The　growing　complexity　of　the　industrial　production　environment　introduces　various　uncertain　events,　resulting　in　increased　process　instability　and　reduced　production　efficiency.　The　stable　scheduling　method　is　crucial　to　ensure　the　continuous　and　stable　operation　of　the　production　process.　However,　the　existing　dynamic　flexible　job　shop　scheduling　problem　(DFJSP)　research　lacks　stability　analysis　of　the　scheduling　method.　To　optimize　the　production　process,　we　propose　a　dynamic　stability-aware　scheduling　method　based　on　dueling　double　deep　Q-network　(DSAS-D3QN).　The　method　solves　DFJSP　with　multiple　uncertain　events　and　reduces　the　job　processing　time.　Meanwhile,　we　analyze　the　stability　of　the　scheduling　method　by　describing　the　overall　distribution　of　DSAS-D3QN＇s　reward　function　values.　The　experiment　shows　that　the　proposed　method　can　effectively　reduce　the　processing　time　while　ensuring　the　stability　of　the　scheduling.　Through　stability　analysis,　we　verify　the　adaptability　of　DSAS-D3QN　to　unstable　environmental　changes.　©　2024　IEEE.