Pre-bond TSV Test Optimization and Stacking Yield Improvement for 3D ICs

Abstract

Through silicon via (TSV) based three-dimensional IC (3D IC) exhibits various advantages over traditional two-dimensional IC (2D IC), including heterogeneous integration,reduced delay and power dissipation, compact device dimension, etc. However, to commercialize 3D IC products, still, many challenges exist. In this dissertation, we focus on conquering two of these challenges. The first challenge is to reduce pre-bond faulty TSV diagnosis time. The second challenge is to improve the compound yield and reduce cost of wafer-on-wafer stacked 3D ICs. Novel ideas are proposed and are demonstrated to be good solutions for these two challenges. Pre-bond TSV testing and defect identification is extremely important for yield assurance of 3D stacked devices. In this dissertation, we proposed a three-step optimization method named “SOS3” to greatly reduce pre-bond TSV test time without losing the capability of identifying certain number of faulty TSVs. The three steps of optimization are as follows. First, an ILP (integer linear programming) model is proposed to generate near-optimal set of test sessions for pre-bond TSV diagnosis. The sessions generated by our ILP model identify defective TSVs in a TSV network with the same capability as that of other available heuristic methods, but with consistently reduced test time. Second, an iterative greedy procedure to sort the order of test sessions is proposed. Third, a fast TSV identification algorithm is proposed to actually diagnoses the faulty TSVs based on given test sessions. Extensive experiments are done for various TSV networks and the results show SOS3 as a framework greatly speeds up the pre-bond TSV test. SOS3 provides useful known-good-die information for 3D die-on-die, die-on-wafer, and wafer-on-wafer stacking. Wafer-on-wafer stacking offers practical advantages over die-on-die and die-on-wafer stacking in 3D IC fabrication, but it suffers from low compound yield. To improve the yield, a novel manipulation scheme of wafer named n-sector symmetry and cut (SSCn) is also proposed in this dissertation. In this method, wafers with rotational symmetry are cut into n identical sectors, where n is a suitably chosen integer. The sectors are then used to replenish repositories. The SSCn method is combined with best-pair matching algorithm for compound yield evaluation. Simulation of wafers with nine different defect distributions shows that previously known plain rotation of wafers offers only a trivial benefits in yield. A cut number four is optimal for most of the defect models. The SSC4 provides significantly higher yield and the advantage becomes more obvious with increase of the repository size and the number of stacked layers. Cost model of SSCn is analyzed and the cost-effectiveness of SSC4 is established. Observations made are: 1) Cost benefits of SSC4 become larger as the manufacturing overhead of SSC4 become smaller, 2) cost improvement of SSC4 over conventional basic method increases as the number of stacked layers increases and 3) for most defect models, SSC4 largely reduces the cost even when manufacturing overhead of SSC4 is considered to be very large.