Simulation-Based Optimization to Increase Tetra Pak CAP/30 Flex Capper Machine Uptime
Open Access DepositedAbstract Tetra Pak’s innovative CAP/30 Flex’s machine is designed for high-speed aseptic food and beverage capping, capable of processing 7,980 caps per hour. Despite the capper’s advanced design, it often suffers from unplanned breakdowns and high-wear component failures. The failures are mostly due to a fusion of corrective and preventive maintenance strategies being utilized instead of proactively addressing concerns before they become breakdowns. The research focus will be on developing an optimization model using AnyLogic 8 simulation modeling software to enhance the Tetra Pak’s CAP/30 capper efficiency, reliability, and sustainability. The adoption of a simulation-based approach in the maintenance department can identify root causes of asset stoppages. Models can also help measure the risk of applying different strategies before implementing them into the process. A boot-on-the-ground root cause analysis, based on 3-months capper runtime observations and 7-years of historical data, reveals that 23% of manufacturing line downtime was caused by the capper asset. This praxis addresses these challenges, by employing a hybrid of Discrete Event Simulation (DES) and Agent-Based Modeling (ABM) to assess an assortment of capper optimization scenarios aimed at reducing equipment stoppages and enhancing resource utilization. Some scenarios under consideration are reactive run-to-failure maintenance, preventive maintenance’s scheduled intervals, sensor driven predictive maintenance are just a few. The merging of condition-based maintenance and production’s autonomous maintenance strategies aims to improve defect detection and mitigation. It is through the simulation of different maintenance strategies; the study seeks to streamline processes and enhance the overall performance of the capping machine. The improvements gathered from the simulation model have been implemented on an aseptic pre-production liquid food line to test real-world results. These enhancements lead to a 23% increase in throughput, a 38% reduction in defect rates, and a 61% decline in the capper’s idle time. By aligning the CAP/30 Flex simulation output responses, predictive maintenance strategies, and production performance enhancement, the production line saw a 300% reduction in maintenance calls to the capper in four months. The results of this praxis demonstrate that improving the relationship between proactive maintenance and operational strategies can improve both production efficiency and machine reliability. This research offers a framework that is both scalable and practicable for optimizing aseptic liquid food packaging systems. Using simulation modeling to optimize machine’s assets, create a practical platform for recommendations to site leadership teams looking to boost throughput, reduce downtime, and implement data-driven maintenance strategies.
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