This paper studies a multi-intelligent-reflecting-surface (IRS)-enabled integrated sensing and communications (ISAC) system, in which multiple IRSs are installed to help a base station (BS) provide ISAC services at the line-of-sight (LoS) blocked areas. In particular, we consider the case with semi-passive uniform linear array (ULA) IRSs each integrated with dedicated sensors for receiving echo signals, in which each IRS simultaneously senses one point target and communicates with one communication user (CU) within its coverage area. Under this setup, we first derive the closed-form Cramér-Rae bound (CRB) for the targets' direction-of-arrival (DoA) estimation at the corresponding IRSs. Then, to achieve fair and optimal sensing performance, we minimize the maximum CRB for targets' DoA estimation at all IRSs, by jointly optimizing the transmit beamformers at the BS and the reflective beamformers at the IRSs, subject to the minimum signal-to-interference-plus-noise ratio (SINR) constraints at individual CUs, the maximum transmit power constraint at the BS, and the unit-modulus constraints at the IRSs. To tackle the highly non-convex SINR-constrained max-CRB minimization problem, we propose an efficient algorithm based on alternating optimization and semi-definite relaxation, to obtain a converged solution. Finally, numerical results are provided to verify the effectiveness of our proposed design over various benchmark schemes based on separate or heuristic beamforming designs.