The　massive　machines　connected　to　the　industrial　cyber-physical　systems　bring　challenges　to　the　machine　management　in　the　industrial　human　machine　interaction　(HMI).　The　engineer　has　to　identify　the　target　machine　from　a　long　list　which　is　a　non-trivial　problem.　Observing　the　fact　that　the　industrial　HMI　is　generally　executed　in　a　face-to-machine　manner,　the　face-to-machine　proximity　estimation　(FaceME)　algorithm　has　been　proposed　to　solve　this　problem.　Nevertheless,　due　to　the　randomness　of　wireless　signal,　the　estimation　accuracy　of　FaceME　is　not　sufficient　in　the　scenarios　with　densely　deployed　machines.　In　this　paper,　we　exploit　the　RSSI　difference　among　multiple　neighbors　in　the　industrial　HMI.　Based　on　the　analysis,　we　propose　a　face-to-machine　proximity　estimation　algorithm　called　FaceME+　which　takes　advantages　of　the　RSSI　difference　among　multiple　neighbors　to　improve　the　estimation　accuracy.　Its　performance　is　studied　on　the　mobile　industrial　HMI　testbed,　and　the　results　prove　the　efficiency　of　FaceME+.　©　2019　IEEE.