Thank you for your comments and guides!
You are definitely correct that the solution was play around with some hyperparameters.
I already resolved these issues by normalizing the input data sets.
The main problem was coming from my input data sets having extremely small values.
Therefore, the hyperparameter tuning process was not worked since the gradient-based optimization algorithm could not capture any features from very small values. So, I think the trained CNN always gave me the similar output predictions.
By normalizing the input sets, I can get the very small mean errors from all 40x80x1 output data forms.
Thank you so much!