Conference Agenda

The objective of this research was to evaluate the influence of the use of emerging technologies in the improvement of pig farming in Peru by 2024. A non-experimental methodological design was used with a qualitative approach and a descriptive scope, using the deductive method and statistical data search techniques and online documentary review. The main results indicated that genomic selection and genetic editing increased production efficiency and genetic quality of pigs by 15-20% in countries such as the European Union and the United States. In addition, technologies based on artificial intelligence, such as FertiBoar and phenotyping, improved reproductive efficiency in Brazil by 18% and reduced operating costs by 10-12%. Likewise, the use of dry and wet scrubbers achieved emission reductions of up to 90% in the European Union, improving animal and environmental welfare. Automation in the evaluation of animal aplomb and behavior allowed a more efficient selection of breeding animals in the United States. The findings suggested that the adoption of these technologies in Peru could have significantly improved the competitiveness of pig farming, optimizing production and meeting quality and sustainability standards. The implementation of these innovations could have reduced production costs by up to 15-20% and improved genetic quality, facilitating entry into international markets that value sustainability and efficiency.

Inefficient inventory management in a veterinary clinic in Guayaquil has led to issues such as stock mismanagement, excess unsold products, shortages of high-demand items, and human errors. This project aims to develop specialized software that optimizes inventory administration through predictive tools and advanced data analysis.

The methodology included interviews with inventory managers, historical data analysis, and the application of tools such as the Ishikawa Diagram, Pareto Analysis, and the 5 Whys to identify the root causes of the problem. Solution alternatives were also evaluated using priority and impact-difficulty matrices, ultimately selecting the design of software incorporating EOQ and Silver-Meal models.

The resulting software enables the calculation of optimal inventory quantities and reorder points, adapting to demand fluctuations. Additionally, it features a secure and accessible web interface to simplify usage. The results demonstrate a reduction in errors, excess, and inventory shortages, as well as an improvement in operational efficiency. The conclusions highlight the importance of identifying root causes and proposing comprehensive technological solutions to optimize processes and enhance organizational performance.

International trade has gained significance, and while many SMEs aim to integrate, a large number fail due to a lack of competitiveness. These businesses often lack awareness of the challenges involved in the process of internationalisation. In this context, the objective was set to describe the main challenges faced by textile SMEs in Lima, Peru, during their internationalisation process from 2019 to 2023. The research adopts a qualitative and descriptive approach, employing a nonexperimental design based on document analysis through data sheets, including the review of key documents such as theses, articles, and reports. Grounded theory was used to analyse data and establish relationships between relevant categories and subcategories. The results indicate that the challenges faced by textile SMEs in Lima during their internationalisation (2019– 2023) include external factors such as trade barriers, global competition, and unfavourable trade policies. Internally, key limitations are a lack of innovation, inefficient management, and limited adaptive capacity. In conclusion, the study highlights the need for gradual internationalisation strategies, such as the Uppsala Model, and the use of digital tools like e-commerce to overcome these barriers. Additionally, it emphasises the importance of inclusive policies, innovation, and efficient business management to strengthen the competitiveness and sustainability of these companies in global markets.

In the metal-mechanical sector, where activities such as the assembly and construction of metal structures with large machinery are carried out, workers are exposed to various risk factors that can generate serious consequences if not properly controlled and managed. The objective of this research is to determine occupational risk prevention techniques that can significantly improve the performance and efficiency of processes in the metalworking industry. Four phases were developed, the first presents the diagnosis that considers the initial proposal, followed by the action plan together with the redesign of the process, the third shows the implementation where the improvement is presented, and the last one corresponds to the validation. After the implementation of the pilot plans and the simulation performed with Arena, we obtained an increase of 32.64% on productive efficiency.

The agro-industrial sector is crucial for the Peruvian economy, contributing significantly to exports and GDP growth. However, it faces challenges, particularly high production waste due to machinery failures, lack of preventive maintenance, and non-standardized processes, which reduce productivity and profitability. This study focuses on excessive waste in a spinach production company and proposes a solution using Total Productive Maintenance (TPM). Emphasis is placed on preventive maintenance to enhance machinery efficiency and process standardization to improve production. Additionally, a FIFO system is suggested for better inventory management, alongside a circular economy approach to reduce waste. The research primarily targets the post-harvest stage, where waste is most critical, but addresses the full production chain. Implementation will follow the PDCA methodology, starting with planning and training staff in preventive maintenance and process standardization. Progress will be tracked through key performance indicators, and a pilot plan will assess the real-world impact of proposed changes. The goal is to improve sustainability and competitiveness in Peruvian agri-food businesses while addressing critical industry challenges.

The Peruvian textile sector has been characterized by its instability. In 2023, it showed an 18.1% decline in GDP, and although the number of companies grew by 0.3% annually between 2019 and 2023, micro-enterprises (95.4%) predominate, with a high concentration in Lima. A challenging sector like this presents particularly difficult obstacles for micro-enterprises, whose opportunities are limited. The objective of this article is to propose a management model based on Lean Manufacturing, Methods Engineering, and Circular Economy to improve the different stages of production. The methodological proposal consists of four stages: planning, implementation, standardization, and flow manufacturing. The circular economy is based on four criteria: supplier selection, product design optimization, production efficiency, and reuse of scraps and waste. The model is applied in a micro-enterprise in Arequipa dedicated to the production of alpaca fiber textiles. Before implementation, the company suffered economic losses, low efficiency, and high return rates. The results show significant improvements: defect reduction (from 15% to 2%), increased on-time deliveries (from 50% to 80%), and a profit margin improvement from -15% to 1%.