Development of New Technique for Reverse Engineering by Microstructure Features Detection

Subject Areas :

Ahmed Hebatalrahman ¹

1 - Dr. Eng., Consultant in Material Science, Egypt

Received: 2022-05-10 Accepted : 2022-07-13 Published : 2022-05-01

Keywords: detection, Microstructure, quantitative, Reverse engineering, qualitative, Software,

Abstract :

Reverse Engineering in the field of material science is considered one of the most important topics, The process is very complicated and depends on different factors. In this work, new software was developed to calculate the microstructure features of metals and alloys such as grain size number, the average diameter of grain, number of particles per unit area, and number of particles per unit volume. The volume fraction and the terms related to volume fraction such as shape factor, edge-to-edge spacing, and distribution of secondary phases were detected by the point count technique. Both quantitative and qualitative analyses were done. The microstructure features were calculated for the selected samples and compared with the standard photos stored in the program, The comparison depends mainly on comparing each constituent characteristic. The chemical composition comparison was taken into account, The C++ and MATLAB environment were used as a tool in this work which can work under Windows or Linux. The new technique has different applications in metallurgy, industry, medicine, and alloy design.

References:

[1] Diógenes, A. N., Hoff, E. and Fernandes C. P. 2005. Grain size measurement by image analysis: An application on ceramic. 18th International Congress of Mechanical Engineering. Ouro Preto, Brazil.

[2] Grande, James. 2005. Crack Characterization Using Image Analysis. Microscopy Society of America, Cambridge University Press.

[3] Kehl, G. L. 1965. The Principles of Metallograhic Laboratory Practice. New Delhi: Indian reprint.

[4] Smith, W. F. 1993. Principles of Materials Science and Engineering. McGraw-Hill, Inc.

[5] Duda, R. O., Hart,  P. E. and Stork, D. G. 2000. Pattern Classification. 2nd Edition Wiley.

[6] Jain, A. K., Murty, M. N. and Flynn,  P.J. 1999. Data Clustering: A Review: ACM Computing Surveys. 31(3):264–323.

[7] Michael, L. H. 2007. Metallographic Interpretation of Steel Forging Defects. Microscopy Society of America, Cambridge University Press.

[8] Geels, K. 2006. Metallographic and Materialographic Specimen Preparation, Light Microscopy, Image Analysis and Hardness Testing. ASTM International.

[9] Vander Voort, G. F. 2005. Metallography and Microstructures, ASM Handbook, ASM International, Materials Park, Ohio, United States.

[10] Vander Voort, G. F. 1999.  Metallography: Principles and Practice, ASM International, Materials Park, Ohio, United States.

[11] Petzow, G. 1999. Metallographic Etching, 2nd Edition. ASM International, United States.

[12] Bjerregaard, L., Geels, K., Ottesen, B. and Rückert, M. 1999. Metalog Guide. Struers Ltd. Copenhagen, Denmark.

[13] Underwood, E. E. 1970. Quantitative Stereology. Addison-Wesley. Boston, Massachusetts, United States.