed exploration work.Keywords-- geological characterization, geochemistry, geophysics, gold and silver.

The objective of this research was to implement a training program and evaluate its impact on the loading and haulage operations at the Marcobre mining company, using a quantitative approach and a 12-month cross-sectional design. The methodology consisted of applying a survey to operators to evaluate how the training affected their performance and efficiency, identifying challenges and collecting feedback on the program. Participants were divided into two groups: Suitability 1, operators with experience on equipment of the same model and brand as the mine, and Suitability 2, with experience on different similar models at other mines, both with a minimum passing score of 85%. The results indicated that 66.7% of EX5600 shovel operators were satisfied or very satisfied with the training, while 83.3% of 793D truck operators reported similar levels of satisfaction. In terms of productivity, the implementation of the program generated improvements in average monthly production: a 4% and 14% annual increase for truck operators in the 01 and 02 retrofit programs, respectively; and a 4.5% and 9.2% monthly increase in EX5600 shovel production in the same programs. The training program improved operator performance, increasing monthly production on 793D trucks and EX5600 shovels. This study demonstrates that well-designed, segmented training can enhance operational efficiency and strengthen operator perception, bringing a more comprehensive and contextualized approach to the specialized literature.

Low efficiency in refractory production is a critical problem that affects both the profitability and sustainability of manufacturing processes. This study proposes an innovative model that integrates Lean and TPM 4.0 tools supported by IoT and artificial intelligence technologies. The proposal seeks to increase operational efficiency, reduce equipment downtime and mitigate high rework rates, thus contributing to greater productivity and lower operating costs. The model was applied in a company in the refractory crucible manufacturing sector, demonstrating a direct and significant impact on the efficiency of the production process. After its implementation, relevant improvements were observed: the porous crucible rate was reduced by 57.69 % (from 18.20 % to 7.70 %); the MTBF of the press increased by 24.34 % (from 173.06 h to 216.91 h), while the MTBF of the mixer increased by 50.43 %. Likewise, the internal configuration time decreased by 27.58%, from 83.60 h to 60.54 h. Finally, it is proposed that the model has the potential to be applied in other industrial environments, as it constitutes a scalable, flexible solution aimed at strengthening competitiveness and sustainability through the intelligent digitalization of maintenance processes.

Our study focuses on identifying the main mineral
species present at the Paredones mine in Cajamarca, and
characterizing their geochemical properties to assess the potential of
exploitable minerals and the possible reactivation of mining
operations. Twelve samples were collected: five for petrographic
analysis using thin sections observed with an OPTIKA B-510POL-I
trinocular polarizing petrographic microscope with HDMI/USB
input, 4K/8 MP CMOS sensor (OPTIKA OP-A-0033), and an
illuminator; and seven for geochemical studies, determining mineral
concentration and average grade. The local geology includes
andesites, tuffs, and volcanic breccias with pyroclastic, porphyritic,
and infill textures, affected by potassic, physical, and propylitic
alteration. The identified ore minerals are galena, chalcopyrite, and
bornite, while the gangue minerals are quartz, epidote, pyrite, and
sericite. The observed hydrothermal zone, along with the
mineralogical associations and geochemical results, demonstrates
the presence of a polymetallic system with high economic potential,
confirming that petro-mineragraphic and geochemical
characterization is essential to identify exploitable minerals and
guide sustainable exploration and exploitation strategies.

The research sought to increase productivity in the freezing cycle at a frozen food plant by implementing a work study. Work measurement and analysis techniques were applied, supported by process analysis diagrams and time studies with continuous timing. The study adopted a quantitative, applied approach. The population consisted of the production cycles of the freezing process at a frozen food plant, with 30 cycles evaluated before and after the intervention. The results showed significant improvements in operational performance, with a 9.2% increase in efficiency, a 33.6% increase in effectiveness, and a 45.9% improvement in productivity. Likewise, the freezing cycle time was reduced by 22.5%, confirming that methods engineering was an effective tool for optimizing production processes.

This study examines the interrelationships between Sustainable Resilience Strategy (ERS), Business Competitiveness (CE), and Digital Skills (HD) in Latin American small and medium-sized enterprises (SMEs) using structural equation modeling (SEM). Data from 387 SME managers in Ecuador, Colombia, and Peru were analyzed using maximum likelihood estimation. The results reveal that SRS significantly predicts CE (β=0.72, p<0.001) and that DS positively influence both SRS (β=0.58, p<0.001) and CE (β=0.45, p<0.001). The multigroup analysis showed significant sectoral differences: SMEs in the service sector showed stronger trajectories from HD to ERS (β=0.65 vs β=0.51, Δχ²=6.42, p<0.05). ERS mediates 52.3% of the effect of HD on CE (VAF=0.523). The model fit indices were excellent (χ²/df=1.89, CFI=0.97, TLI=0.96, RMSEA=0.042, SRMR=0.035). These findings contribute to understanding how digital capabilities enable sustainable resilience and competitive positioning in SMEs in emerging markets.