Generalised overlapping model for multi-material wire arc additive manufacturing (WAAM)

Banaee, Seyed Aref; Kapil, Angshuman; Marefat, Fereidoon; Sharma, Abhay

doi:10.1080/17452759.2023.2210541

Cited by 22 publications

(4 citation statements)

References 31 publications

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“…A reduced lead time and an increased mold life were reported, thus indicating the potential of the multimaterial injection molding process. In more recent work with the utilization of WAAM, the bi-metallic pairs LCS-SS [117] and CRS-SS [118,119] have been successfully fabricated. To manufacture titanium-based alloy and nickel-based alloy bi-metallic components (TC4-IN718), which are widely used in the aerospace industry due to their excellent characteristics, tantalum-copper interlayers were utilized by Wang et al [115] to prevent the formation of Ti-Ni and Ti-Cu compounds at the interface and thus form a good bond at the interface.…”

Section: Bi-metallic Componentsmentioning

confidence: 99%

“…A reduced lead time and an increased mold life were reported, thus indicating the potential of the multi-material injection molding process. In more recent work with the utilization of WAAM, the bi-metallic pairs LCS-SS [117] and CRS-SS [118,119] have been successfully fabricated.…”

Section: Bi-metallic Componentsmentioning

confidence: 99%

“…To alleviate the issue of the reduced ductility of intermetallic phases in multi-material structures, Chen et al [137] introduced a third metal element into the MMAM process, which led to an increase in the ductility of the intermetallic phase. More recently, Banaee et al [119], in their study on the WAAM of CRS-SS bi-metallic walls, found that the difference in material fluidity has a drastic effect on the interfacial fusion. They advocated that, unlike for single-material deposition, for multi-material deposition, a proper combination of process parameters for each material, the sequence of the deposition of the materials, and the overlapping distance, together, control the resulting fusion state (or lack of it) in the multi-material interface.…”

Section: Materials Interaction and Related Issues In Mmammentioning

confidence: 99%

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A Review on Multiplicity in Multi-Material Additive Manufacturing: Process, Capability, Scale, and Structure

et al. 2023

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Additive manufacturing (AM) has experienced exponential growth over the past two decades and now stands on the cusp of a transformative paradigm shift into the realm of multi-functional component manufacturing, known as multi-material AM (MMAM). While progress in MMAM has been more gradual compared to single-material AM, significant strides have been made in exploring the scientific and technological possibilities of this emerging field. Researchers have conducted feasibility studies and investigated various processes for multi-material deposition, encompassing polymeric, metallic, and bio-materials. To facilitate further advancements, this review paper addresses the pressing need for a consolidated document on MMAM that can serve as a comprehensive guide to the state of the art. Previous reviews have tended to focus on specific processes or materials, overlooking the overall picture of MMAM. Thus, this pioneering review endeavors to synthesize the collective knowledge and provide a holistic understanding of the multiplicity of materials and multiscale processes employed in MMAM. The review commences with an analysis of the implications of multiplicity, delving into its advantages, applications, challenges, and issues. Subsequently, it offers a detailed examination of MMAM with respect to processes, materials, capabilities, scales, and structural aspects. Seven standard AM processes and hybrid AM processes are thoroughly scrutinized in the context of their adaptation for MMAM, accompanied by specific examples, merits, and demerits. The scope of the review encompasses material combinations in polymers, composites, metals-ceramics, metal alloys, and biomaterials. Furthermore, it explores MMAM’s capabilities in fabricating bi-metallic structures and functionally/compositionally graded materials, providing insights into various scale and structural aspects. The review culminates by outlining future research directions in MMAM and offering an overall outlook on the vast potential of multiplicity in this field. By presenting a comprehensive and integrated perspective, this paper aims to catalyze further breakthroughs in MMAM, thus propelling the next generation of multi-functional component manufacturing to new heights by capitalizing on the unprecedented possibilities of MMAM.

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Section: Bi-metallic Componentsmentioning

confidence: 99%

Section: Bi-metallic Componentsmentioning

confidence: 99%

Section: Materials Interaction and Related Issues In Mmammentioning

confidence: 99%

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A Review on Multiplicity in Multi-Material Additive Manufacturing: Process, Capability, Scale, and Structure

et al. 2023

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“…A central composite design of the experiment (referenced in Table 1) was employed, focusing on the working range of the process parameters. This range for parameters such as wire feed speed, travel speed, and interpass temperature was de ned based on another in-house study [12]. A total of 15 walls, each 80 mm in length and 110 mm in height, were deposited using a pulsed gas metal arc welding process facilitated by a Fronius TransPulsedSynergic 4000 power source.…”

Section: Depositionmentioning

confidence: 99%

Artificial Neural Network-Based Surface Reconstruction Model of Wire-Arc Additively Manufactured Surfaces using Discrete Cosine Transfer

Banaee,

Sharma

2023

Preprint

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The unique arc-based additive manufacturing process boasts exceptionally high deposition rates, but it comes with a trade-off – the generation of highly irregular surfaces that demand extensive post-machining efforts. These post-processing activities not only consume critical raw materials but also substantial energy resources. To mitigate these challenges and enhance process efficiency, it is crucial to develop predictive capabilities for surface topography based on key process parameters like wire feed speed and travel speed. In this study, a surface topography model is meticulously developed to reconstruct surfaces, utilizing wire feed speed, travel speed, and inter-pass temperature as input parameters. The initial phase involves identifying pertinent surface features that collectively define the surface. Out of the features examined, eight representative attributes emerge, including spatial average roughness, spatial peak height, spatial maximum valley depth, spatial skewness, spatial kurtosis, maximum flatness, and waviness. The surface reconstruction model employs the discrete cosine transform (DCT), necessitating a minimum of 30 DCT parameters for accurate surface reconstruction. Additionally, an ANN model is established to predict DCT parameters based on wire feed speed, travel speed, and inter-pass temperature inputs. Validation using the 309L stainless steel test material demonstrates the model's impressive accuracy in predicting DCT parameters, enabling precise forecasts of overall surface topography and machining allowances. This model lays the foundation for simulation-based additive-subtractive process design by identifying optimal deposition conditions and corresponding machining parameters. Furthermore, it streamlines the integration of realistic surfaces into computational models for additive process simulations, offering significant potential for improving additive manufacturing processes.

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Cold Metal Transfer-Based Wire Arc Additively Manufactured Austenitic Stainless Steel/Inconel 625/Superduplex Stainless Steel Wall: Microstructural, Corrosion Properties, and Impact Toughness Evaluation

Kumar,

Singh,

Kaur

et al. 2024

J. of Materi Eng and Perform

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Generalised overlapping model for multi-material wire arc additive manufacturing (WAAM)

Cited by 22 publications

References 31 publications

A Review on Multiplicity in Multi-Material Additive Manufacturing: Process, Capability, Scale, and Structure

A Review on Multiplicity in Multi-Material Additive Manufacturing: Process, Capability, Scale, and Structure

Artificial Neural Network-Based Surface Reconstruction Model of Wire-Arc Additively Manufactured Surfaces using Discrete Cosine Transfer

Cold Metal Transfer-Based Wire Arc Additively Manufactured Austenitic Stainless Steel/Inconel 625/Superduplex Stainless Steel Wall: Microstructural, Corrosion Properties, and Impact Toughness Evaluation

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