Real-time smart sensing of surface integrity attributes in manufacturing applications

Surface integrity (SI) directly affects the functional performance, fatigue life, and corrosion resistance of engineering components, particularly in the automotive, textile, medical, and aerospace industries. This article covers a complete overview of methods for determining SI, such as surface roughness, hardness, and hydrophobicity. Micro-electro-mechanical systems-based characterization techniques such as stylus profilometry, optical profilometry, indentation-based hardness testing, contact angle measurements, and surface energy evaluation are systematically explained with working principles, advantages, and limitations. Development of artificial intelligence and machine learning technologies, such as image-based predictive models and materials/process parameters-based modeling techniques, is also discussed. These advanced techniques develop complex and nonlinear correlations between attributes of SI and surface parameters, which allow for automation, accuracy, and real-time prediction.