To　reveal　the　regularities　among　comprehensive　performance,　configuration　and　scales　for　simultaneous　mechanism　analysis　and　synthesis,　due　to　the　correlation　and　diversity　of　the　single　performance　indexes　of　robot　mechanism,　combined　with　statistical　principles,　based　on　linear　dimension　reduction　and　nonlinear　dimension　reduction　principle,　principal　component　analysis　(PCA)　and　kernel　principal　component　analysis　(KPCA)　can　be　introduced　into　comprehensive　performance　evaluation　for　typical　serial　robots-plane　series　manipulator　with　different　configurations　and　scales,　then　the　mechanism＇s　configuration　and　scales　with　best　performance　can　be　selected.　Reults　show　that　KPCA　method　has　more　effective　reduction　effects,　and　can　reveal　the　nonlinear　relationship　among　different　single　performance　indexes　to　provide　more　comprehensive　performance　evaluation　information,　which　can　reveal　the　numerical　calculation　relationships　among　comprehensive　performance,　configuration　and　scales,　and　provide　a　scientific　reference　for　simultaneous　mechanism　analysis　and　synthesis.