Modeling and Optimization of Laser Polishing Process (original) (raw)
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Topography modeling of laser polishing on AISI 316L milled surfaces
Mechanics & Industry, 2014
Laser polishing is a finishing process based on melting material, with the objective of improving surface topography. Some operating parameters must be taken into consideration, such as laser power, feed rate, offset, and overlap. Moreover, because of its dependence on the primary process, the initial topography has also an impact on the final result. This study describes a quadratic model, conceived to optimize final topography according to the primary process and laser polishing. Based on an experimental matrix, the model takes into account both laser operating parameters and the initial topography, in order to predict polished surfaces and to determine an optimal set of parameters. Furthermore, uncertainties linked to the measuring device need to be taken into consideration, as well as the process variability, in order to facilitate the interpretation of the results. After the phase of experimentation and the creation of the quadratic model, an optimal final topography is introduced, taking into account the initial surface and the laser parameters. Finally, in order to reduce the time process, it is important to study the impact of laser polishing strategy on the surface roughness.
International Journal of Manufacturing Research, 2020
The manufacturing chain is usually made of several processes, to create the final surface with regard to design specifications. Manufacturing processes are composed by a complex database, which contains the operating parameters and their settings combinations that impact on the surface parameters. This database may be composed by measured values and it is important to determine the non-measured values through modelling methods to master the final result. This paper aims at establishing a protocol to determine the laser polishing operating parameters for milled and additive lasermanufactured primary surfaces. Several experiments enable to propose models coming from polynomial regression calculus. The proposed models are 88-99% correlated with experiments and the laser polishing parameter enables to bring the initial surface roughness down to 99%. Finally, experiments and models are integrated into a global database to select the laser polishing process parameters regarding both initial milled and additive laser-manufactured surfaces.
Optimization of Process Parameters for the Laser Polishing of Hardened Tool Steel
Materials
In mold making, the mold surface roughness directly affects the surface roughness of the produced part. To achieve surface roughness below 0.8 μm, the cost of surface finish is high and time-consuming. One alternative to the different grinding and polishing steps is laser polishing (LP). This study investigates and models the LP of tool steel (X38CrMoV5-1-DIN 1.2343), typical for the mold industry, having an initial rough surface obtained by electrical discharge machining. The microstructures of the re-melted layer and heat-affected zone due to the LP process were also studied. Four parameters: the laser spot size, velocity, maximum melt pool temperature and overlapping were investigated via a design of experiments (DoE) approach, specifically a factorial design. The responses were line roughness (Ra), surface roughness (Sa), and waviness (Wa). The surface topography was measured before and after the LP process by white light profilometer or confocal microscopy. DoE results showed t...
Materials
Metal parts produced by additive manufacturing often require postprocessing to meet the specifications of the final product, which can make the process chain long and complex. Laser post-processes can be a valuable addition to conventional finishing methods. Laser polishing, specifically, is proving to be a great asset in improving the surface quality of parts in a relatively short time. For process development, experimental analysis can be extensive and expensive regarding the time requirement and laboratory facilities, while computational simulations demand the development of numerical models that, once validated, provide valuable tools for parameter optimization. In this work, experiments and simulations are performed based on the design of experiments to assess the effects of the parametric inputs on the resulting surface roughness and heat-affected zone depths. The data obtained are used to create both linear regression and artificial neural network models for each variable. Th...
Laser polishing of additive laser manufacturing surfaces
Journal of Laser Applications, 2015
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 sm...
Predicting laser polishing outcomes at edge features
The field of laser polishing has grown to include many strategies and materials, but several barriers remain to widespread commercialization of this technology, one being a lack of predictive capability of how laser polishing affects part edge features. The objective of the present work is to present a method of predicting this change in edge geometry and compare the results with experimental observation of laser polishing on blunt, square, and sharp edges. This was done by measuring the edge geometry before and after polishing using optical focus-variation metrology and comparing this with a prediction from a laser polishing simulation. The results showed good agreement in the edge rounding behavior between simulation and experiment except for an asymmetry of the observed polished edge at higher power that is not captured in the capillary smoothing model. This indicates that the present model can act as a good model for predicting edge rounding at lower power conditions, but additional capability in predicting material buildup and displacement at higher power needs to be added for fully pre-dictive capability. V C 2017 Laser Institute of America. [http://dx.doi.org/10.2351/1.4976560\]
Pulsed laser micro polishing: Surface prediction model
Journal of Manufacturing Processes, 2012
This project is focused on developing physics-based models to predict the outcome of pulsed laser micro polishing (PLµP). Perry et al. [1-3] have modeled PLµP as oscillations of capillary waves with damping resulting from the forces of surface tension and viscosity and a one-dimensional spatial frequency domain analysis was proposed. They have also proposed a critical spatial frequency, f cr , above which a significant reduction in the amplitude of the spatial Fourier components is expected. The current work extends the concept of critical frequency to two dimensional spatial frequency analysis of PLµP. We propose a physics-based prediction methodology to predict the spatial frequency content and surface roughness after polishing, given the features of the original surface, the material properties, and laser parameters used for PLµP. The proposed prediction methodology was tested using PLµP line polishing data for stainless steel 316L and area polishing results for pure Nickel, Ti6Al4V, and Al-6061-T6. The predicted average surface roughnesses were within 10% to 12% of the values measured on the polished surfaces. The results show that the critical frequency continues to be a useful predictor of polishing results in the 2-D spatial frequency domain. The laser processing parameters, as represented by the critical frequency, and the initial surface texture can be used to predict the final surface roughness before actually implementing PLµP.
Performance of laser polishing in finishing of metallic surfaces
The International Journal of Advanced Manufacturing Technology, 2014
Laser polishing is presently regarded as one of the enabling technologies hoped to eventually replace the need for time-consuming and error-prone manual polishing operations which are often required by metallic surfaces. During laser polishing, a thin layer of material is being melted as a result of laser irradiation. Since molten metal is characterized by increased relocation capabilities, laser polishing is generally accompanied by a more or less significant decrease in the surface roughness. The primary objective of this study is to present a comprehensive snapshot of the advancements made over more than one decade with respect to theoretical and experimental investigation of laser polishing technology. However, in addition to the usual review of the state-of-theart in the field, the study places an increased emphasis on the finishing performance of the process, defined through the perspective of pre-and postpolishing surface roughness. The implementation of this metric with strong practical implications has revealed that under appropriate process parameters, certain classes of metallic materials can reduce their average surface roughness by more than 80 %, possibly to R a =5 nm. Nonetheless, a more rigorous and fundamental understanding of the intrinsic mechanisms underlying laser polishing remains one of the currently unfulfilled premises toward a wider industrial adoption of the process.
Mathematical modelling of influence functions in computer-controlled polishing: Part II
Applied Mathematical Modelling, 2008
Computer-controlled polishing (CCP) is commonly used to finish high-quality surfaces, such as optical lenses. Based on magnetorheological finishing (MRF), a mathematical model to calculate the polishing tool characteristic (influence function) was developed and verified experimentally. The second part of this paper describes the calculation of the distribution of material removal within the size of an influence function and is based on Preston's fundamental polishing equation. The complete influence function model was implemented using MATLAB. The result is a user-friendly and easy-to-use software tool that enables fast computation of MRF influence functions without the current cumbersome determination procedure, and thus gives improved and more economical production of high-quality surfaces.