Conference Agenda

This paper presents a systematic review of the impact of the Poka Yoke (PY) methodology in the manufacturing industry, focusing on how these practices can influence the prevention of errors, decrease defects, ensure higher quality processes, and foster a culture of continuous improvement. This research focuses on analyzing and synthesizing the existing literature to determine its contribution to quality and operational efficiency in the manufacturing sector. This study uses reliable databases such as Scopus and ScienceDirect, applying the PICO and PRISMA approaches to structure the search and selection of relevant articles published between 2019 and 2024. The results highlight the significant reduction of errors and defects, improvements in risk management and quality, as well as the optimization of delivery times and production processes. In addition, the methodologies that best fit with PY are identified, such as 5S, SMED, TPM and VSM, which also contribute to continuous improvement and production efficiency. Likewise, the bibliometric analysis carried out reveals a growing interest in the PY methodology, with a notable increase in the number of publications in recent years, especially in countries such as India and Peru. This study provides a comprehensive and up-to-date view of the contribution of the PY methodology in the manufacturing industry, highlighting its positive impact on improving quality and operational efficiency.

This study was conducted to apply engineering methodologies and tools in an environmental consultancy firm to address issues related to poor maintenance management of environmental equipment and inadequate responsiveness to customer demand. To tackle these challenges, two alternative solutions were proposed and evaluated for each problem, with Autonomous Maintenance and the Kanban Methodology being selected as the most viable approaches. The simulation of these solutions demonstrated significant improvements within the company. Regarding the first issue, equipment availability increased from 75% to 91%. Additionally, customer service efficiency improved from 15% to 21%, validating the effectiveness of the implemented tools. Finally, the economic analysis revealed a total benefit of S/ 6,869.74, with an internal rate of return (IRR) of 21%, a net present value (NPV) of S/ 2,891.99, and a benefit-cost (B/C) ratio of 1.73. These results confirm that the applied solutions were both technically and economically viable, leading to substantial improvements in operational processes and customer responsiveness.

Abstract–This study was conducted with the objective of implementing the Poka Yoke tool in a footwear supply importing company. The research began with an initial diagnostic phase, identifying stock shortages and subsequent sales losses due to inefficient inventory management. To address this issue, several alternative solutions were proposed and evaluated under realistic constraints, with Poka Yoke being selected as the most effective approach. The research followed an experimental design, and the implementation of this methodology was simulated, yielding positive results, including an internal rate of return (IRR) of 11%, a net present value (NPV) of $1,086.76, and a benefit-cost (B/C) ratio of 6.62. In summary, the adoption of the Poka Yoke tool facilitated greater operational efficiency, enabling more precise and adaptable inventory management. This proposal aims to establish a replicable model to optimize inventory management across various industries.

The growing complexity of globalized supply chains has compelled organizations to adopt innovative solutions to maintain their competitive edge. In this scenario, artificial intelligence (AI) has emerged as a pivotal tool for optimizing logistical processes and enhancing operational efficiency. This Systematic Literature Review (SLR) aims to analyze how AI applications improve operational efficiency within the supply chains of industrial companies. To address this objective, the PIOC methodology (Problem, Intervention, Outcomes, Context) was employed to structure specific research questions and guide the search for relevant studies in scientific databases such as Scopus. The analysis of twenty academic articles reveals that demand forecasting and inventory management are the most impactful AI applications, contributing 25% and 20% to overall performance, respectively. Other applications, such as route optimization and predictive maintenance, also demonstrate significant contributions, each accounting for 15% of the improvements. These findings underscore that AI implementation not only enhances key operational efficiency metrics—such as reducing logistics costs and minimizing downtime—but also enables companies to swiftly adapt to dynamic operational environments. This research enriches the existing literature by offering a comprehensive framework on the practical applications of AI in supply chain management and its positive effects across various global industries. Beyond highlighting the tangible benefits of AI, the study emphasizes its transformative potential in optimizing processes, particularly in the context of ongoing digital transformation. By doing so, it provides valuable insights for both academia and industry, paving the way for further exploration and adoption of AI-driven solutions in supply chain operations.

This study was conducted at a Higher Education Institution in Arequipa with the purpose of ergonomically evaluating the workstations of cleaning operators and proposing improvements to optimize their working conditions. To achieve this, psychosocial, environmental, and physiological factors were analyzed. Additionally, the Ergo/IBV software and its modules (REBA Postures, RULA Postures, and Manual Handling of Multiple Loads) were used to assess ergonomic risks in the workstations. The results indicated high levels of ergonomic risk, leading to the formulation of proposals focused on the implementation of ergonomic equipment and training programs. The feasibility of the proposal was evaluated from an economic perspective, demonstrating its viability and benefits for the health and productivity of the operators. Finally, a follow-up plan was established to ensure its effectiveness.