For the sake of product yield and quality considerations, time constraints (TCs) are imposed between process operations in various multi-product manufacturing systems. Often spanning a number of operations, time constraints tend to follow each other in close succession and overlap, forming thus time constraint tunnels (TCTs). The regulation problem of releasing lots in these time constraint tunnels is particularly challenging in semiconductor manufacturing systems, because of re-entrant flows, machine heterogeneity and high mix low volume (HM-LV) production configurations, which are typical in many wafer fabrication facilities. In such an evolving and time-varying context, this paper proposes a sequential sampling-based approach to estimate the probability that, prior to its release, a lot leaves a given time constraint tunnel on time. The proposed approach proves to be competitive in various respects by (i) taking into account industry specific features, (ii) being industrially tractable, and (iii) being sensitive and responsive to the current manufacturing system. Based on real-life instances, numerical experiments highlight the computational effectiveness and the industrial soundness of the proposed problem modelling together with the solution approach.