The　problem　with　computer　model　calibration　by　tuning　the　parameters　associated　with　computer　models　is　significant　in　many　engineering　and　scientific　applications.　Although　several　methods　have　been　established　to　estimate　the　calibration　parameters,　research　focusing　on　the　design　of　calibration　parameters　remains　limited.　Therefore,　this　paper　proposes　a　sequential　computer　experiment　design　based　on　the　D-optimal　criterion,　which　can　efficiently　tune　the　calibration　parameters　while　improving　the　prediction　ability　of　the　calibrated　computer　model.　Numerical　comparisons　of　the　simulated　and　real　data　demonstrate　the　efficiency　of　the　proposed　technique.