In recent years, the giant squid processing industry in Peru exhibited a 59% increase in exports with respect to 2018. According to estimates, this industry generates approximately 30,900 jobs per year. However, some SMEs experience low productivity, such as the PECEPE company, due to plant downtime. This represents 26% of the available time, which translates into the loss of 1760 tons every year. The most constraining external factor the sector faces is uncertainty in resource availability caused by changing weather conditions and informal fishing activities. Although there is a large number of research studies on the fishing industry and resource extraction, literature on processing plant operations is scarce. Within this context, this study seeks to promote a high impact sector in Peru, as well as fostering processing plant competitiveness and productivity. Hence, to address these iss...

For companies operating within the garment manufacturing industry, having frequent downtimes in their production flows is an extremely common issue. In this context, a balanced production line is required to prevent high waiting times due to limited productive capacity. A well-balanced assembly line allows products to be produced in an optimum time while using less resources, such as machines, materials, or labour, since the right number of products is produced with the exact amount of resources, thus generating savings in production costs. This paper seeks to foster optimum resource allocation through the line balancing tool. Finally, to define a work methodology, best practices were selected, and a procedures manual was developed focusing on Standardization. Both tools were implemented after implementing changes to the company culture by means of the Employee Empowerment tool. As a res...

Several factors compel graphic design companies to improve efficiency and competitiveness in their production lines. However, these companies are not prepared to take on this challenge, as they report delays in 20% of their deliveries, caused by high setup times, low machine availability, and poor work scheduling. In this context, this study proposes a new production management model fed by the interaction of lean manufacturing tools and the Johnson scheduling method. This model has been validated by direct application at the SISSA. The results obtained were the reduction of the setup time to 15 minutes, increased machine availability up to 24%, and an efficient scheduling of its tasks. All of these reduced the percentage of delivery delays from 20% to 6%.