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I am a PhD student and I am studying PLS-MIMIC model. I have just one latent and two construct, one of them is formative and the other one is reflective. I have 10 indicators for formative construct, and 3 causes for reclective one . I am using SmartPLS 3. I understand I have just direct effect. Both indicators and causes have their loadings so how can I specify the relationship between causes and indicators?

I don't quite understand the problem, but you might look into the PLS SEM book for redundancy analysis and also the following paper might help you:
Cheah, J. H., Sarstedt, M., Ringle, C. M., Ramayah, T., & Ting, H. (2018). Convergent validity assessment of formatively measured constructs in PLS-SEM: on using single-item versus multi-item measures in redundancy analyses. International Journal of Contemporary Hospitality Management, 30(11), 3192-3210.

I attached my model. I would lile to know that how I can know the relationships between eee and fff or ddd and hhh? Is it possible multiply their loadings of them to understand their(indicators) effects on causes)?

Yes, you could multiply outer_weight*path_coefficient*outer_loading, e.g., 0.866*-0.371*0.833 = -0.268 for the effect of eee on fff in a sence of a total effect that matches partial regression coefficient logic.
Another option would be the use of outer_loading*path_coefficient*outer_loading, which would match a canonical correlation. You could find that also under Indicator Data (Correlations) > Model Implied Estimated Correlation Matrix