The evaluation of wear progress of gear tooth flanks made of 16MnCr5 was performed using non-destructive micro-magnetic testing, specifically Barkhausen noise (BN) and incremental permeability (IP). Based on the physical interaction of the microstructure with the magnetic field, the micro-magnetic characterization allowed the analysis of changes of microstructure caused by wear, including phase transformation and development of residual stresses. Due to wide parameter variation and application of bandpass filter frequencies of micro-magnetic signals, it was possible to indicate and separate the main damage mechanisms considering the wear development. It could be shown that the maximum amplitude of BN correlates directly with the profile form deviation and increases with the progress of wear. Surface investigations via optical and scanning electron microscopy indicated strong surface fatigue wear with micro-pitting and micro-cracks, evident in cross-section after 3 × 10⁵ cycles. The result of fatigue on the surface layer was the decrease of residual compression stresses, which was indicated by means of coercivity by BN-analysis. The different topographies of the surfaces, characterized via confocal white light microscopy, were also reflected in maximum BN-amplitude. Using complementary microscopic characterization in the cross-section, a strong correlation between micro-magnetic parameters and microstructure was confirmed and wear progress was characterized in dependence of depth under the wear surface. The phase transformation of retained austenite into martensite according to wear development, measured by means of X-ray diffraction (XRD) and electron backscatter diffraction (EBSD) was also detected by micro-magnetic testing by IP-analysis.

In continuous casting processes, inevitable voids (damage) are generated inside the material. The subsequent forming process of hot flat rolling offers the potential of healing these defects by closing the voids and bonding the internal surfaces. In this paper, different forming conditions from hot flat rolling process were characterized with micromagnetic measurement techniques and the influence of the damage evolution on the fatigue behavior was investigated. To characterize the reduction of voids through hot flat rolling processes, nondestructive testing techniques are required. Therefore, micromagnetic measurements such as Barkhausen noise, incremental permeability, and harmonic analysis were carried out, correlated with the number of voids, and compared with each other. The influence of damage evolution of different forming conditions on the fatigue behavior was characterized based on instrumented constant amplitude and multiple amplitude (load increase) tests. A significant increase in fatigue strength due to the hot flat rolling process, which leads to a reduction in the number of voids, was observed. In addition, the fracture surfaces of the specimens were analyzed in the scanning electron microscope.

The production of complex multi-functional, high-strength parts is becoming increasingly important in the industry. Especially with small batch size, the incremental flow forming processes can be advantageous. The production of parts with complex geometry and locally graded material properties currently depicts a great challenge in the flow forming process. At this point, the usage of closed-loop control for the shape and properties could be a feasible new solution. The overall aim in this project is to establish an intelligent closed-loop control system for the wall thickness as well as the α’-martensite content of AISI 304L-workpieces in a flow forming process. To reach this goal, a novel sensor concept for online measurements of the wall thickness reduction and the martensite content during forming process is proposed. It includes the setup of a modified flow forming machine and the integration of the sensor system in the machine control. Additionally, a simulation model for the flow forming process is presented which describes the forming process with regard to the plastic workpiece deformation, the induced α’-martensite fraction, and the sensor behavior. This model was used for designing a closed-loop process control of the wall thickness reduction that was subsequently realized at the real plant including online measured feedback from the sensor system.

This paper evaluates the suitability of the X-ray diffraction (XRD) technique to characterize the phase transformation during the metal forming of the metastable austenitic steel AISI 304L. Due to plastic deformation, phase transformation from γ-austenite into α′-martensite occurs. The XRD peaks at specific 2θ diffraction angles give information about the phase amount. Analyses of the results with different characterization techniques such as microscopic analysis, including electron backscatter diffraction (EBSD), macro- and microhardness tests and magneto-inductive measurements of α′-martensite, were carried out. A qualitative and quantitative correlation to compute the amount of α′-martensite from the XRD measurements was deduced. XRD was validated as a suitable technique to characterize the phase transformation of metastable austenites. Additional data could provide necessary information to develop a more reliable model to perform a quantitative analysis of the phases from XRD measurements.

This paper deals with micromagnetic measurements for online detection of strain‐induced α′‐martensite during plastic deformation of metastable austenitic steel AISI 304L. The operating principles of the sensors are magnetic Barkhausen noise (MBN) and eddy currents (EC), which are suitable for detection of microstructure evolution due to formation of ferromagnetic phases. The focus of this study was put on the qualification of different micromagnetic techniques and different measurement systems under conditions similar to the real ones during production, which is crucial for implementation of a property‐controlled flow forming process. The investigation was carried out on tubular specimens produced by flow forming, which have different content of α′‐martensite. To characterize the sensitivity of the sensors, different contact conditions between sensors and workpieces were reproduced. MBN sensors are suitable for detecting amount of α′‐martensite, but the measurements are affected by the surface roughness. This entails that the calibration models for MBN sensors must take account of these effects. EC sensors show a closer match with the amount of α′‐martensite without having major affectation by other effects.