Laser power based surface characteristics models for 3-D printing process

Selective laser melting (SLM) is one of the important 3-D Printing processes that builds components of complex 3D shapes directly from the metal powder. It is widely used in manufacturing industries and is operated on significant amount of laser power drawn from the electric grid. The literature reveals that the properties such as surface roughness, waviness, tensile strength and dimensional accuracy of an SLM fabricated parts, depend on the laser power and can be improved by its appropriate adjustment. Determination of accurate values of laser power and the other inputs could lead to an improvement in energy efficiency and thus contributing to a clean and healthy environment. For determining the accurate value of laser power in achieving the required surface characteristics, the formulation of generalized mathematical models is an essential pre-requisite. In this context, an artificial intelligence approach of multi-gene genetic programming (MGGP) which develops the functional expressions between the process parameters automatically can be applied. The present work introduces an ensemble-based-MGGP approach to model the SLM process. Experiments on the SLM process with measurement of surface characteristics, namely surface roughness and waviness, based on the variations of laser power and other inputs are conducted, and the proposed ensemble-based-MGGP approach is applied. Statistical evaluation concludes that the performance of the proposed approach is better than that of the standardized MGGP approach. Sensitivity and parametric analysis conducted reveals the hidden relationships between surface characteristics and the laser power, which can be used to optimize the SLM process both economically and environmentally.     

Study of the hinge thickness deviation for a 316L parallelogram flexure mechanism fabricated via selective laser melting

3D printing offers great potential for developing complex flexure mechanisms. Recently, thickness-correction factors (TCFs) were introduced to correct the thickness and stiffness deviations of powder-based metal 3D printed flexure hinges during design and analysis. However, the reasons for the different TCFs obtained in each study are not clear, resulting in a limited value of these TCFs for future design and fabrication. Herein, the influence of the porous layer of 3D printed flexure hinges on the hinge thickness is investigated. Samples of parallelogram flexure mechanisms (PFMs) were 3D printed using selective laser melting (SLM) and 316L stainless steel powder. A 3D manufacturing error analysis was completed for each PFM sample via 3D scanning, surface roughness measurement and morphological observation. The thickness of the porous layer of the flexure hinge was independent of the designed hinge thickness and remained close to the average powder particle diameter. The effective hinge thickness could be estimated by subtracting twice the value of the porous layer thickness from the designed value. Guidelines based on finite element analysis and stiffness experiments are proposed. The limitations of the presented method for evaluating the effective hinge thickness of flexure hinges 3D printed via SLM are also discussed.

     

Robust beam compensation for laser-based additive manufacturing

Today’s software for laser-based additive manufacturing compensates for the finite dimensions of the laser spot by insetting the contours of a solid part. However, features having smaller dimensions are removed by this operation, which may significantly alter the structure of thin-walled parts. To avoid potential production errors, this work describes in detail an algorithmic framework that makes beam compensation more reliable by computing laser scan paths for thin features. The geometry of the features can be adjusted by the scan paths by means of five intuitive parameters, which are illustrated with examples. Benchmarks show that the scan path generation comes at a reasonable cost without altering the computational complexity of the overall beam compensation framework. The framework was applied to Selective Laser Melting (SLM) to demonstrate that it can significantly improve the robustness of additive manufacturing. Besides robustness, the framework is expected to allow further improvements to the accuracy of additive manufacturing by enabling a geometry-dependent determination of the laser parameters.     

Effect of imprinting times and stress annealing on warm laser shock imprinting

The rapid development of mechanical systems’ miniaturization has expanded the demand for higher precision and performance micro formed parts. For improving the forming height and quality of formed parts, and studying the influences of the stress annealing and imprinting times on the forming as well as surface roughness (Sa) of the formed parts, this paper proposed a composite process of imprinting times and stress annealing on warm laser shock imprinting (WLSI) to realize the precision forming of the aluminium foil. In this research, the WLSI experiments were carried out with the imprinting temperature, imprinting times, and stress annealing treatment as variables. Subsequently, the forming height, surface roughness, and surface oxidation of the formed parts were measured, the loading–displacement curve were monitored, the transient deformation process induced by WLSI was divided four stages (deformation stage, rebound stage, vibration stage, and stable stage), and the residual stress distribution of the formed parts were simulated and analyzed by ABAQUS. Finally, the influences of the above three factors on the formed parts were discussed and explicated, and these results showed that the imprinting times and stress annealing can improve effectively the forming effect of WLSI.

     

Recurrent ANN-based modelling of the dynamic evolution of the surface roughness in grinding

Grinding is critical in modern manufacturing due to its capacity for producing high surface quality and high-precision parts. One of the most important parameters that indicate the grinding quality is the surface roughness (R _a). Analytical models developed to predict surface finish are not easy to apply in the industry. Therefore, many researchers have made use of artificial neural networks. However, all the approaches provide a particular solution for a wheel–workpiece pair, not generalizing to new grinding wheels. Besides, these solutions do not give surface roughness values related to the grinding wheel status. Therefore, in this work the modelling of the dynamic evolution of the surface roughness (R _a) based on recurrent neural networks is presented with the capability to generalize to new grinding wheels and conditions taking into account the wheel wear. Results show excellent prediction of the surface finish dynamic evolution. The absolute maximum error is below 0.49 µm, being the average error around 0.32 µm. Besides, the analysis of the relative importance of the inputs shows that the grinding conditions have higher influence than the wheel characteristics over the prediction of the surface roughness confirming experimental knowledge of grinding technology users.

     

Digital twin-driven surface roughness prediction and process parameter adaptive optimization

In the process of parts machining, the real-time state of equipment such as tool wear will change dynamically with the cutting process, and then affect the surface roughness of parts. The traditional process parameter optimization method is difficult to take into account the uncertain factors in the machining process, and cannot meet the requirements of real-time and predictability of process parameter optimization in intelligent manufacturing. To solve this problem, a digital twin-driven surface roughness prediction and process parameter adaptive optimization method is proposed. Firstly, a digital twin containing machining elements is constructed to monitor the machining process in real-time and serve as a data source for process parameter optimization; Then IPSO-GRNN (Improved Particle Swarm Optimization-Generalized Regression Neural Networks) prediction model is constructed to realize tool wear prediction and surface roughness prediction based on data; Finally, when the surface roughness predicted based on the real-time data fails to meet the processing requirements, the digital twin system will warn and perform adaptive optimization of cutting parameters based on the currently predicted tool wear. Through the development of a process-optimized digital twin system and a large number of cutting tests, the effectiveness and advancement of the method proposed in this paper are verified. The organic combination of real-time monitoring, accurate prediction, and optimization decision-making in the machining process is realized which solves the problem of inconsistency between quality and efficiency of the machining process.     

Control of the quality of laser surface texturing

Since the conception of the first lasers in the 60’s, the knowledge and consequently the applications of laser have been widely increased. Laser surface texturing is a specific field among the various applications of the laser. This technique is employed in the aim of improving tribological performances for instance. This paper presents the laser surface texturing of a heterogeneous material. This material is lamellar cast iron. It has been chosen for its good friction properties. The textured surface is composed of grooves or dimples. The dimensions are micrometric. For the grooves, different cross sections have been engraved: semicircular, rectangular, trapezoidal and triangular. The dimples are cylindrical. All these laser textured surfaces are engraved with the laser manufacturing machine: DML 40 SI of Gildemeister (Germany). This machine is equipped with a galvanometric scanner, which allows tilted surfaces to be engraved. Various machining strategies and the following results are discussed in function of the different desired laser surface texturing results. In addition, to increase the aspect of the engraved surfaces, laser polishing is employed. Thanks to a defocalisation of the laser beam on the surface, the material is not ablated but melted. To be able to compare the different laser machining process, several techniques of control have been used: roughness profilometry, scanning electron microscopy and non contacting optical measurement. The rules of use of these methods must be defined bearing in mind their inherent limitations.     

Laser polishing and 2PP structuring of inside microfluidic channels in fused silica

This study presents the development of post-processing steps for microfluidics fabricated with selective laser etching (SLE) in fused silica. In a first step, the SLE surface—even inner walls of microfluidic channels—can be smoothed by laser polishing. In addition, two-photon polymerization (2PP) can be used to manufacture polymer microstructures and microcomponents inside the microfluidic channels. The reduction in the surface roughness by laser polishing is a remelting process. While heating the glass surface above softening temperature, laser radiation relocates material thanks to the surface tension. With laser polishing, the RMS roughness of SLE surfaces can be reduced from 12 µm down to 3 nm for spatial wavelength λ < 400 µm. Thanks to the laser polishing, fluidic processes as well as particles in microchannels can be observed with microscopy. A manufactured microfluidic demonstrates that SLE and laser polishing can be combined successfully. By developing two-photon polymerization (2PP) processing in microchannels we aim to enable new applications with sophisticated 3D structures inside the microchannel. With 2PP, lenses with a diameter of 50 µm are processed with a form accuracy rms of 70 nm. In addition, this study demonstrates that 3D structures can be fabricated inside the microchannels manufactured with SLE. Thanks to the combination of SLE, laser polishing and 2PP, research is pioneering new applications for microfluidics made of fused silica.     

A prediction approach of SLM based on the ensemble of metamodels considering material efficiency,energy consumption,and tensile strength

Journal of Intelligent Manufacturing - As a rapid developing additive manufacturing (AM) technology, selective laser melting (SLM) provides a promising way for intelligent manufacturing. The SLM...     

基于SolidWorks的虚拟装配路径规划研究

在机械产品制造过程中,装配工作占有重要的地位,其成本可以占到制造成本的30%—50%。装配工作对产品的最终质量也有很大影响。虚拟装配可以提前模拟装配过程,对保障装配质量和最终产品质量有着重要的意义,机械手臂的应用也使得装配工作更可控。本文基于SolidWorks三维模型设计软件,利用SolidWorks提供的API接口,通过.NET编程语言控制机械手臂,对产品零件进行装配模拟、碰撞干涉检查和机械手臂运动空间路径规划,最终生成机械手臂装配最优路径,大大减少了人工对机械手臂运动的调试工作,提高了产品的最终质量,对加速制造业发展具有重要意义。     

A novel methodology of design for Additive Manufacturing applied to Additive Laser Manufacturing process

Nowadays, due to rapid prototyping processes improvements, a functional metal part can be built directly by Additive Manufacturing. It is now accepted that these new processes can increase productivity while enabling a mass and cost reduction and an increase of the parts functionality. However, the physical phenomena that occur during these processes have a strong impact on the quality of the produced parts. Especially, because the manufacturing paths used to produce the parts lead these physical phenomena, it is essential to considerate them right from the parts design stage. In this context, a new numerical chain based on a new design for Additive Manufacturing (DFAM) methodology is proposed in this paper, the new DFAM methodology being detailed; both design requirements and manufacturing specificities are taken into account. The corresponding numerical tools are detailed in the particular case of thin-walled metal parts manufactured by an Additive Laser Manufacturing (ALM) process.     

Process energy analysis and optimization in selective laser sintering

Additive manufacturing (AM) processes are increasingly being used to manufacture complex precision parts for the automotive, aerospace and medical industries. One of the popular AM processes is the selective laser sintering (SLS) process which manufactures parts by sintering metallic, polymeric and ceramic powder under the effect of laser power. The laser energy expenditure of SLS process and its correlation to the geometry of the manufactured part and the SLS process parameters, however, have not received much attention from AM/SLS researchers. This paper presents a mathematical analysis of the laser energy required for manufacturing simple parts using the SLS process. The total energy expended is calculated as a function of the total area of sintering (TAS) using a convex hull based approach and is correlated to the part geometry, slice thickness and the build orientation. The TAS and laser energy are calculated for three sample parts and the results are provided in the paper. Finally, an optimization model is presented which computes the minimal TAS and energy required for manufacturing a part using the SLS process.     

Micro-metalforming with silicon dies

 The introduction of forming technology into MEMS manufacturing demands forming dies being characterized by a high strength and hardness, a good microstructurability, a low surface roughness, and a high precision of the microgeometry to be molded. Silicon structured by lithography and etching processes meeting these requirements especially concerning precision and surface roughness. For micro-metalforming silicon dies with different structural dimensions (>1 μm) have been used. The microstructures could be molded in different materials using cold and superplastic embossing. The precision and surface quality of the formed parts correspond to the high quality of the microstructured die. Both the low surface roughness and the accurate edges of the silicon structures are nearly represented in the molded structures. However, in particular during cold embossing die wear or even die failure could be observed limiting the implementation of silicon for micro-metalforming.     

In-situ point cloud fusion for layer-wise monitoring of additive manufacturing

Additive manufacturing (AM) has received an increasing attention in the manufacturing sector, owing to its high-level design freedom and enhanced capability to produce parts with complex geometries. With advances in AM technologies, the role of AM has been shifting from rapid prototyping to viable production-worthy manufacturing of functional parts. However, AM processes are highly inconsistent, and the lack of quality assurance significantly hampers the broader adoption of AM. Most existing techniques for AM online monitoring focus on the detection of conspicuous defects, such as under-fills and cracks. They are limited in their ability to detect layer surface variations induced by miniature process shifts. The objective of this study is to develop a new layer-wise monitoring framework for AM quality assurance based on in-situ point cloud fusion. Specifically, online 3D structured-light scanning is used to capture the surface morphology from each printed layer. The collected point cloud is partitioned, and the morphological patterns in local regions are delineated with a new affinity measure to evaluate the conformity to the reference. A deep cascade model is further introduced to leverage the local affinities for the identification of abnormal patterns on the printed layers. Finally, a statistical control chart is constructed for process monitoring and the identification of miniature shifts. Simulation and real-world case studies using the fused filament fabrication (FFF) process are conducted, and experimental results have demonstrated the effectiveness of the developed framework. It has a great potential to be implemented in diverse AM processes with a wide variety of materials for mission-critical applications.     

基于金属熔覆三维成型的机械手指研究与设计

文中介绍了基于三维打印的激光熔覆技术(LMD),用于机械手指的成型和修复缺损部分。以金属表面强化与修复为工程应用背景,从理论分析和实验两个方面,研究激光熔覆再制造的工艺,通过大量的数据揭示多种工艺参数对成型质量的影响。在分析比较SLA、SLM、SLS技术原理的基础上,重点阐述LMD技术的特点,分析影响金属成型质量的关键因素——稀释率。借助于测量仪器对实验数据进行记录和分析,结合理论得到较为准确的实验参数,并分析实验过程中所产生问题的原因,经理论与实际相结合,验证得出最优参数。     

Surface roughness analysis and improvement of micro-fluidic channel with excimer laser

Micro-fluidic channel was fabricated on a PMMA sheet (thickness of 1.5 mm) using 248 nm excimer laser direct-writing technique. The influence of excimer laser fluence on the micromachining quality (channel’s depth and surface roughness) was analyzed. Higher laser fluence results in the augmentation of channel’s depth and surface roughness. The excimer laser polishing processing is favorable for the improvement of surface roughness. However, over-abundant polishing will generate tenuous stripe on the channel’s edge and worsen the surface roughness.     

Packable Springs

Laser cutting is an appealing fabrication process due to the low cost of materials and extremely fast fabrication. However, the design space afforded by laser cutting is limited, since only flat panels can be cut. Previous methods for manufacturing from flat sheets usually roughly approximate 3D objects by polyhedrons or cross sections. Computational design methods for connecting, interlocking, or folding several laser cut panels have been introduced; to obtain a good approximation, these methods require numerous parts and long assembly times. In this paper, we propose a radically different approach: Our approximation is based on cutting thin, planar spirals out of flat panels. When such spirals are pulled apart, they take on the shape of a 3D spring whose contours are similar to the input object. We devise an optimization problem that aims to minimize the number of required parts, thus reducing costs and fabrication time, while at the same time ensuring that the resulting spring mimics the shape of the original object. In addition to rapid fabrication and assembly, our method enables compact packaging and storage as flat parts. We also demonstrate its use for creating armatures for sculptures and moulds for filling, with potential applications in architecture or construction.     

Fabrication of microstructures on different materials by diode-pumped solid state laser writing for microfluidics applications

Laser writing attached many attentions for fabrication micro-channels in microfluidics devices and lab-on-chip devices for biomedical applications. In this study, micro-channels were fabricated on different materials as masters using nanosecond diode-pumped solid state (DPSS) laser writing for imprinting on glass and polymer microfluidics devices. Good quality microstructures were fabricated on silicon, nickel alloy, cooper/brass and alumina, respectively by laser writing which proved that the nanosecond DPSS laser is suitable for rapid prototyping and rapid manufacturing of surface microstructures on different substrates as mask-less exposure system of imprinting.     

A cost-driven process planning method for hybrid additive–subtractive remanufacturing

Hybrid manufacturing combines additive manufacturing’s advantages of building complex geometries and subtractive manufacturing’s benefits of dimensional precision and surface quality. This technology shows great potential to support repairing and remanufacturing processes. Hybrid manufacturing is used to repair end-of-life parts or remanufacture them to new features and functionalities. However, process planning for hybrid remanufacturing is still a challenging research topic. This is because current methods require extensive human intervention for feature recognition and knowledge interpretation, and the quality of the derived process plans are hard to quantify. To fill this gap, a cost-driven process planning method for hybrid additive–subtractive remanufacturing is proposed in this paper. An automated additive–subtractive feature extraction method is developed and the process planning task is formulated into a cost-minimization optimization problem to guarantee a high-quality solution. Specifically, an implicit level-set function-based feature extraction method is proposed. Precedence constraints and cost models are also formulated to construct the hybrid process planning task as a mixed-integer programming model. Numerical examples demonstrate the efficacy of the proposed method.     

Axisymmetric structural optimization design and void control for selective laser melting

Additive manufacturing processes, of which Selective Laser Melting (SLM) is one, provide an increased design freedom and the ability to build structures directly from CAD models. There is a growing interest in using optimization methods to design structures in place of manual designs. Three design optimization problems were addressed in this paper. The first related to axisymmetric structures and the other two addressing important design constraints when manufacturing using SLM. These solutions were developed and applied to a case study of a turbine containment ring. Firstly, many structural components such as a turbine containment ring are axisymmetric while they are subjected to a non-axisymmetric load. A solution was presented in this paper to generate optimized axisymmetric designs for a problem in which the mechanical model was not axisymmetric. The solution also worked equally well for generating a prismatic geometry with a uniform cross section, requiring no change in the procedure from axisymmetric designs to achieve this. Secondly, the SLM process experiences difficulties manufacturing structures with internal voids larger than a certain upper limit. A method was developed that allowed the designer to provide a value for this upper limit to the optimization method which would prevent the generation of internal voids larger than this value in any optimized design. The method calculated the sizes of all the voids and did not increase their size once they reached this limit. It was also aware of voids near each other, providing a minimum distance between them. Finally, in order to remove the metal powder, that fills the internal voids of structures built using SLM to reduce unnecessary weight, a method was developed to build paths to join the internal voids created during the optimization process. It allowed the analyst to nominate suitable path entrance locations from which powder could be removed, then found the shortest path connecting all voids and these locations. For axisymmetric structures it also distributed this path around the circumference to avoid generating weak points.