Conference Agenda

En el marco de la transformación digital del sector industrial, esta revisión analizó el uso de Big Data para predecir materia prima, enfocándose en su aplicación en la planificación de compras y la gestión de inventarios. Se realizó una búsqueda sistemática en Scopus en abril de 2025, siguiendo el protocolo PRISMA y la estrategia PIOC. De 829 artículos identificados, 23 cumplieron los criterios de inclusión relacionados con técnicas predictivas en el sector manufacturero. Los resultados muestran mejoras significativas en la precisión de los pronósticos, reducción de costos operativos y optimización del inventario mediante el uso de redes neuronales LSTM, algoritmos híbridos y gemelos digitales. Estas tecnologías favorecen una toma de decisiones más ágil y adecuada en contextos de alta incertidumbre. La revisión evidencia los beneficios del análisis de Big Data en la cadena de suministro, aunque también revela limitaciones, como la escasa representación de estudios en Latinoamérica y la concentración de investigaciones en Asia y Europa. Se recomienda impulsar estudios empíricos en contextos locales para validar la aplicabilidad de estas herramientas en entornos con menor desarrollo digital.

This study addresses an organizational transformation model guided by intrapreneurship, applied in a Peruvian textile microenterprise with low operational efficiency (63.54%) and unplanned cost overruns equivalent to 8% of sales. The proposal integrates Lean Manufacturing tools with IoT technology, highlighting the implementation of an IoT-supported Poka Yoke system in the cutting area, which reduced defects due to excess layers in the layouts from 60% to 13.64%. This improvement directly contributed to a decrease in the rework rate, which went from 13.34% to 6.3%, strengthening the quality of the final product. At the same time, the standardization of tasks and balancing using the Operator Balance Chart (OBC) improved operational uniformity, reducing non-conformity in cuffs from 10.13% to 7.15% and in collars from 9.31% to 6.22%. Likewise, the application of the 5S methodology and visual management tools optimized the work environment, achieving a reduction in unproductive time spent searching for materials from 23.77% to 9.12%. As a result, operational efficiency increased to 79.70%, approaching the international standards of Colombia (79.12%) and Brazil (80%). The model demonstrates not only its technical effectiveness but also its potential for replication as a sustainable strategy to increase the competitiveness of the Peruvian textile sector.

The objective of this research is to propose a model for improving organizational processes in the company Elevaria Café & Tostaduría. The research is descriptive and cross-sectional, and an observation guide was used as instruments to identify the current situation of the company. company. and a questionnaire for the collection of data and information. Previous studies indicate that Human Resources management is becoming a challenge for companies in the coffee sector, even more so when this sector is constantly growing. The case study shows that using business process management (BPM) in the process improvement model could reduce 78% of the execution time and 88% of the operating costs of payroll calculation management. The results show the measurement of the processes as they are executed using the Balanced Scorecard model together with the ACM methodology, the analysis of the results and the proposal of activities for the improvement of prioritized processes such as recruitment and selection of personnel, hiring personnel, training staff, management of absences and dismissal of staff

This article presents the design of a prototype system based on artificial intelligence aimed at optimizing logistics processes in the commercial sector of Trujillo, Peru. The proposed architecture includes predictive modules and a conversational interface (chatbot) to address common issues such as stockouts, overstocking, and empirical decision-making. The system conceptually applies mathematical models for demand forecasting and automated recommendations. Key data sources were identified, performance metrics were defined, and a cost structure feasible for small and medium-sized enterprises was estimated. Results indicate that the system significantly improves operational efficiency, reduces logistical errors, and supports data-driven decision-making. The conclusions confirm the applicability of the system in regional digital transformation efforts, demonstrating its potential to enhance commercial competitiveness through accessible, scalable, and context-aware technological solutions.

Veterinary clinics, like other service businesses, had to digitize their marketing channels in the face of COVID-19. Electronic media offer an agile and timely service system, which should be aligned with purchasing decisions, although there is still little academic literature on this field. This research aimed to confirm this relationship in users of a veterinary clinic in the city of Trujillo, northern Peru. A quantitative approach and a non-experimental cross-sectional design were adopted. A total of 224 clients of a veterinary clinic participated. An ordinal scale questionnaire was used for data collection, as well as inferential statistics. The main finding confirms the positive and moderate association between the constructs, i.e., although there is a link between the two, the variation in one does not predict exactly the level of change in the other. Likewise, the purchase decision is positively and moderately associated with the attitude towards social media marketing and content marketing, while there is a negative relationship with emailing. This work shows that, although digital marketing represents a key factor for businesses, not all actions are linked to the consumption decision, especially in businesses where the purchase experience is essential.

The research showed that the valorization of mango peel through unit operations (washing, cutting, crushing) and thermal processes (infusion, concentration, gelatinization) made it possible to obtain functional foods of more than 97% and a flexible and resistant biodegradable bioplastic. The material balances showed efficiencies of more than 90% and the energy balance indicated a total consumption of less than 500 kJ per batch, identifying drying as the phase of greatest demand.To optimize the circular economy and sustainable packaging, it was suggested to analyze moisture, water activity and phenolic compounds, evaluate the biodegradability of bioplastic and optimize drying.