Optimization and Simulation of SLM Process for High Density H13 Tool Steel Parts

Laakso, Petri; Riipinen, Tuomas; Laukkanen, Anssi; Andersson, Tom; Jokinen, Antero; Revuelta, Alejandro; Ruusuvuori, Kimmo

doi:10.1016/j.phpro.2016.08.004

Cited by 88 publications

(41 citation statements)

References 15 publications

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“…Laser power, laser scan speed, hatch speed, hatch overlaps, hatch style etc. are the parameters which have significant effect on mechanical assets of the manufactured parts [17][18][19]. SLM is the most versatile process as it has the ability to process a large variety of materials such as Al-based alloys, Ti-based alloys, Fe-based alloys, Cu-based alloys, Co-based alloys, and Ni-based alloys as well as their composites.…”

Section: Selective Laser Meltingmentioning

confidence: 99%

“…Comparatively Faster process as that of conventional process, prototypes are strong enough to undergo machining; costly process, careful handling of photopolymer is required 10 µm Selective laser melting [14][15][16][17][18][19]21] Metal or polymer powder is spread in layers and is selectively melted as per input from CAD file with the help of a laser beam and resolidified; strut build angle has strong influence on properties of structure To optimize the process, limited number of parameters are to be considered; capable of processing large number of metal powders 40 -200 µm Electron beam melting [21] Similar operation to that of SLM but the laser beam is replaced by an electron beam, capable of processing brittle materials.…”

Section: Process Explanation Features Minimum Feature Sizementioning

confidence: 99%

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Applications, Manufacturing and Thermal Characteristics of Micro-Lattice Structures: Current State of the Art

Sur¹,

Narkhede²,

Darvekar³

2019

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Micro-lattice structures are emerging as multi-functional devices. They possess excellent heat transfer capabilities, energy absorption abilities, vibration control abilities, etc. The higher surface area to volume ratio of micro-lattice structures makes them suitable for heat transfer applications where compact and lightweight heat transfer mechanism is necessary such as in case of space and transportation. The heat transfer and mechanical load-bearing properties of micro-lattice structures can be tailored by altering several parameters such as the lattice strut angle, node-to-node spacing, the diameter of the strut, etc. In this paper, micro-lattice structures, their manufacturing methods, applications are reviewed and a passive heat transfer mechanism consisting of micro-lattice heat pipe is proposed for the battery thermal management system in electric vehicles.

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Section: Selective Laser Meltingmentioning

confidence: 99%

Section: Process Explanation Features Minimum Feature Sizementioning

confidence: 99%

Applications, Manufacturing and Thermal Characteristics of Micro-Lattice Structures: Current State of the Art

Sur¹,

Narkhede²,

Darvekar³

2019

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“…Equation (10) is solved in Matlab under the previous assumptions with a heat flux of Gaussian shape as proposed in [29,30]:…”

Section: Analytical Modelmentioning

confidence: 99%

Analytical and Numerical Temperature Prediction in Direct Metal Deposition of Ti6Al4V

Batut

Fergani²,

Brøtan

et al. 2017

JMMP

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Direct Metal Deposition (DMD) is an additive manufacturing (AM) process capable of producing large components using a layer by layer deposition of molten powder. DMD is increasingly investigated due to its higher deposition rate and the possibility to produce large structural components specifically for the aerospace industry. During fabrication, a complex thermal history is experienced in different regions of the workpiece, depending on the process parameters and part geometry. The thermal history induces residual stress accumulation in the buildup, which is the main cause of distortions. In order to control the process and enhance the product quality, the understanding of the workpiece temperature is substantial. In this study, two methods to predict temperature evolution during the DMD process are introduced based on analytical and finite element methods. The objective is to compare these methods to experimental results and to provide more insights about their capabilities to predict accurately the temperature gradient, the cooling rate, and the melt pool geometry. A comparison of the computational time is also provided. Based on the results of the investigation, It appears that the analytical method provides an effective and accurate method to understand the influence of the process on the workpiece temperature.

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“…By further mapping the structure to the properties and performance, the part design can be intelligently guided with process-structure-properties-performance (PSPP) modeling chain, which spares time and money compared to trial-and-error type design, which is the core idea of integrated computational materials engineering (ICME).Significant progress has been made in developing submodels for the PSPP chain [8]. Physics-based causal computer modeling can accelerate the process design [8], for example, to improve the density of SLM tool steels [9]. Khairallah et al presented a melt pool model with multiphase fluid flow, heat transfer, and ray-tracing that describes process-induced spattering, pore formation, and denudation zones [10].…”

mentioning

confidence: 99%

“…Significant progress has been made in developing submodels for the PSPP chain [8]. Physics-based causal computer modeling can accelerate the process design [8], for example, to improve the density of SLM tool steels [9]. Khairallah et al presented a melt pool model with multiphase fluid flow, heat transfer, and ray-tracing that describes process-induced spattering, pore formation, and denudation zones [10].…”

mentioning

confidence: 99%

Process-Structure-Properties-Performance Modeling for Selective Laser Melting

Pinomaa

Yashchuk

Lindroos

et al. 2019

Metals

Self Cite

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Selective laser melting (SLM) is a promising manufacturing technique where the part design, from performance and properties process control and alloying, can be accelerated with integrated computational materials engineering (ICME). This paper demonstrates a process-structure-properties-performance modeling framework for SLM. For powder-bed scale melt pool modeling, we present a diffuse-interface multiphase computational fluid dynamics model which couples Navier-Stokes, Cahn-Hilliard, and heat-transfer equations. A computationally efficient large-scale heat-transfer model is used to describe the temperature evolution in larger volumes. Phase field modeling is used to demonstrate how epitaxial growth of Ti-6-4 can be interrupted with inoculants to obtain an equiaxed polycrystalline structure. These structures are enriched with a synthetic lath martensite substructure, and their micromechanical response are investigated with a crystal plasticity model. The fatigue performance of these structures are analyzed, with spherical porelike defects and high-aspect-ratio cracklike defects incorporated, and a cycle-amplitude fatigue graph is produced to quantify the fatigue behavior of the structures. The simulated fatigue life presents trends consistent with the literature in terms of high cycle and low cycle fatigue, and the role of defects in dominating the respective performance of the produced SLM structures. The proposed ICME workflow emphasizes the possibilities arising from the vast design space exploitable with respect to manufacturing systems, powders, respective alloy chemistries, and microstructures. By digitalizing the whole workflow and enabling a thorough and detailed virtual evaluation of the causal relationships, the promise of product-targeted materials and solutions for metal additive manufacturing becomes closer to practical engineering application.to be modified to maintain similar properties achieved with traditional techniques such as casting or wrought parts. Compared to traditional manufacturing methods, due to local powder fusion in rapid solidification conditions and solid-state heat cycling, the resulting microstructures present unique features such as metastable phases, smaller scale microsegregation, formation of unexpected secondary phases, spherical or high-aspect-ratio pores, oxide inclusions, microstructural residual stresses, melt pool boundaries, grains with complex morphology, and strong texture.The aforementioned structural features in SLM lead to properties and performance that are unexpected [1]. For example, stainless steel 316L can achieve remarkably high hardness and ductility [2] but has a susceptibility to pitting corrosion [3]; Inconel 625 nickel superalloy contains detrimental intermetallic and carbide phases [4]; Ti-6-4 tends to produce hard needlelike α martensite which leads to high hardness but low ductility; tool steels are extremely difficult to fabricate with SLM due to their complex metallurgy, including a tendency to form brittle martensite and high volume fractions of ...

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Optimization and Simulation of SLM Process for High Density H13 Tool Steel Parts

Cited by 88 publications

References 15 publications

Applications, Manufacturing and Thermal Characteristics of Micro-Lattice Structures: Current State of the Art

Applications, Manufacturing and Thermal Characteristics of Micro-Lattice Structures: Current State of the Art

Analytical and Numerical Temperature Prediction in Direct Metal Deposition of Ti6Al4V

Process-Structure-Properties-Performance Modeling for Selective Laser Melting

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