Sequential Estimation for Monitoring One-Shot Device Stockpiles

One-shot devices yield binary current-status observations because each unit can be tested only once. In stockpile settings, where testing is destructive and failures are rare, fixed-sample plans may consume more units than necessary. This paper proposes a sequential estimation procedure for monitoring one-shot device stockpiles at a fixed inspection time. The method is formulated in terms the inspection-time failure probability and its reciprocal, and is therefore applicable to general one-parameter lifetime models. A squared-error-plus-sampling-cost risk function is used to derive a stopping rule that adaptively determines the required number of observed failures. We establish first-order efficiency relative to an optimal fixed-sample benchmark and illustrate the framework through a stockpile case study motivated by stored N95 respirators. The proposed procedure provides a practical and theoretically justified tool for stockpile monitoring when destructive testing is costly and unnecessary sampling should be minimized.