Plant simulation is one of the most wide spread tools for manufacturing companies related to operations and management. Its utility lies in its a bility to conduct experiments and investigate production scenarios without disrupting actual manufacturing operations. A cross industry, a similar process is recommended for developing these simulations. An essential step in this process is ensuring the accuracy of the simulation before it can be used for experimentation. To ensure the accuracy of a simulation with respect to the intended purpose there are two steps: verification and validation.This thesis specifically focuses on the validation of a complex plant simulation encompassing numerous conditions, known as discrete-event simulation. The thesis was  conducted in collaboration with a globally recognized manufacturer of medical devices. The primary objective is to establish a standardized framework that assists simulation engineers in conducting validation for both current and future simulation projects. With respect to the objective, this framework guides the validator through various conditions that result in other validation techniques being deemed appropriate. Therefore, various validation techniques found in literature are examined and categorized according to their applicability to the given situation. The development of this framework aims to enhance the confidence of simulation engineers and other stakeholders in the experimental results, while also fostering an increased understanding of interrelationships within the production line. Ultimately, the utilization of experiments can lead to advancements in productivity, efficiency, and sustainability.