Improving Energy Performance in Flexographic Printing Process through Lean and AI Techniques: A Case Study

Flexographic printing is a highly sought-after technique within the realm of packaging and labeling due to its versatility, cost-effectiveness, high speed, high-quality images, environmentally friendly nature. A major challenge in flexographic need optimize energy usage, which requires diligent attention resolve. This research combines lean principles machine learning improve efficiency selected machines; i.e., Miraflex F&K. By implementing 5Why root cause analysis Kaizen, study found that idle time was reduced by 30% for F&K machine, resulting savings 34.198% 38.635% per meter, respectively. Additionally, multi-linear regression model developed using range input parameters, such as production substrate density, time, working total run predict consumption job scheduling. The results exhibit efficient accurate, leading reduction costs while maintaining or even improving quality printed output. approach can also add reducing carbon footprint manufacturing process help companies meet sustainability goals.