In a worldwide environment, sustaining high yield with a minimum number of quality controls is key for manufacturing plants to remain competitive. In high-mix semiconductor plants, where more than 200 products are concurrently run, the complexity of designing efficient control plans comes from the larger amount of data and number of production parameters to handle. Several sampling algorithms were pro-posed in the literature, but most of them are seen impracticable when coming to an industrial implemen-tation. In this paper, we present and discuss the industrial implementation of a dynamic sampling algo-rithm in a high-mix semiconductor plant. We describe how the sampling algorithm has been modified, and point out the set of questions that have been raised by the industrial program. Results indicate that more than 30% of control operations on lots could be avoided without increasing the material at risk in production.