Designing Resilient Manufacturing Systems using Cross Domain Application of Machine Learning Resilience.

The COVID-19 pandemic and crises like the Ukraine-Russia war have led to numerous restrictions for industrial manufacturing due to interrupted supply chains, staff absences due to illness or quarantine measures, and order situations that changed significantly at short notice. These influences have exposed that it is crucial to address the issue of manufacturing resilience in the context of current disruptions. This can be plausibly guaranteed by subjecting the ML model of a manufacturing system to attacks deliberately designed to fool its prediction.

adhered on surfaces: Resistance of a seawater bacterium against shear forces under the influence of roughness, surface energy, and zeta potential of the surfaces.

Bacteria in flowing media are exposed to shear forces exerted by the fluid. Before a biofilm can be formed, the bacteria have to attach to a solid surface and have to resist these shear forces. Here, the authors determined dislodgement forces of single bacteria by means of lateral force microscopy.

Adhesion forces of the sea-water bacterium Paracoccus seriniphilus on titanium: Influence of microstructures and environmental conditions.

The bacterial attachment to surfaces is the first step of biofilm formation. This attachment is governed by adhesion forces which act between the bacterium and the substrate. Such forces can be measured by single cell force spectroscopy, where a single bacterium is attached to a cantilever of a scanning force microscope, and force-distance curves are measured.