Search results
1 – 10 of 111Guanchen Liu, Dongdong Xu, Zifu Shen, Hongjie Xu and Liang Ding
As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous…
Abstract
Purpose
As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.
Design/methodology/approach
Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.
Findings
In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.
Originality/value
With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.
Details
Keywords
Veera Harsha Vardhan Jilludimudi, Daniel Zhou, Eric Rubstov, Alexander Gonzalez, Will Daknis, Erin Gunn and David Prawel
This study aims to collect real-time, in situ data from polymer melt extrusion (ME) 3D printing and use only the collected data to non-destructively identify printed parts that…
Abstract
Purpose
This study aims to collect real-time, in situ data from polymer melt extrusion (ME) 3D printing and use only the collected data to non-destructively identify printed parts that contain defects.
Design/methodology/approach
A set of sensors was created to collect real-time, in situ data from polymer ME 3D printing. A variance analysis was completed to identify an “acceptable” range for filament diameter on a popular desktop 3D printer. These data were used as the basis of a quality evaluation process to non-destructively identify spatial regions of printed parts in multi-part builds that contain defects.
Findings
Anomalous parts were correctly identified non-destructively using only in situ collected data.
Research limitations/implications
This methodology was developed by varying the filament diameter, one of the most common reasons for print failure in ME. Numerous other printing parameters are known to create faults in melt extruded parts, and this methodology can be extended to analyze other parameters.
Originality/value
To the best of the authors’ knowledge, this is the first report of a non-destructive evaluation of 3D-printed part quality using only in situ data in ME. The value is in improving part quality and reliability in ME, thereby reducing 3D printing part errors, plastic waste and the associated cost of time and material.
Details
Keywords
Mohammad Saleh Afsharkohan, Saman Dehrooyeh, Majid Sohrabian and Majid Vaseghi
Fabrication settings such as printing speed and nozzle temperature in fused deposition modeling undeniably influence the quality and strength of fabricated parts. As available…
Abstract
Purpose
Fabrication settings such as printing speed and nozzle temperature in fused deposition modeling undeniably influence the quality and strength of fabricated parts. As available market filaments do not contain any exact information report for printing settings, manufacturers are incapable of achieving desirable predefined print accuracy and mechanical properties for the final parts. The purpose of this study is to determine the importance of selecting suitable print parameters by understanding the intrinsic behavior of the material to achieve high-performance parts.
Design/methodology/approach
Two common commercial polylactic acid filaments were selected as the investigated samples. To study the specimens’ printing quality, an appropriate scaffold geometry as a delicate printing sample was printed according to a variety of speeds and nozzle temperatures, selected in the filament manufacturer’s proposed temperature range. Dimensional accuracy and qualitative surface roughness of the specimens made by one of the filaments were evaluated and the best processing parameters were selected. The scaffolds were fabricated again by both filaments according to the selected proper processing parameters. Material characterization tests were accomplished to study the reason for different filament behaviors in the printing process. Moreover, the correlations between the polymer structure, thermo-rheological behavior and printing parameters were denoted.
Findings
Compression tests revealed that precise printing of the characterized filament results in more accurate structure and subsequent improvement of the final printed sample elastic modulus.
Originality/value
The importance of material characterization to achieve desired properties for any purpose was emphasized. Obtained results from the rheological characterizations would help other users to benefit from the highest performance of their specific filament.
Details
Keywords
Ruiliang Feng, Jingchao Jiang, Atul Thakur and Xiangzhi Wei
Two-level support with Level 1 consisting of a set of beams and Level 2 consisting of a tree-like structure is an efficient support structure for extrusion-based additive…
Abstract
Purpose
Two-level support with Level 1 consisting of a set of beams and Level 2 consisting of a tree-like structure is an efficient support structure for extrusion-based additive manufacturing (EBAM). However, the literature for finding a slim two-level support is rare. The purpose of this paper is to design a lightweight two-level support structure for EBAM.
Design/methodology/approach
To efficiently solve the problem, the lightweight design problem is split into two subproblems: finding a slim Level 1 support and a slim Level 2 support. To solve these two subproblems, this paper develops three efficient metaheuristic algorithms, i.e. genetic algorithm (GA), genetic programming (GP) and particle swarm optimization (PSO). They are problem-independent and are powerful in global search. For the first subproblem, considering the path direction is a critical factor influencing the layout of Level 1 support, this paper solves it by splitting the overhang region into a set of subregions, and determining the path direction (vertical or horizontal) in each subregion using GA. For the second subproblem, a hybrid of two metaheuristic algorithms is proposed: the GP manipulates the topologies of the tree support, while the PSO optimizes the position of nodes and the diameter of tree branches. In particular, each chromosome is encoded as a single virtual tree for GP to make it easy to manipulate Crossover and Mutation. Furthermore, a local strategy of geometric search is designed to help the hybrid algorithm reach a better result.
Findings
Simulation results show that the proposed method is preferred over the existing method: it saves the materials of the two-level support up to 26.34%, the materials of the Level 1 support up to 6.62% and the materials of the Level 2 support up to 37.93%. The proposed local strategy of geometric search can further improve the hybrid algorithm, saving up to 17.88% of Level 2 support materials.
Research limitations/implications
The proposed approach for sliming Level 1 support requires the overhanging region to be a rectilinear polygon and the path direction in a subregion to be vertical or horizontal. This limitation limits the further material savings of the Level 1 support. In future research, the proposed approach can be extended to handle an arbitrary overhang region, each with several choices of path directions.
Practical implications
The details of how to integrate the proposed algorithm into the open-source program CuraEngine 4.13.0 is presented. This is helpful for the designers and manufacturers to practice on their own 3D printers.
Originality/value
The path planning of the overhang is a critical factor influencing the distribution of supporting points and will thus influence the shape of the support structure. Different from existing approaches that use single path directions, the proposed method optimizes the volume of the support structure by planning hybrid paths of the overhangs.
Details
Keywords
Solomon O. Obadimu and Kyriakos I. Kourousis
The material extrusion (ME) process induces variations in the final part’s microscopic and macroscopic structural characteristics. This viewpoint article aims to uncover the…
Abstract
Purpose
The material extrusion (ME) process induces variations in the final part’s microscopic and macroscopic structural characteristics. This viewpoint article aims to uncover the relation between ME fabrication parameters and the microstructural and mesostructural characteristics of the ME BASF Ultrafuse Steel 316L metal parts. These characteristics can affect the structural integrity of the produced parts and components used in various engineering applications.
Design/methodology/approach
Recent studies on the ME BASF Ultrafuse Steel 316L are reviewed, with a focus on those which report microstructural and mesostructural characteristics that may affect structural integrity.
Findings
A relationship between ME fabrication parameters and subsequent microstructural and mesostructural characteristics is discussed. Common microstructural and mesostructural/macrostructural defects are also highlighted and discussed.
Originality/value
This viewpoint article attempts to bridge the existing gap in the literature, highlighting the influence of ME fabrication parameters on Steel 316L parts fabricated via this additive manufacturing method. Moreover, this article identifies and discusses important considerations for the purposes of selecting and optimising the structural integrity of ME-fabricated Steel 316L parts.
Details
Keywords
Deepak Kumar, Yongxin Liu, Houbing Song and Sirish Namilae
The purpose of this study is to develop a deep learning framework for additive manufacturing (AM), that can detect different defect types without being trained on specific defect…
Abstract
Purpose
The purpose of this study is to develop a deep learning framework for additive manufacturing (AM), that can detect different defect types without being trained on specific defect data sets and can be applied for real-time process control.
Design/methodology/approach
This study develops an explainable artificial intelligence (AI) framework, a zero-bias deep neural network (DNN) model for real-time defect detection during the AM process. In this method, the last dense layer of the DNN is replaced by two consecutive parts, a regular dense layer denoted (L1) for dimensional reduction, and a similarity matching layer (L2) for equal weight and non-biased cosine similarity matching. Grayscale images of 3D printed samples acquired during printing were used as the input to the zero-bias DNN.
Findings
This study demonstrates that the approach is capable of successfully detecting multiple types of defects such as cracks, stringing and warping with high accuracy without any prior training on defective data sets, with an accuracy of 99.5%.
Practical implications
Once the model is set up, the computational time for anomaly detection is lower than the speed of image acquisition indicating the potential for real-time process control. It can also be used to minimize manual processing in AI-enabled AM.
Originality/value
To the best of the authors’ knowledge, this is the first study to use zero-bias DNN, an explainable AI approach for defect detection in AM.
Details
Keywords
Ashish Kaushik and Ramesh Kumar Garg
This study aims to cover the overall gamut of rapid prototyping processes and biomaterials used for the fabrication of occlusal splints in a comprehensive manner and elucidate the…
Abstract
Purpose
This study aims to cover the overall gamut of rapid prototyping processes and biomaterials used for the fabrication of occlusal splints in a comprehensive manner and elucidate the characteristics of the materials, which are essential in determining their clinical efficacy when exposed to oral surroundings.
Design/methodology/approach
A collective analysis of published articles covering the use of rapid prototyping technologies in the fabrication of occlusal splints, including manufacturing workflow description and essential properties (mechanical- and thermal-based) evaluation of biocompatible splinting materials, was performed.
Findings
Without advances in rapid prototyping processes and materials engineering, occlusal splints would tend to underperform clinically due to biomechanical limitations.
Social implications
Three-dimensional printing can improve the process capabilities for commercial customization of biomechanically efficient occlusal splints.
Originality/value
Rapid technological advancement in dentistry with the extensive utilization of rapid prototyping processes, intra-oral scanners and novel biomaterial seems to be the potential breakthrough in the fabrication of customized occlusal splints which have endorsed occlusal splint therapy (OST) as a cornerstone of orthodontic treatment.
Details
Keywords
Bahador Bahrami, Mohammad Reza Mehraban, Seyed Saeid Rahimian Koloor and Majid R. Ayatollahi
The purpose of this study is to develop an efficient numerical procedure for simulating the effect of printing orientation, as one of the primary sources of anisotropy in…
Abstract
Purpose
The purpose of this study is to develop an efficient numerical procedure for simulating the effect of printing orientation, as one of the primary sources of anisotropy in 3D-printed components, on their fracture properties.
Design/methodology/approach
The extended finite element method and the cohesive zone model (XFEM-CZM) are used to develop subroutines for fracture simulation. The ability of two prevalent models, i.e. the continuous-varying fracture properties (CVF) model and the weak plane model (WPM), and a combination of both models (WPM-CVF) are evaluated to capture fracture behavior of the additively manufactured samples. These models are based on the non-local and local forms of the anisotropic maximum tangential stress criterion. The numerical models are assessed by comparing their results with experimental outcomes of 16 different configurations of polycarbonate samples printed using the material extrusion technique.
Findings
The results demonstrate that the CVF exaggerates the level of anisotropy, and the WPM cannot detect the mild anisotropy of 3D-printed parts, while the WPM-CVF produces the best results. Additionally, the non-local scheme outperforms the local approach in terms of finite element analysis performance, such as mesh dependency, robustness, etc.
Originality/value
This paper provides a method for modeling anisotropic fracture in 3D-printed objects. A new damage model based on a combination of two prevalent models is offered. Moreover, the developed subroutines for implementing the non-local anisotropic fracture criterion enable a reliable crack propagation simulation in media with varying degrees of complication, such as anisotropy.
Details
Keywords
Mohd Nazri Ahmad, Mohamad Ridzwan Ishak, Mastura Mohammad Taha, Faizal Mustapha and Zulkiflle Leman
The purpose of this paper is to investigate the tensile strength, Young’s modulus, dimensional stability and porosity of acrylonitrile butadiene styrene (ABS)–oil palm fiber…
Abstract
Purpose
The purpose of this paper is to investigate the tensile strength, Young’s modulus, dimensional stability and porosity of acrylonitrile butadiene styrene (ABS)–oil palm fiber composite filament for fused deposition modeling (FDM).
Design/methodology/approach
A new feedstock material for FDM comprising oil palm fiber and ABS as a matrix was developed by a twin screw extruder. The composite filament contains 0, 3, 5 and 7 Wt.% of oil palm fiber in the ABS matrix. The tensile test is then performed on the fiber composite filament, and the wire diameter is measured. In this study, the Archimedes method was used to determine the density and the porosity of the filament. The outer surface of the wire composite was examined using an optical microscope, and the analysis of variance was used to assess the significance and the relative relevance of the primary factor.
Findings
The results showed that increasing the fiber loading from 0.15 to 0.4 MPa enhanced tensile strength by 60%. Then, from 16.1 to 18.3 MPa, the Young’s modulus rose by 22.8%. The density of extruded filament decreased and the percentage of porosity increased when the fiber loading was increased from 3 to 7 Wt.%. The diameter deviation of the extruded filaments varied from −0.21 to 0.04 mm.
Originality/value
This paper highlights a novel natural resource-based feedstock material for FDM. Its mechanical and physical properties were also discovered.
Details
Keywords
Wanbin Pan, Hongyi Jiang, Shufang Wang, Wen Feng Lu, Weijuan Cao and Zhenlei Weng
This paper aims to detect the printing failures (such as warpage and collapse) in material extrusion (MEX) process effectively and timely to reduce the waste of printing time…
Abstract
Purpose
This paper aims to detect the printing failures (such as warpage and collapse) in material extrusion (MEX) process effectively and timely to reduce the waste of printing time, energy and material.
Design/methodology/approach
The approach is designed based on the frequently observed fact that printing failures are accompanied by abnormal material phenomena occurring close to the nozzle. To effectively and timely capture the phenomena near the nozzle, a camera is delicately installed on a typical MEX printer. Then, aided by the captured phenomena (images), a smart printing failure predictor is built based on the artificial neural network (ANN). Finally, based on the predictor, the printing failures, as well as their types, can be effectively detected from the images captured by the camera in real-time.
Findings
Experiments show that printing failures can be detected timely with an accuracy of more than 98% on average. Comparisons in methodology demonstrate that this approach has advantages in real-time printing failure detection in MEX.
Originality/value
A novel real-time approach for failure detection is proposed based on ANN. The following characteristics make the approach have a great potential to be implemented easily and widely: (1) the scheme designed to capture the phenomena near the nozzle is simple, low-cost, and effective; and (2) the predictor can be conveniently extended to detect more types of failures by using more abnormal material phenomena that are occurring close to the nozzle.
Details