This paper presents a signal processing based algorithm, the Mildly Nonstationary Mission Synthesis
(MNMS), which produces a short mission signal from long records of experimental data. The
algorithm uses the Discrete Fourier Transform, Orthogonal Wavelet Transform and bump reinsertion
procedures. In order to observe the algorithm effectiveness a fatigue damage case study was
performed for a vehicle lower suspension arm using signals containing tensile and compressive
preloading. The mission synthesis results were compared to the original road data in terms of both the
global signal statistics and the fatigue damage variation as a function of compression ratio. Three
bump reinsertion methods were used and evaluated. The methods differed in the manner in which
bumps (shock events) from different wavelet groups (frequency bands) were synchronised during the
reinsertion process. One method, based on time synchronised section reinsertion, produced the best
results in terms of mission signal kurtosis, crest factor, root-mean-square level and power spectral
density. For improved algorithm performance, bump selection was identified as the main control
parameter requiring optimisation
