OBRABOTKAMETALLOV Vol. 23 No. 4 2021 31 TECHNOLOGY References 1. Wejrzanowski T., Spychalski W., Różniatowski K., Kurzydłowski K. Image based analysis of complex microstructures of engineering materials. International Journal of Applied Mathematics and Computer Science , 2008, vol. 18 (1), pp. 33–39. 2. Samuels L.E. Light microscopy of carbon steels . Materials Park, Ohio, ASM International, 1999. 3. Schwartz A.J., Kumar M., Adams B.L., Field D.P. Electron backscatter diffraction in materials science. 2nd ed. New York, Springer US Publ., 2009. 403 p. ISBN 978-0-387-88135-5. DOI: 10.1007/978-0-387-88136-2. 4. Krauss G. Steels: processing, structure, and performance . Materials Park, Ohio, ASM International, 2015. Application of digital image processing technique in the microstructure analysis and the machinability investigation Manojkumar Sheladiya 1, 2, a,* , Shailee Acharya 3, b , Ashish Kothari 2, c , Ghanshyam Acharya 4, d 1Gujarat Technological University, Ahmedabad, 382424, India 2Atmiya University, Faculty of Engineering & Technology, Yogidham Gurukul, Kalawad Road, Rajkot, 360005, India 3Sardar Vallabhbhai Patel Institute of Technology, Affiliated to GTU, Vasad, 388306, India 4Atmiya Institute of Technology and Science, Yogidham Gurukul, Kalawad Road, Rajkot, 360005, India a https://orcid.org/0000-0002-9154-3355, mvsheladiya@gmail.com, b https://orcid.org/0000-0001-6428-8961, shailee.acharya@gmail.com, c https://orcid.org/0000-0002-1981-8465, amkothari.ec@gmail.com, d https://orcid.org/0000-0002-3580-3116, gdacharya@rediffmail.com Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science. 2021 vol. 23 no. 4 pp. 21–32 ISSN: 1994-6309 (print) / 2541-819X (online) DOI: 10.17212/1994-6309-2021-23.4-21-32 Obrabotka metallov - Metal Working and Material Science Journal homepage: http://journals.nstu.ru/obrabotka_metallov ARTICLE INFO Article history : Received: 11 July 2021 Revised: 30 July 2021 Accepted: 07 September 2021 Available online: 15 December 2021 Keywords : Machinability Index ASTMA 48 Class 20 K-means clustering Mould-metal interface Acknowledgment The group of authors is much obligated to the Krislur Castomech Pvt. Ltd., Bhavanagar, Gujarat, India for availing the facility for the experimentation. ABSTRACT Introduction. The world is at the stage of creating an interdisciplinary approach that will be implemented in metallurgical research. The paper formulates the technique of image analysis in the study of processing at different depths from the mold-metal interface. The purpose of the work. Processing of a cast-iron workpiece within the first 3.5 mm of thickness from the mold-metal interface is a serious problem of solid processing. The study of machinability at different depths is a key requirement of the industry for ease of processing. Machinability will determine a number of factors, including tool consumption, workpiece surface quality, energy consumption, etc. The method of investigation. Image analysis is performed to determine the percentage of graphite in etched and non-etched samples. K -means clustering allows to create a new image from a given one with a clear separation of white and black areas by converting a digital image into a binary image using a threshold value for segmentation. The volume fraction of perlite, the volume fraction of graphite and the average size of graphiteflakes in microns are used as input variables for the machinability of cast iron. Results and discussion. The output, that is, the segmented image, will be the input function for calculating the workability index using formulas. Thus, microstructural analysis will help predict the workability index of grey cast iron ASTM A48 Class 20. Using this method and the program, based on the microstructure, it is possible to predict in advance the characteristics of the machining of the part, taking into account possible changes in the casting process itself. For citation: SheladiyaM.V.,Acharya S.G., KothariA.M.,Acharya G.D.Application of digital image processing technique in the microstructure analysis and the machinability investigation. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science , 2021, vol. 23, no. 4, pp. 21–32. DOI: 10.17212/1994-6309-2021-23.4-21-32. (In Russian). ______ * Corresponding author Sheladiya Manojkumar V. , M.Tech.(Engineering), Assistant Professor Atmiya University, Faculty of Engineering & Technology, Yogidham Gurukul, Kalawad Road, 360005, Rajkot, Gujarat, India. Tel.: +91-9898278267, e-mail: mvsheladiya@gmail.com
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