In　the　acceptance　process　of　newly　developed　five-axis　machine　tools　(FAMTs),　it　is　urgent　for　machine　tool　builders　to　understand　the　main　causes　of　machining　defects　on　S-shaped　test　piece.　This　paper　proposes　a　novel　causation　analysis　method　based　on　error　spatial　morphology　of　S-shaped　test　piece　to　decouple　the　key　geometric　error　parameters　causing　contour　errors　of　test　piece.　Firstly,　based　on　multi-body　system　(MBS)　theory,　tool　axis　surface　error　model　of　a　FAMT　is　set　up.　In　order　to　eliminate　the　effect　of　theoretical　error　on　contour　error　of　S-shaped　test　piece,　the　optimized　tool　path　is　planned　based　on　the　three-point　tangential　method.　Then,　the　NC　instruction　is　calculated,　and　error　spatial　model　is　established　to　characterize　contour　error　of　the　test　piece　by　considering　tool　setting　position.　As　a　basis,　error　spatial　morphologies　of　test　piece　are　drawn　and　the　relationships　between　geometric　error　parameters　and　error　spatial　morphologies　are　analyzed.　In　order　to　decouple　the　key　geometric　error　parameters　affecting　contour　error　of　test　piece,　the　causation　analysis　method　of　local　error　and　global　error　are　presented.　After　repairing　the　local　and　global　key　error　parameters　of　the　test　piece　obtained　from　these　two　analysis　methods　respectively,　the　local　machining　errors　are　reduced　by　more　than　80%,　and　the　global　machining　error　is　not　beyond　the　tolerance.　Finally,　the　cutting　experiments　of　S-shaped　test　piece　on　the　FAMT　XKAS2525x60　are　implemented.　Error　detection　results　of　the　cutting　test　piece　are　basically　the　same　as　that　shown　in　error　spatial　morphologies　of　test　piece,　which　verifies　the　correctness　of　error　spatial　model　for　the　test　piece.　After　compensating　the　global　key　error　parameters　obtained　from　the　causation　analysis　method　of　global　error　in　CNC　system,　the　detection　results　of　re-cutting　test　piece　under　the　same　conditions　indicate　the　test　piece　has　very　few　points　that　are　not　within　the　tolerance　range,　and　detection　results　after　compensation　and　global　repaired　results　are　almost　similar,　which　verifies　the　feasibility　and　correctness　of　the　proposed　analysis　method.　Therefore,　it　is　obvious　that　the　presented　method　bridges　between　geometric　characteristics　of　S-shaped　test　piece,　geometric　errors　of　machine　tool,　and　machining　defects　of　test　piece　and　provides　a　comprehensive　error　analysis　method　in　the　acceptance　and　performance　testing　of　FAMTs　by　using　the　S-shaped　test　piece.　Thus,　this　study　is　of　great　significance　for　improving　the　accuracy　evaluation　method　and　enhancing　the　design　accuracy　of　FAMTs.