Performance Evaluation of a Label Manufacturer Using Simulation Modeling
Currently, the Supply Chain has been affected by freight prices, material scarcity, demand forecasting, port congestion, and digital transformation which are causing high lead times and delaying deliveries in all industries, but specifically in the labeling/printing industry. The industry is currently affected by the lack of new research improvements, optimization methodologies, supply chain disruptions, and technologies implementations within the label industry. Labeling /Printing industry has been out in business for more than 50 years, where labeling technologies such as Flexographic, Digital, and Die Cutting have advance in performance, effectiveness, complexity, and dependability over the last years. The implementation of a Discrete-Event Simulation (DES) with Simulation Modeling Intelligent Objects (SIMIO) software will model the behavior and performance of each process and system by predicting the results system performance over time, system interactions, and tracking statistics to measure and compare performance. The input data selected for the model are cycle times, setup times, lead times, product ID, roll footage, machines, processes, and systems, to simulate the accurate simulation. Input data is analyzed with Stat: Fit Distribution algorithms and Excel Analyzer programs utilized to approximate data. Outputs are known to be results, results will be treated to implement scenarios will improve the overall process and system. This research will focus on the implementation of a SIMIO DES system will model virtual and real-world scenarios, while inputting measures will improve the overall flow of setup times, lead times, cycle times, process flow, and number processed. The research will assist in understanding the current manufacturing process with performance capacity enhancements that will improve the overall flow of setup times, schedule utilization, process flow, and number processed.
Holguin, Joshua, "Performance Evaluation of a Label Manufacturer Using Simulation Modeling" (2022). ETD Collection for University of Texas, El Paso. AAI29211178.