Further development of manufacturing technology, in particular machining requires the search for new innovative technological solutions. This applies in particular to the advanced processing of measurement data from diagnostic and monitoring systems. The increasing amount of data collected by the embedded measurement systems requires development of effective analytical tools to efficiently transform the data into knowledge and implement autonomous machine tools of the future. This issue is of particular importance to assess the condition of the tool and predict its durability, which are crucial for reliability and quality of the manufacturing process. Therefore, a mathematical model was developed to enable effective, real-time classification of the cutting blade status. The model was verified based on real measurement data from an industrial machine tool.
The results of experimental investigations on the effect of the oil pockets existence on seizure resistance of sliding elements are presented. Seizure tests were conducted with block-on-ring apparatus at increasing pressure. The stationary block (counter specimen) contacted the rotating steel ring (specimen). The tested assemblies were lubricated by oil L-AN 46, which was heated to 30°C before each experiment. The sliding was unidirectional. The block was a part of a bearing sleeve-hardened EN-GJS 400-15 cast iron with a hardness value of 50 HRC. The ring samples, 35 mm in diameter, were made from hardened 42CrMo4 steel of hardness 32 HRC. The friction force and temperature near the contact zone were measured during the tests. Some variants of specimen surfaces were created by burnishing technique. They were characterised by the oil pocket density, the holes depth, length, and width. The oil pockets existence of area density of 10% on the ring surface improved seizure resistance of the sliding pair steel-cast iron for speed of 0.27 m/s. The pit shape and orientation are very important, too.
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