I would suggest iteratively enhancing features (while checking in the visualisations) makes sense by systematically bringing more domain knowledge into your features. Feature crosses are one way but you are not limited to this. Feel free to use any mathematical operations resp. physical or other domain models that just make sense to derive good features. My experience is that signal processing techniques (that you learn in Mechatronics or System theory) are especially helpful, e.g.: for example a Fourier transform can come in handy when you work with oscillating systems and want to use your model for predictive analytics of a steady state system.
Besides that, in general a residual analysis is always helpful when evaluating your models resp. working on your features, see also: Anomaly Detection Algorithm Statistical Independence - #2 by Christian_Simonis
Please let me know if anything is unclear.
All the best and happy learning, @mehmet_baki_deniz!
Best regards
Christian