A sawmill operation uses many techniques, such as debarking, sawing, drying, and planning, to convert unprocessed logs into timber products. To achieve maximum productivity and satisfy client needs, effective coordination, resource management, and quality control are essential.

Sawmill operations may make use of simulation approaches including Discrete Event Simulation (DES), System Dynamics (SD), and Agent-Based Simulation (ABS). By simulating the flow of logs and timber, DES can improve workflows and resource efficiency. SD offers perceptions on feedback loops and causal interactions. ABS provides extensive analysis by modelling individual agents and their interactions.

The investigation began with a thorough data analysis and modelling approach for the sawmill system. There were efforts made to collect qualitative and quantitative data, which were rigorously validated. The system's basic features and processes were then shown in a conceptual model. To test several elements of the system's performance, simulation scenarios were run on the ExtendSim platform using a certified digital model.

The influence of buffer sizes on sawmill throughput and efficiency was studied, and it was discovered that changing buffer sizes enhanced production efficiency and reduced waiting times. Strategic buffer allocation resulted in greater efficacy and lower wait times.

Another set of tests looked at process delays and how they affected sawmill productivity and throughput. Although effective workflow management reduced process durations, the boost in productivity that resulted was not statistically significant.

After looking into input fluctuations (log quantity and quality), the study showed that the best input combinations for increasing sawmill productivity could be determined based on the products that were produced. Controlling input variance turned out to be crucial for raising system efficiency as a whole.