Sensitivity Analysis for the Important Input Variable based on the Orthogonal Arrays

Purpose: This study aims to identify the critical input variables that significantly affect the optimization of repair parts in complex weapon systems.Methods: A total of 75 input variables are initially considered and then reduced to 28 based on expert review and system requirements. An orthogonal array-based design of experiments is applied to perform sensitivity analysis.Results: The analysis reveals that several variables, including Annual Operating Hours, System Life Cycle, MTBF, Unit Price, Weight, Procurement Lead Time, Unit Repair Cost, and Repair Time, have a strong influence on the total life cycle cost.Conclusion: By applying orthogonal arrays to sensitivity analysis, the study identifies key variables that significantly affect optimization outcomes. These variables should be managed with precision through enhanced user training and system guidance. Meanwhile, less sensitive inputs may be simplified, improving efficiency and reducing the potential for data entry errors in logistics support systems.