A ceramic monolith risks breakage during production of the exhaust systems in the automotive industry. This is due to its position at a specific angle throughout the canning phase (stuffing technique). To overcome this problem, quality control needs to be automated on each brick. This control aims to adjust, if needed, the positioning of the brick before starting the production. This paper applies image processing techniques following the Canny-Hough method and reaches more than 99% of good detection of straight lines within a tolerance of ±5 degrees, as requested by the plant. Some vision parameters (gain, exposure time and aperture range), have been tested in order to have a better visibility of the reference part. Furthermore, a repeatability test is validated in this paper, allowing the algorithm to be deployed in the plant. The dataset is accessible on the following link: https://doi.org/10.5281/zenodo.5948822