Automatic visual quality inspection is a cornerstone of modern manufacturing, leveraging advancements in computer vision and robotics to enhance speed and efficiency. While numerous inspection planning methodologies exist, they often neglect the critical challenge of designing the inspection cell—specifically, determining the optimal placement of the robot relative to the inspected objects. This placement is pivotal for maximizing inspection performance and minimizing the inspection time. In this work, we present a flexible framework to determine the robot base placement via an optimization routine to facilitate the inspection of diverse objects. This eliminates the need to re-program the inspection cell whenever the object changes, significantly simplifying and streamlining the process. Extensive simulations validate the effectiveness of our method, demonstrating significant improvements in achieving high coverage and reducing the time compared to a brute force approach.