The alcoholic and non-alcoholic beverage manufacturing sector faces persistent challenges that directly impact operational efficiency and business profitability. Recurrent problems in the equipment and sub-optimal practices of operators generate significant waste and production delays. Previous studies have explored methodologies such as Six Sigma, Lean Manufacturing and Kaizen to address these challenges, highlighting tools such as VSM, 5S and SMED. The sector urgently needs to improve operator training, implement advanced monitoring and control technologies to reduce equipment failures. This study proposes a model that integrates Lean Manufacturing and Machine Learning to optimize the production process, reduce line change times and reduce the percentage of waste. Key results showed a significant improvement in production efficiency, with a 42.4% reduction in quality control time thank...