SIMULATION META-MODEL OF ASSEMBLY LINE WITH CONWIP CONTROL

This research navigates the application of simulation meta-modeling in understanding and controlling assembly line dynamics. Aimed at unveiling the relationship between input factors and output parameters in a production system, a precise meta -model was devised based on real system data and simulation statistics. The meta -model predicts parameteR-values within a verified validity range, simplifying complex variable relationships for enhanced decision -making in intricate systems. The accuracy of the model was notable within the tested range of CONWIP cards from 1 to 25, showcasing reliable output approximation. This study highlights the classical approach to simulation meta-modeling as cumbersome, propelling the quest for further simplification in analyzing complex production systems. The utilization of simulation meta-modeling emerged as a pivotal tool for validating complex simulation models and swiftly testing system sensitivity to input factor alterations. Noteworthy findings include the identification of an optimal number of CONWIP cards for maximizing throughput without excessive increases in Work -In -Progress or throughput time. The research also underscores the potential of 5th-degree polynomial models in approximating production performance and throughput time accurately, offering robust tools for informed decision -making. This venture marks a significant stride towards a more streamlined, accurate, and efficient analysis of complex production systems, showcasing the promising applicability of simulation meta-modeling in industrial engineering and production management.