Laser polishing of additive laser manufacturing surfaces

Abstract

The additive laser manufacturing (ALM) technique is an additive manufacturing process which enables the rapid manufacturing of complex metallic parts and the creation of thin parts so as, for example, to decrease parts weight for biomechanical or aeronautic applications. Furthermore, compared with selective laser sintering technology, the ALM process allows creating more huge parts and material gradient. However, for aesthetic or tribological functions, the ALM surfaces need an additional finishing operation, such as the polishing operation. Polishing processes are usually based on abrasive or chemical techniques. These conventional processes are composed by many drawbacks such as accessibility of complex shape, environmental impact, high time consumption and cost, and health risks for operators. In order to solve these problems and to improve surface quality, the laser polishing (LP) process is investigated. Based on melting material by laser, laser polishing process enables the smoothing of initial topography. However, the ALM process and the laser polishing processes are based on laser technology. In this context, the laser ALM process is used directly on the same machine for the polishing operation. Moreover, an alternation between both processes can be established during the manufacturing operation in order to treat nonaccessible surfaces. Currently, few studies focus on laser polishing of additive laser manufacturing surfaces, and it tends to limit the industrial use of additive manufacturing technology. The proposed study describes an experimental investigation of laser polishing surfaces obtained by additive laser manufacturing process. The investigation results in the improvement of complete final surface quality, according to laser polishing parameters. This experimental study introduces the laser polishing of thin section parts, in order to develop laser polishing applications. According to a manufacturing chain context, the final objective is to create a multiprocess mastery in order to optimize the final topography and productivity time.