Steel is one of the most important materials used in modern maritime vehicles. Modern production techniques make steel grades available that fulfill current requirements of these safety critical applications regarding their mechanical properties and their processing. However, constantly increasing demands on the quality and cost-effectiveness of steel products must be matched by the development and implementation of efficient testing methods.

This paper explores the possibility of using induction thermography as a non-destructive testing method for this measurement task. Therefore multiple experiments were conducted using representative pieces of steel in which defined artificial defects were incorporated through milling.


Ships, offshore constructions as well as autonomous or manned underwater crafts depend on a material quality that perfectly fits the needs of these safety critical applications. As of today steel remains one of the most important materials used in maritime construction. In order to minimize fatale failures in integral structures, the quality of semifinished steel products cannot be compromised by material defects. Material flaws within the product pose an increased challenge since the mainly applied optical testing methods throughout the production process are not able to detect defects without distinct visibility on the surface. Typically, near surface defects such as slivers and scabs are macroscopic non-visible on the hot rolled materials' surface. During the subsequent metal forming process some of these defects will break through the surface and become visible to the bare eye. Since this phenomenon is linked to the position of the flaw regarding high degrees of deformation of the formed part, large dimensional flaws can remain undetected.

In 2018 an estimated 1 682 million tons of hot rolled steel products have been produced globally, whereof 158 million tons are produced within the European Union (worldsteel, 2019). These dimensions require an online high-speed testing method, which allows a costefficient total area monitoring within the production process.

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