The challenge in the aggregate production planning for high-tech manufacturing, such as aerospace, semiconductor manufacturing, or high precision components production, is the variability in cycle times or cycle steps due to the rework required to meet very high levels (6-sigma) of quality. This variability in the lower planning level needs to be accounted for the aggregate planning level. Planning circularity, whereby cycle time depends on resource utilization while resource utilization is determined by cycle time continues to be an important problem in the aggregate planning literature. It is well known that ignoring congestion, as is the case in MRP-II based systems still widely in use is inaccurate. In the presence of congestion, the relationship of WIP and throughput is nonlinear and bottleneck resources may shift constantly. The most common approach of addressing the nonlinear relationship between the WIP and the throughput is through the clearing function. Recent work by Omar et al. (2017) proposed a mixed-integer linear model for closed queuing production networks using fixed release planning. The challenge with this model is that it is difficult to scale up for typically sized problems scalability. This work extends the approach in Omar et al. (2017) by proposing a non-linear model based for the open queuing production network which shows some promising results.