The Sawmill industry plays a crucial role in the forestry sector, providing the raw material needed for various industries such as construction, furniture, and paper production. Efficient production in sawmills is essential to meet the increasing demand for lumber and to remain competitive in the market. In this context, Discrete Event Simulation (DES) is a powerful tool for improving production efficiency by identifying bottlenecks, reducing lead times, and optimizing inventory levels.

This thesis project aims to develop a simulation model using Discrete Event Simulation (DES) to improve the production flow in a Sawmill. The simulation model allows the company to test different scenarios, such as changes in production schedules, machine configurations, and inventory management, without disrupting the actual production. By answering two investigative questions, the report provides insights into the level of information needed for the simulation and the limits of the simulation model's capability to detect flaws in the production process.

Accurate data is essential for building a reliable simulation model. Therefore, the report emphasizes the importance of collecting data on various aspects of the Sawmill, such as machine utilization rates, machine capacities, processing times, and inventory levels. The report also highlights the need for simplifications and assumptions to create an optimal model, as collecting data on every detail may not always be feasible. 

The ExtendSim software is used to build the Discrete Event Simulation (DES) in this report. This software allows the modeler to create an accurate representation of the Sawmill's production flow and analyze the impact of different scenarios on the production process. The simulation model can help the company make informed decisions by identifying bottlenecks, reducing lead times, and optimizing inventory levels.

In conclusion, this thesis project provides valuable insights into the use of Discrete Event Simulation (DES) to improve the efficiency of the Sawmill process. The simulation model developed in this report can help the company test different scenarios, reduce lead times, optimize inventory levels, and make informed decisions. The report highlights the importance of accurate data, simplifications, and assumptions in building a reliable simulation model. By leveraging Discrete Event Simulation (DES) as a tool for optimization, the Sawmill industry can enhance its productivity and remain competitive in the market.