Fraunhofer IZFP @ EuroBLECH 2022: Quality assurance and reliable identification of sheet metal parts in production
Saarbrücken, October 13, 2022
Time-consuming destructive inspection processes for quality assurance result in huge costs due to damage or destruction of the products. Process deviations that are detected too late can lead to a considerable amount of scrap. Furthermore, clear identification and complete traceability of each object at any time during processing enables the optimization of product quality and resource efficiency, thus being essential prerequisites for the development of self-organizing value chains (I4.0). Fraunhofer IZFP experts will present solutions to both problems at EuroBLECH in Hannover from October 25 to 28, 2022 (Hall 27, Booth E8).
Due to production conditions conventional object markings, e.g. by labels and barcodes, usually do not remain permanently and undamaged on the sheet metal part. Optically detectable features of the component surface can only be exploited while the surface is not changed too much by forming, coating or machining. Thus, new sensory methods are required to detect features located within the component volume.
Markerless component identification
INSITU (Intrinsic Structural Analysis for Identification and Traceability of Formed Parts) is a novel electromagnetic method. It allows to detect characteristic (micro-) structural intrinsic features of the material that are preserved even after the surface is changed. The method is based on an inductive sensor array, which covers a component area of approx. 10 x 10 mm2. The resulting identification data is classified using machine learning methods, thus guaranteeing distinct identification of the sheet metal parts even after forming. This is supported by a digital object memory and the additional use of process and quality data in the feature space, which enables the prediction of feature changes. Currently, the measurement time is 3 seconds; a maximum measurement time of 0.5 seconds is targeted.
Material characterization in manufacturing and development with 3MA II
Conventional inspection methods such as residual stress measurements by X-ray diffraction, metallographic analyses and hardness indentation methods share a low testing speed and the destructive inspection character. This renders them widely inept for inspecting the surface layer properties during or immediately after a manufacturing step in the process chain. As a solution to this situation, non-destructive testing methods, such those developed and advanced by Fraunhofer IZFP, offer an alternative and, if implemented appropriately, a long-term replacement for X-ray or destructive methods. Micromagnetic inspection methods come with the potential for fast and non-destructive inspection of up to 100 percent of production during or immediately after a manufacturing step.
The 3MA II inspection method (Micromagnetic Multiparameter, Microstructure and Stress Analysis) developed by Fraunhofer IZFP essentially enables the characterization of surface layer properties. It can be fully automated and integrated directly into the manufacturing process. Its high inspection speed enables non-destructive 100 percent testing for most applications, thus allowing the rapid and simultaneous evaluation of several relevant quality characteristics of the surface layer (0 to 8 mm component depth). 3MA II combines four micromagnetic methods (Barkhausen noise, incremental permeability, analysis of the upper harmonics of the tangential magnetic field and multi-frequency eddy current). This is indispensable especially in case of the target quantities to be measured (e.g. hardness, hardness depth) and the disturbance quantities (temperature, residual stresses, etc.) can vary simultaneously. Thus, the influence of the disturbance variables is reduced or eliminated altogether.
Sensor and data systems for safety, sustainability and efficiency
Fraunhofer IZFP is an internationally networked research and development institute in the field of applied, industry-related research. The institute's activities zero in on the development of cognitive sensor and data systems for the non-destructive monitoring of industrial processes and value chains. We are pathfinders and pioneers in the transformation of classic non-destructive measurement and testing technology towards NDE 4.0. Our advanced sensor and data systems help to ensure a sustainable and efficient (material) recycling economy. These sensor and data systems decide providently and intelligently on their own on how to generate, process, forward and archive relevant information from their data.