R&D Tax Credit for Mechanical
Engineering

Industry-Specific Requirements in Mechanical Engineering

Mechanical engineering offers a particularly broad spectrum of eligible R&D activities. Prototyping costs frequently represent the largest single item: from the first concept sketch through 3D-printed functional prototypes to a fully operational test vehicle, all material, manufacturing and personnel costs are potentially eligible. The key point is that the prototype must not primarily serve series production preparation, but rather the overcoming of a technical uncertainty – such as validating a novel drive concept or testing an innovative kinematic design.

CAD/CAE-Simulationen werden von der BSFZ als vollwertige F&E-Tätigkeit anerkannt, sofern sie der Erforschung technischer Grenzbereiche dienen. FEM-Analysen (Finite-Elemente-Methode), CFD-Strömungssimulationen, Mehrkörpersimulationen und thermische Analysen sind typische Beispiele. Die Herausforderung liegt in der Dokumentation: Simulationsparameter, Randbedingungen, Konvergenzstudien und die Gegenüberstellung mit experimentellen Validierungsdaten müssen nachvollziehbar aufbereitet werden. Unsere Ingenieure unterstützen dabei, Simulationsberichte BSFZ-konform zu strukturieren.

Compliance with DIN and ISO standards (e.g. DIN EN ISO 12100 machine safety, ISO 13849 control system safety) generates extensive technical documentation that is ideally suited as R&D evidence. Material tests per DIN EN 10002 (tensile test), fatigue strength tests, corrosion tests and wear analyses document the experimental character of the development. Standard conformity assessments frequently require iterative test series – precisely the systematic approach the FZulG promotes.

Particularly in special-purpose machine construction and customised systems, the R&D share often amounts to 40–60% of total development costs. If your engineering department regularly develops solutions not available on the market, the funding prospects are very good. Development of predictive maintenance systems, integration of IoT sensors into existing machines, and automation of complex manufacturing processes are also frequently eligible.

Eligible R&D Projects in Mechanical Engineering

German mechanical engineering is one of the most innovative industries worldwide – and accordingly offers diverse starting points for the R&D Tax Credit. From researching new manufacturing processes to integrating intelligent sensors into existing machine concepts: the following project types are regularly recognised by the BSFZ as eligible R&D.

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Additive Manufacturing for Metal Components

Researching additive manufacturing processes for load-bearing metal components is a prime example of eligible R&D in mechanical engineering. Typical projects include developing novel printing parameters for previously unprocessable alloys (e.g. high-strength titanium alloys for turbine blades), researching hybrid manufacturing strategies combining conventional machining with laser powder bed fusion, and qualifying additively manufactured parts for safety-critical applications. A NOVARIS client – a special-purpose machine builder with 120 employees – developed an SLM process (Selective Laser Melting) for topology-optimised gripper systems intended to achieve full strength at half the weight. The technical uncertainty lay in whether the anisotropic material properties of the layer-by-layer built material could meet the required fatigue strength values under cyclic loading. The BSFZ fully recognised the project as experimental development, resulting in a research allowance of €85,000 per year.

Predictive Maintenance with Machine Learning Integration

Developing predictive maintenance systems combines classical mechanical engineering with cutting-edge data analytics and offers substantial funding potential. Eligible projects include those researching novel sensor concepts for condition monitoring of machine tools (e.g. structure-borne sound-based wear detection on spindle bearings), developing ML algorithms for anomaly detection in vibration spectra, or training domain-specific remaining useful life models that work with limited field training data. The technical challenge often lies in the fact that failures rarely occur in practice, providing scarce labelled data for supervised learning – necessitating research into semi-supervised or transfer-based learning methods. NOVARIS has supported several mechanical engineering companies in documenting such interdisciplinary projects so that both the mechanical and software-related R&D components became fully eligible.

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Novel Actuator and Sensor Development

Developing novel actuators and sensors for mechanical engineering applications is a core area of eligible R&D. Hierzu zählen die Erforschung piezoelektrischer Aktoren mit höheren Stellwegen für Präzisionspositionierung, die Entwicklung faseroptischer Dehnungssensoren zur In-situ-Strukturüberwachung von Großanlagen oder die Konzeption magnetorheologischer Dämpfungssysteme für adaptive Schwingungsisolierung. A machine tool manufacturer developed, with NOVARIS support, a novel capacitive sensor for non-contact measurement of tool wear during the machining process. Since no known measurement methods could guarantee the required resolution of under 5 micrometres under the harsh conditions of a CNC milling machine (coolant, chips, vibrations), the project was recognised as industrial research – the highest funding category.

Industry 4.0 – Digital Twins and Connected Production

Developing digital twins for production systems is a growing field with high R&D content. Eligible projects particularly include those coupling physics-based simulation models with real-time production data to predict dynamic machine behaviour. This includes researching reduced order models (ROM) that approximate complex FEM simulations in real time, developing self-calibrating digital twins that automatically adapt to changing operating conditions, and designing interoperable data models following the Asset Administration Shell concept. The technical uncertainty regularly concerns whether the simplified models can deliver sufficient prediction accuracy for process-critical decisions. NOVARIS supports mechanical engineering companies in highlighting the R&D character of these digitalisation projects and clearly distinguishing them from routine IT integration.

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Unser Tipp: Im Maschinenbau werden häufig Entwicklungsprojekte durchgeführt, die als „normale Konstruktionsarbeit" eingestuft werden, obwohl sie echte technische Unsicherheiten überwinden. Unsere Ingenieure identifizieren in Erstgesprächen regelmäßig 40–60 % mehr förderfähige Projektanteile, als die Unternehmen selbst einschätzen.