A method for detecting anomalies in a cyclic manufacturing process; wherein an item is produced in one cycle (Zk, k=1...1) of the manufacturing process; and in which cycle (Zk, k=1...1) a cavity pressure (P) is measured; wherein, if there is an anomaly in cavity pressure (P), the item is a bad part (S); wherein in a first step (V1) of the method at least one chronological sequence of pressure values (Xkj, k=1...1, j=1...m) for at least one cycle (Zk, k=1...1) is provided; wherein in a second step (V2) of the method for each chronological sequence of pressure values (Xkj, k=1...1, j=1...m) at least one characteristic value (Kki, k=1...1, i=1...n) is automatically determined; wherein in a third step (V3) of the method the characteristic value (Kki, k=1...1, i=1...n) for a plurality of cycles (Zk, k=1...1) is automatically partitioned in at least one decision tree (Bi, i=1...n) and an average depth (Ti, i=1...n) of the decision tree (Bi, i=1...n) is automatically determined; wherein in a fourth step (V4) of the method a chronological sequence of further pressure values (Xj', j=1...m) in a further cycle (Z') is provided; wherein in a fifth step (V5) of the method at least one further characteristic value (Ki', i=1...n) is automatically determined for the chronological sequence of further pressure values (Xj', j=1...m); wherein in a sixth step (V6) of the method the further characteristic value (Ki', i=1...n) is automatically partitioned in at least one further decision tree (Bi', i=1...n) and a further depth (Ti', i=1...n) of the further decision tree (Bi', i=1...n) is automatically determined; and wherein in a seventh step (V7) of the method it is automatically determined whether for a characteristic value (Kki, k=1...1, i=1...n) and a further characteristic value (Ki', i=1...n) having the same characteristic value index (i) the further depth (Ti', i=1...n) of the further decision tree (Bi', i=1...n) is lower than the average depth (Ti, i=1...n) of the decision tree (Bi, i=1...n) and whether an anomaly in cavity pressure (P) exists. wherein in a first step (V1) of the method at least one chronological sequence of pressure values (Xkj, k=1...1, j=1...m) for at least one cycle (Zk, k=1...1) is provided; wherein in a second step (V2) of the method for each chronological sequence of pressure values (Xkj, k=1...1, j=1...m) at least one characteristic value (Kki, k=1...1, i=1...n) is automatically determined; wherein in a third step (V3) of the method the characteristic value (Kki, k=1...1, i=1...n) for a plurality of cycles (Zk, k=1...1) is automatically partitioned in at least one decision tree (Bi, i=1...n) and an average depth (Ti, i=1...n) of the decision tree (Bi, i=1...n) is automatically determined; wherein in a fourth step (V4) of the method a chronological sequence of further pressure values (Xj', j=1...m) in a further cycle (Z') is provided; wherein in a fifth step (V5) of the method at least one further characteristic value (Ki', i=1...n) is automatically determined for the chronological sequence of further pressure values (Xj', j=1...m); wherein in a sixth step (V6) of the method the further characteristic value (Ki', i=1...n) is automatically partitioned in at least one further decision tree (Bi', i=1...n) and a further depth (Ti', i=1...n) of the further decision tree (Bi', i=1...n) is automatically determined; and wherein in a seventh step (V7) of the method it is automatically determined whether for a characteristic value (Kki, k=1...1, i=1...n) and a further characteristic value (Ki', i=1...n) having the same characteristic value index (i) the further depth (Ti', i=1...n) of the further decision tree (Bi', i=1...n) is lower than the average depth (Ti, i=1...n) of the decision tree (Bi, i=1...n) and whether an anomaly in cavity pressure (P) exists. <EOS>