One key characteristic of any process performance is variability; that is, a process rarely performs consistently over time. The bottleneck is one of the main reasons causing the system variability and fluctuation in production. Short-term production analysis and short-term bottleneck identification are imperative to enable manufacturing operations to optimally respond to dynamic changes in system behavior. However, conventional throughput and bottleneck analysis focus on long-term statistic bottleneck identification, which is usually not applicable to a short-term period. An on-line supervisory control method is introduced to search for short-term production constraints with unknown machine reliability distribution and mitigate those constraints to improve system throughput. The control mechanism uses playback simulation of the real production data to identify the bottleneck station, and control parameters of that station to reach a near balanced production line operation by understanding the bottleneck inertia phenomenon. The results ensure the smooth flow of products on the production line and increase the line’s performance.