This paper addresses the limitations of the L’AMDEC method in maintenance operations, particularly the errors that lead to incorrect maintenance strategies. To mitigate this issue, Monte Carlo Simulation is applied to improve the reliability of maintenance decisions by evaluating multiple scenarios. Additionally, this approach optimizes maintenance schedules, human resource allocation, and spare parts inventory costs in manufacturing environments. The paper further explores various manufacturing optimization techniques, including just-in-time, statistical process control, total quality management, Six Sigma, value stream mapping, and computer numerical control. However, challenges such as resistance to change, limited data availability, and insufficient testing remain barriers to the widespread adoption of simulation-based optimization technologies in manufacturing.