Biocorrosion in cheese shelving: failure detected by 3D pipeline

A silent collapse in a ripening chamber revealed the vulnerability of stainless steel structures to biocorrosion. A shelving unit loaded with tons of cheese gave way without warning. The failure originated at the welded joints, where the high-humidity and high-salinity environment caused a loss of cross-section invisible to traditional inspection methods. Subsequent analysis, supported by a 3D pipeline, allowed the disaster to be reconstructed and the real causes of the collapse to be understood.

3D Pipeline: from scanning to corrosion fatigue simulation 🧀

To address the failure, a multidisciplinary workflow was implemented. First, Pix4D was used to perform photogrammetry of the accident area, generating a high-density point cloud that captured the deformed geometry and affected surfaces. This cloud was imported into PolyWorks to align and compare the actual state with the original SolidWorks CAD model. The dimensional difference revealed a critical reduction in weld thickness, up to 40%. With this data, a fatigue simulation was run in SolidWorks Simulation, incorporating environmental conditions of relative humidity above 85% and chloride concentrations typical of cheese brine. The parametric model demonstrated that biocorrosion accelerated crack propagation, reducing the estimated service life of the structure from 20 years to just 3.

Lessons for the industry: what is not seen is simulated 🔬

This case demonstrates that routine visual inspections are insufficient in aggressive environments. The combination of photogrammetry and parametric modeling not only explains the failure but also allows for predicting future collapses. For similar infrastructure in the food industry, it is recommended to integrate a periodic 3D pipeline that scans critical joints and updates fatigue models. Simulation of materials under corrosion ceases to be a theoretical exercise and becomes a mandatory prevention tool.

Which surface roughness parameters and local curvature obtained from the 3D pipeline are more reliable predictors for early detection of biocorrosion pitting in stainless steel in the presence of dairy biofilms?

(PS: Material fatigue is like yours after 10 hours of simulation.)