The current volatility in the marketplaces, complexity in technology, and fluctuations in customer demand motivate us to understand the dynamics involved in a complex system. This study focuses on analyzing the steel bar production system and its performance. This study uses system dynamics modelling (SDM) to model a steel plant production system and demonstrate a decision-making approach to improve steel bar production. This study uses simulation to incorporate key factors identified from existing research, including those that influence steel production. A causal loop diagram (CLD) and stock-flow diagram (SFD) are used to analyze the involved qualitative and quantitative features. In addition, sensitivity analysis was performed to analyze how the production grows with time in various scenarios of input variables. This model can be customized for specific steel plants. Industry practitioners can use this framework to make data-driven decisions regarding steel production. Additionally, practitioners can leverage this study to determine the essential variables and identify the factors that negatively or positively impact steel production.