diff --git a/aio/assets/templates/durable/durable_data_current.xlsx b/aio/assets/templates/durable/durable_data_current.xlsx
index 4ef2ed0..241fc60 100644
Binary files a/aio/assets/templates/durable/durable_data_current.xlsx and b/aio/assets/templates/durable/durable_data_current.xlsx differ
diff --git a/aio/assets/templates/durable/durable_data_velocity.xlsx b/aio/assets/templates/durable/durable_data_velocity.xlsx
index 4ef2ed0..0b47ea4 100644
Binary files a/aio/assets/templates/durable/durable_data_velocity.xlsx and b/aio/assets/templates/durable/durable_data_velocity.xlsx differ
diff --git a/aio/code/durable_action/factory_test.py b/aio/code/durable_action/factory_test.py
index ebcf0e2..0833162 100644
--- a/aio/code/durable_action/factory_test.py
+++ b/aio/code/durable_action/factory_test.py
@@ -233,7 +233,7 @@ def get_durable_data(path, config_file, data, scenario_time, hr, w2t):
         if len(_d2d_trq['device_servo_trq_feedback_0']) / 1000 > scenario_time + 1:
             _df = pd.DataFrame(_d2d_trq)
             for i in range(6):
-                _ = sqrt(_df[f'device_servo_trq_feedback_{i}'].apply(lambda x: (rcs[i]*x/1000)**2).sum()/len(_df[f'device_servo_trq_feedback_{i}']))
+                _ = sqrt(100*_df[f'device_servo_trq_feedback_{i}'].apply(lambda x: (rcs[i]*x/10000)**2).sum()/len(_df[f'device_servo_trq_feedback_{i}']))
                 del data[0][f"axis{i + 1}"][0]
                 data[0][f"axis{i + 1}"].append(_)
             _df = pd.DataFrame(data[0])
@@ -248,7 +248,7 @@ def get_durable_data(path, config_file, data, scenario_time, hr, w2t):
 
             _df = pd.DataFrame(_d2d_vel)
             for i in range(6):
-                _ = sqrt(_df[f'hw_joint_vel_feedback_{i}'].apply(lambda x: (rcs[i]*x/1000)**2).sum()/len(_df[f'hw_joint_vel_feedback_{i}']))
+                _ = sqrt(100*_df[f'hw_joint_vel_feedback_{i}'].apply(lambda x: (rcs[i]*x/10000)**2).sum()/len(_df[f'hw_joint_vel_feedback_{i}']))
                 del data[1][f"axis{i + 1}"][0]
                 data[1][f"axis{i + 1}"].append(_)
             _df = pd.DataFrame(data[1])