This paper presents the development of a stochastic cost model aimed at determining the optimal number of operators required for a workstation, considering the activities performed by them, the time required for each activity, and the associated costs. The model takes into account the inherent variability in task performance and the corresponding costs involved. By utilizing the derived time equations, the study identifies both value-added and non-value-added activities, along with their respective costs. The proposed optimization model not only enables the estimation of the required number of operators but also provides insights into the impact of addition of workstation on the overall cost of the product. By considering the variability in task performance and associated costs, the model offers a comprehensive approach to operator allocation and workstation planning. Through the application of this stochastic cost model, organizations can make informed decisions regarding operator allocation, optimizing the utilization of available resources while minimizing costs. The findings of this research contribute to the understanding of the relationship between operator allocation, number of workstation, and production costs. The developed model serves as a valuable tool for decision-makers in the manufacturing industry, enabling them to analyze and optimize their operations effectively.