Polishing of additive manufactured metallic components: retrospect on existing methods and future prospects

• Published in: International journal of advanced manufacturing technology 2022-07, Vol.121 (1-2), p.83-125
• Main Authors: Boban, Jibin, Ahmed, Afzaal, Jithinraj, E. K., Rahman, M. Azizur, Rahman, Mustafizur
• Format: Article
• Language: English
• Subjects: Abrasive finishing; Additive manufacturing; Ambience; Artificial intelligence; CAE) and Design; Chemical polishing; Computer-Aided Engineering (CAD; Critical Review; Customization; Electric discharges; Electropolishing; Engineering; Industrial and Production Engineering; Machine learning; Manufacturing; Mechanical Engineering; Media Management; Near net shaping
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-022-09382-y

Additive manufacturing (AM) is an advanced near net shape manufacturing technology that facilitates the formation of complex shaped products from a digital 3D design. Freedom of design, minimal scrap formation, and mass customization make AM technology dominant over conventional methods. Recently, metal additive manufacturing (MAM) gained ambience owing to the ever-increasing demand for complex and customized metallic parts/components in aerospace, biomedical, automotive and marine industries. However, the parts/components produced by MAM cannot be directly employed in practical applications due to the poor surface integrity and loss of dimensional accuracy. Metallic AM surfaces are characterized by staircase effect, balling phenomena, lack of fusion defects, porosities and cracks. In order to overcome the aforementioned problems, several post-processing methods have been introduced by researchers over the years. These include laser polishing, abrasive finishing, chemical and electrochemical polishing, conventional finishing, electrical discharge polishing, and some other hybrid methods. The principle of operation, significant outcomes in terms of surface modification as well as pros and cons of each of these methods are discussed in detail in this review article. The comprehensive outlook of the paper establishes a foundation of reference for future research works in the area of post-processing metallic AM components. Moreover, the future path of research ahead in the domain of post-processing methods has been discussed with special attention on automation of finishing methods using machine learning and artificial intelligence.