Process for manufacturing objects, such as tubes or packaging, comprising at least one quality inspection integrated into the manufacturing process, performed during production and continuously, said quality inspection comprising a learning phase and a production phase, said learning phase comprising at least the following steps: -) producing N objects considered to be acceptable; -) taking at least one reference primary image (A k ) of each of the N objects; -) dividing each reference primary image (A k ) into (P k ) reference secondary images (S k,p ); -) grouping the corresponding reference secondary images into batches of N images; -) determining a compression - decompression model (F k,p ) with a compression factor (Q k,p ) per batch and said production phase comprising at least the following steps: -) taking at least one primary image of at least one object in production; -) dividing each primary image into secondary images (S k,p ); -) applying the compression - decompression model and the compression factor defined in the learning phase to each secondary image (S k,p ) so as to form a reconstructed secondary image (R k,p ); -) computing the reconstruction error of each reconstructed secondary image R k,p ; -) assigning one or more scores per object based on the reconstruction errors; -) determining whether or not the produced object successfully passes the quality inspection based on the one or more assigned scores. said quality inspection comprising a learning phase and a production phase, said learning phase comprising at least the following steps: -) producing N objects considered to be acceptable; -) taking at least one reference primary image (A k ) of each of the N objects; -) dividing each reference primary image (A k ) into (P k ) reference secondary images (S k,p ); -) grouping the corresponding reference secondary images into batches of N images; -) determining a compression - decompression model (F k,p ) with a compression factor (Q k,p ) per batch and said production phase comprising at least the following steps: -) taking at least one primary image of at least one object in production; -) dividing each primary image into secondary images (S k,p ); -) applying the compression - decompression model and the compression factor defined in the learning phase to each secondary image (S k,p ) so as to form a reconstructed secondary image (R k,p ); -) computing the reconstruction error of each reconstructed secondary image R k,p ; -) assigning one or more scores per object based on the reconstruction errors; -) determining whether or not the produced object successfully passes the quality inspection based on the one or more assigned scores. -) producing N objects considered to be acceptable; -) taking at least one reference primary image (A k ) of each of the N objects; -) dividing each reference primary image (A k ) into (P k ) reference secondary images (S k,p ); -) grouping the corresponding reference secondary images into batches of N images; -) determining a compression - decompression model (F k,p ) with a compression factor (Q k,p ) per batch and said production phase comprising at least the following steps: -) taking at least one primary image of at least one object in production; -) dividing each primary image into secondary images (S k,p ); -) applying the compression - decompression model and the compression factor defined in the learning phase to each secondary image (S k,p ) so as to form a reconstructed secondary image (R k,p ); -) computing the reconstruction error of each reconstructed secondary image R k,p ; -) assigning one or more scores per object based on the reconstruction errors; -) determining whether or not the produced object successfully passes the quality inspection based on the one or more assigned scores. <EOS>