Revolutionizing Grain and Particle Size Measurement in Metals: The Role of Sensor-Assisted Metallographic Image Analysis

• Published in: Sensors (Basel, Switzerland) Vol. 24; no. 16; p. 5328
• Main Authors: Shirsat, Tushar, Bairagi, Vinayak, Buchade, Amar, Boonchieng, Ekkarat
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 17.08.2024; MDPI
• Subjects: Algorithms; Aluminum; Corrosion resistance; Failure analysis; Fuzzy logic; Grain boundaries; Grain size; Manufacturing; Mechanical properties; metallographic; Metals; Microscopy; Morphology; Particle size; particle size measurement; Quality control; Quality management; Quality standards; R&D; Research & development; revolutionizing grain; sensor-assisted; Steel alloys; Steel products; Tensile strength; revolutionizing grain; sensor-assisted; particle size measurement; metallographic
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s24165328

Metallographic image analysis is vital in the field of metal science due to its potential to automate the sensing process for grain and particle size estimation. To ensure the good quality and reliability of metal products, analysis of the integrity of metallic components is required. In contemporary manufacturing processes, microscopic analysis is a crucial step, mainly when complex systems like gearboxes, turbines, or engines are assembled using various components from multiple suppliers. A final product's quality, durability, and lifespan are determined via the quality analysis of properties of a material with proper tolerances. A flaw in a single component can cause the breakdown of the entire finished product. To ensure the good quality of a material, micro-structural analysis is necessary, which includes the routine measurement of inclusions. The particle and grain sizes of particulate samples are the most crucial physical characteristics of metals. Their measurement is routinely conducted across various industries, and they are frequently considered essential parameters in the creation of many products. This paper discusses the role of sensors in enhancing the accuracy and efficiency of metallographic image analysis, as well as the challenges and limitations associated with this technology. The paper also highlights the potential applications of sensor-assisted metallographic image analysis in various industries, such as aerospace, automotive, and construction. The paper concludes by identifying future research directions for this emerging field, including the development of more sophisticated algorithms for grain and particle size estimation, the integration of multiple sensors for more accurate measurements, and the exploration of new sensing modalities for metallographic image analysis.