In this paper, we discuss the implementation of Continuous Sampling Plan (CSP)-1 under two scenarios: (i) infallible, and (ii) fallible inspection systems. For both cases, we develop an optimization model for designing a CSP-1 that minimizes the total expected cost. We use Markov theory to derive the expected results from the application of the CSP-1. A Bayesian approach is used to model the inspection system reliability. Based on the analyses for the two models, we offer a discussion on the adverse effects of disregarding inspection errors when implementing CSP-1.