Increasing efficiency in flexographic MSEs through standard work, SMED, Artificial Intelligence and RCM in?Latin?America

In the graphics sector, companies face a significant challenge: a high rate of order noncompliance due to limited capacity in their production processes. The importance of this problem is not only defined in the dissatisfaction among customers, but also in the direct impact on profits due to the economic loss due to unfulfilled orders. Significant efforts have been made to address this issue, including the proposal of an improvement model that seeks to increase efficiency through standard working practices, SMED, AI and RCM. The motivation to solve these problems lies in the need to improve the efficiency and profitability of companies in the graphic sector, as well as in customer satisfaction. The main contribution of this study lies in the identification and validation of an improvement model that can help companies in the graphics sector to overcome their efficiency and order fulfillment challenges. The validation of the proposed model was carried out through simulations in the Arena software and its implementation was in a Peruvian company dedicated to the printing of self-adhesive labels. The main result achieved was a 13.3% increase in the efficiency indicator of the ILMA 340 printer (from 63 to 76.3%), a 27% reduction in machine assembly times (from 90.5 to 65.3 minutes) and an increase in the average time between failures by 53.4% (from 30.0 to 46.5 hours). In conclusion, the improvement model managed to overcome the technical gap, increasing efficiency and productivity for companies in the graphic sector, which contributes to customer satisfaction and increased profits.