The　great　changes　in　the　external　environment　of　the　manufacturing　supply　chain　make　its　demand　more　complex　and　difficult　to　control.　This　paper　takes　China　as　an　example.　According　to　questionnaire　survey　and　principal　component　analysis,　the　risk　indicators　caused　by　uncertain　demand　are　screened　and　classified　to　construct　evaluation　system　and　complete　risk　identification.　The　Bayesian　network　integrating　fuzzy　set　theory　and　left　and　right　fuzzy　ranking　is　used　to　explore　the　relationship　between　risk　indicators　and　supply　chain　to　achieve　risk　evaluation.　In　view　of　the　highest　risk　factors,　an　incentive　mechanism　model　based　on　information　sharing　is　put　forward　to　prove　theoretically　that　information　sharing　is　an　important　strategy　to　reduce　risk.　The　results　are　as　follows:　The　uncertain　demand　will　lead　to　a　high　level　of　risk　in　China＇s　manufacturing　supply　chain,　in　which　the　level　of　information　technology　is　the　biggest　cause.　Only　when　manufacturing　enterprises　are　willing　to　share　information　and　other　node　enterprises　join　the　information　sharing　team,　can　demand　uncertainty　be　fundamentally　reduced.　The　proposed　risk　assessment　model　realizes　the　method　innovation　and　theoretical　innovation.　It　can　practical　and　effectively　help　relevant　enterprises　to　determine　and　control　risks.