Continuous-Flow　Microfluidic　Biochip　(CFMB),　with　their　integrated　features,　bring　traditional　biochemical　experiments　on　a　single　chip　to　accomplish　complex　operations　and　reactions　through　precise　control,　efficient　reactions　and　emerging　ways　of　saving　reagents.　In　the　field　of　intelligent　digital　healthcare,　CFMB　have　attracted　a　lot　of　attention.　However,　traditional　manual　design　schemes　can　no　longer　meet　the　needs　of　increasingly　complex　chip　architecture　design.　Therefore,　this　paper　proposes　an　automated　design　method　for　resource　binding　and　module　placement　of　CFMB　based　on　a　list　scheduling　algorithm　and　an　improved　Simulated　Annealing　algorithm.　Through　the　resource　binding　and　scheduling　design　based　on　the　list　scheduling　algorithm,　an　effective　scheduling　strategy　is　generated,　which　effectively　improves　the　biochip　execution　efficiency.　In　addition,　the　improved　Simulated　Annealing　algorithm　solves　the　module　placement　problem　in　the　biochip　in　a　limited　physical　space.　Compared　with　some　benchmark　algorithms,　the　experimental　results　demonstrate　the　effectiveness　of　the　method　in　the　biochip　design　process　and　provide　a　practical　framework　for　further　development　of　CFMB　in　the　field　of　intelligent　digital　healthcare.　©　The　Author(s),　under　exclusive　license　to　Springer　Nature　Singapore　Pte　Ltd　2024.