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

Abstract

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

Artificial intelligence in lean manufacturing: digitalization with a human touch?

“…This includes decision support for production scheduling (Bouzekri et al, 2022), optimization of resource utilization (Tripathi et al, 2022b) and multi-skilled worker assignment (Xin et al, 2015). (Abusaq et al, 2023;Arana-Landín et al, 2023;Marinelli, 2022;Shahin et al, 2023aShahin et al, , 2023bShahin et al, , 2023cShahin et al, , 2023dShahin et al, 2023a;Thiede et al, 2017;Trabucco and De Giovanni, 2021;Tripathi et al, 2022a;Tseng et al, 2021) Source: Author's own work adapt to changing environments and respond quickly to market changes. Importantly, and in line with lean thinking and practice, most of the research here points towards the decentralization of production planning and control systems, increasing flexibility and resilience of operations (Küfner et al, 2021;Rossit et al, 2019;Ulhe et al, 2023).…”

“…Toward Industry 5.0: sustainability, resilience and human-centricity The fourth and final theme that emerged from the SLR is based on developments toward Industry 5.0 and considers sustainability, resilience and human-centric aspects. In terms of sustainability, Abusaq et al (2023) combined lean principles and AI to improve energy efficiency in the case of a flexographic printing process for tissue roll packaging. In combining five-why analysis, value stream mapping and kaizen practices with ML, the OEE of the process was shown to improve by 25% and energy cost was reduced by more than US $150,000.…”

Energy consumption optimization in a printing company

“…The proposed approaches were compared on the basis of the case study, and it was concluded that the proposed heuristic algorithm was able to improve machine utilization in large-scale problems. Abusaq et al (2023) proposed an approach that combined lean production methods and machine learning to improve energy efficiency in flexographic printing machines. The study showed that the lean methodology employed was efficient and that idle time on each machine was reduced by 30%, resulting in energy savings of around 35%.…”

“…In all of the studies cited, the subjects addressed are: improving the production process and management in general, be it in terms of process flow and/or layout; logistics; working per item or per stock; as well as sustainability issues such as reducing and analyzing waste and pollutants; print production design and electronic design automation; optimization in digital printing, addressing simultaneous mapping of tasks, selection of resources for those tasks and mapping of tasks to resources; optimization of the physical location and task allocation of printing devices in office floor plans. It is worth noting that Abusaq et al (2023) addressed energy efficiency in using flexographic printing machines. However, that is different from the energy problem addressed in this study on printing and finishing machines in rotary offset presses.…”

Assessment of Efficiency and Anilox-Roll Condition after Ultrasonic Cleaning

“…To cater to evolving market requisites, anilox-roll manufacturers have been progressively enhancing anilox cell densities alongside their depths and volumes. However, despite advanced solutions optimizing the functionality of these cylinders [5,6], they remain susceptible to wear [7][8][9] and operational damage [10][11][12][13][14].…”