An　interval-parameter　fuzzy　robust　programming　(IFRP)　method　is　developed　for　the　assessment　of　filter　allocation　and　replacement　strategies　in　a　fluid　power　system　(FPS)　under　uncertainty.　The　developed　IFRP　can　effectively　handle　the　uncertainties　expressed　as　fuzzy　sets,　interval　values,　and　their　combinations,　which　exist　in　contaminant　ingression/generation　of　the　system　and　contaminant-holding　capacity　of　filter　without　making　assumptions　on　their　probabilistic　distributions.　The　fuzzy　decision　space　can　be　delimited　into　a　more　robust　one　with　the　uncertainties　being　specified　through　dimensional　enlargement　of　the　original　fuzzy　constraints,　leading　to　enhanced　robustness　for　the　optimization　process.　Results　indicate　that　the　developed　IFRP　can　not　only　help　decision-maker　to　identify　optimal　filter　allocation　and　replacement　strategies　to　control　the　contamination　level　of　FPS　with　a　minimized　system-cost　and　system-failure　risk　under　multiple　uncertainties,　but　also　mitigate　uncertainties　through　abating　interval　widths　of　the　replacement　periods　and　service　life　under　different　contamination　ingression/generation　rates.