This study presents a constraint programming (CP) approach for modeling batch operations both in fab (incompatible job families) and backend (compatible job families) which involves the constraints of different job release times, non-identical job sizes, and different batch size. We formulate this scheduling problem as CP and compare with a mixed integer programming (MIP) approach. The models are tested on a set of common problem instances from a paper in the literature. Computational results show that CP outperforms the MIP approach with respect to solution quality and run time.