Bottleneck Identification and Production Improvement in Manufacturing Systems Using Discrete-Event Simulation

In the highly competitive manufacturing industry, optimizing production processes is essential for improving efficiency, reducing bottlenecks, and minimizing production delays. This study employs JaamSim (Simulutaion tool) to perform Discrete-Event Simulation (DES) in order to analyze the production workflow at Geo Sondaj Makine AŞ., a drilling equipment manufacturer. The study thoughtfully explores seven key components, aiming to identify potential bottlenecks using queue metrics and machine activity data. Different strategies, such as increasing workstation capacities, implementing parallel multiple working stations, and dynamic resource allocation, were tested to improve throughput and reduce production time. Simulation experiments showed significant performance benefits, especially a 37.9% reduction in the production time of the HQ Core Barrel component, which demonstrates the effectiveness of the proposed improvements. Statistical analysis (confidence intervals: 90%, 95%, 99%) and graphical comparisons were performed to validate these improvements, which confirmed the reliable effectiveness of the implemented strategies. The results prove that DES is an effective tool not only for identifying bottlenecks but also for production optimization and decision-making in manufacturing. Future research should explore predictive models based on artificial intelligence to further improve performance and resource utilization.