Fast　switching　speed,　low　power　consumption,　and　good　stability　are　some　of　the　important　properties　of　spin　transfer　torque　assisted　voltage　controlled　magnetic　anisotropy　magnetic　tunnel　junction　(STT-assisted　VCMA-MTJ)　which　makes　the　non-volatile　full　adder　(NV-FA)　based　on　it　attractive　for　Internet　of　Things.　However,　the　effects　of　process　variations　on　the　performances　of　STT-assisted　VCMA-MTJ　and　NVFA　will　be　more　and　more　obvious　with　the　downscaling　of　STT-assisted　VCMA-MTJ　and　the　improvement　of　chip　integration.　In　this　paper,　a　more　accurate　electrical　model　of　STT-assisted　VCMA-MTJ　is　established　on　the　basis　of　the　magnetization　dynamics　and　the　process　variations　in　film　growth　process　and　etching　process.　In　particular,　the　write　voltage　is　reduced　to　0.7　V　as　the　film　thickness　is　reduced　to　0.9　nm.　The　effects　of　free　layer　thickness　variation　(gamma(tf))　and　oxide　layer　thickness　variation　(gamma(tox))　on　the　state　switching　as　well　as　the　effect　of　tunnel　magnetoresistance　ratio　variation　(beta)　on　the　sensing　margin　(SM)　are　studied　in　detail.　Considering　that　the　above　process　variations　follow　Gaussian　distribution,　Monte　Carlo　simulation　is　used　to　study　the　effects　of　the　process　variations　on　the　writing　and　output　operations　of　NV-FA.　The　result　shows　that　the　state　of　STT-assisted　VCMA-MTJ　can　be　switched　under　-0.3%　＜=　gamma(tf)　＜=　6%　or　-23%　＜=　gamma(tox)　＜=　0.2%.　SM　is　reduced　by　16.0%　with　beta　increases　from　0　to　30%.　The　error　rates　of　writing　＇0＇　in　the　NV-FA　can　be　reduced　by　increasing　V-b1　or　increasing　positive　V-b2.　The　error　rates　of　writing　＇1＇　can　be　reduced　by　increasing　V-b1　or　decreasing　negative　V-b2.　The　reduction　of　the　output　error　rates　can　be　realized　effectively　by　increasing　the　driving　voltage　(V-dd).