A Preliminary Experimental Study of Additive Manufacturing Energy Consumption

2017 ◽  
Author(s):  
Daniel Dunaway ◽  
James Dillon Harstvedt ◽  
Junfeng Ma
Keyword(s):  
Energy Consumption ◽  
Additive Manufacturing ◽  
Experimental Design ◽  
Surface Area ◽  
Surface Geometry ◽  
Fused Deposition ◽  
Part Geometry ◽  
Industrial Sectors ◽  
Part Surface ◽  
The Impact

Additive manufacturing (AM) refers to a group of manufacturing techniques that produce components by melting and bonding material powders in a layer-by-layer fashion. By virtue of its capability of producing parts with complex geometry and functionally graded materials, AM is leading the charge of the “third industrial revolution” and has attracted great attention in multiple industrial sectors, such as manufacturing, healthcare, aerospace, and others. Sustainability of AM remains an open question. AM is inherently an energy expensive process and may be energy inefficient as compared to the traditional manufacturing process. Thus, there exists an urgent need to identify the key influence factors and quantify the energy consumption during AM production. The proposed study aims to obtain a preliminary understanding of the impact of part surface geometry on AM energy consumption. The study addresses the effect of part geometry on AM energy consumption through experimental design method. Part geometry consists of two level meanings, part surface area and part surface complexity. The study utilizes a MakerGear M2 fused deposition modeling (FDM) 3D printer to complete the designed experiments. By implementing experimental design and statistical analysis technologies, the study firstly identifies the correlation between part geometry and AM energy consumption. The result shows that part surface area is positively correlated with AM energy consumption and no significant statistical evidence to support that part surface complexity is associated with AM energy consumption. Such findings are of significance to AM energy consumption in terms of both qualitative and quantitative analysis. In addition, the study has significant potentials to guide the future AM energy consumption model development and to be extended to future AM process improvement.

Data Driven Modeling and Optimization for Energy Efficiency in Additive Manufacturing Process With Geometric Accuracy Consideration

2018 ◽  
Author(s):  
Junfeng Ma ◽  
Wenmeng Tian ◽  
Morteza Alizadeh
Keyword(s):  
Energy Consumption ◽  
Additive Manufacturing ◽  
Process Parameters ◽  
Complex Geometry ◽  
Statistical Regression ◽  
Geometric Accuracy ◽  
Fused Deposition ◽  
Optimization Framework ◽  
Accuracy Measure ◽  
The Impact

Despite of its tremendous merits in producing parts with complex geometry and functionally graded materials, additive manufacturing (AM) is inherently an energy expensive process. Prior studies have shown that process parameters, such as printing resolution, printing speed, and printing temperature, are correlated to energy consumption per part. Moreover, part geometric accuracy is another major focus in AM research, and extensive studies have shown that the geometric accuracy of final parts is highly dependent on those process parameters as well. Though both energy consumption and part geometric accuracy heavily depend on the process parameters in AM processes, jointly considering the dual outputs in AM process is not fully investigated. The proposed study aims to obtain a quantitative understanding of the impact of these process parameters on AM energy consumption given part quality requirements, such as geometric accuracy. The study utilizes a MakerGear M2 fused deposition modeling (FDM) 3D printer to complete the designed experiments. By implementing experimental design and statistical regression analysis technologies, the study quantifies the correlation between AM process parameters and energy consumption as well as the final geometric accuracy measure. An optimization framework is proposed to minimize the energy consumption per part. The Kuhn-Tucker non-linear optimization algorithm is used to identify the optimal process parameters. This study is of significance to AM energy consumption in terms of jointly considering energy consumption and final part geometric accuracy in the optimization framework.

scholarly journals Effect of Process Parameters on Energy Consumption, Physical, and Mechanical Properties of Fused Deposition Modeling

Polymers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2406
Author(s):  
Emmanuel U. Enemuoh ◽  
Stefan Duginski ◽  
Connor Feyen ◽  
Venkata G. Menta
Keyword(s):  
Energy Consumption ◽  
Additive Manufacturing ◽  
Process Parameters ◽  
Fused Deposition Modeling ◽  
Function Optimization ◽  
Free Form ◽  
Production Time ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
The Impact

The application of the fused deposition modeling (FDM) additive manufacturing process has increased in the production of functional parts across all industries. FDM is also being introduced for industrial tooling and fixture applications due to its capabilities in building free-form and complex shapes that are otherwise challenging to manufacture by conventional methods. However, there is not yet a comprehensive understanding of how the FDM process parameters impact the mechanical behavior of engineered products, energy consumption, and other physical properties for different material stocks. Acquiring this information is quite a complex task, given the large variety of possible combinations of materials–additive manufacturing machines–slicing software process parameters. In this study, the knowledge gap is filled by using the Taguchi L27 orthogonal array design of experiments to evaluate the impact of five notable FDM process parameters: infill density, infill pattern, layer thickness, print speed, and shell thickness on energy consumption, production time, part weight, dimensional accuracy, hardness, and tensile strength. Signal-to-noise (S/N) ratio analysis and analysis of variance (ANOVA) were performed on the experimental data to quantify the parameters’ main effects on the responses and establish an optimal combination for the FDM process. The novelty of this work is the simultaneous evaluation of the effects of the FDM process parameters on the quality performances because most studies have considered one or two of the performances alone. The study opens an opportunity for multiobjective function optimization of the FDM process that can be used to effectively minimize resource consumption and production time while maximizing the mechanical and physical characteristics to fit the design requirements of FDM-manufactured products.

scholarly journals Environmental and Economic Analysis of FDM, SLS and MJF Additive Manufacturing Technologies

Materials ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4161 ◽  
Author(s):  
Vincenzo Tagliaferri ◽  
Federica Trovalusci ◽  
Stefano Guarino ◽  
Simone Venettacci
Keyword(s):  
Additive Manufacturing ◽  
High Performance ◽  
Large Scale ◽  
Fused Deposition Modeling ◽  
Production Capacity ◽  
Optimal Choice ◽  
Scale Production ◽  
Fused Deposition ◽  
Manufacturing Technologies ◽  
The Impact

In this study, the authors present a comparative analysis of different additive manufacturing (AM) technologies for high-performance components. Four 3D printers, currently available on the Italian national manufacturing market and belonging to three different AM technologies, were considered. The analysis focused on technical aspects to highlight the characteristics and performance limits of each technology, economic aspects to allow for an assessment of the costs associated with the different processes, and environmental aspects to focus on the impact of the production cycles associated with these technologies on the ecosystem, resources and human health. This study highlighted the current limits of additive manufacturing technologies in terms of production capacity in the case of large-scale production of plastic components, especially large ones. At the same time, this study highlights how the geometry of the object to be developed greatly influences the optimal choice between the various AM technologies, in both technological and economic terms. Fused deposition modeling (FDM) is the technology that exhibits the greatest limitations hindering mass production due to production times and costs, but also due to the associated environmental impact.

Analysis of factors influencing energy consumption of material extrusion-based additive manufacturing using interpretive structural modelling

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ramesh P. ◽  
Vinodh S.
Keyword(s):  
Energy Consumption ◽  
Additive Manufacturing ◽  
Influencing Factors ◽  
Structural Model ◽  
Ease Of Use ◽  
Content Type ◽  
Material Extrusion ◽  
Prototype Development ◽  
Factors Influencing ◽  
The Impact

Purpose Material extrusion (MEX) is a class of additive manufacturing (AM) process based on MEX principle. In the viewpoint of Industry 4.0 and sustainable manufacturing, AM technologies are gaining importance than conventional manufacturing route (subtractive manufacturing). Because of the ease of use and lesser operation skills, MEX had wide popularity in industry for product and prototype development. This study aims to analyze energy consumption of MEX-based AM process and its influencing factors. Design/methodology/approach A group of factors were identified pertaining to MEX-based AM process. In this viewpoint, this study presents the configuration of a structural model using interpretive structural modeling (ISM) to depict dominant factors in MEX-based AM process. A total of 18 influencing factors are identified and ranked using ISM methodology for MEX process. The Impact Matrix Cross-reference Multiplication Applied to a Classification analysis was done to categorize influencing factors into four groups for MEX-based AM process. Findings The derivation of structural model would enable AM practitioners to systematically analyze the factors and to derive key factors which enable comprehensive energy modeling and energy assessment studies. Also, it facilitates the development of energy efficient AM system. Originality/value The development of structural model for analysis of factors influencing energy consumption of MEX-based AM is the original contribution of the authors.

Finite Element Analysis of Additive Manufacturing Based on Fused Deposition Modeling: Distortions Prediction and Comparison With Experimental Data

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Alberto Cattenone ◽  
Simone Morganti ◽  
Gianluca Alaimo ◽  
Ferdinando Auricchio
Keyword(s):  
Additive Manufacturing ◽  
3D Printing ◽  
Fused Deposition Modeling ◽  
Step Size ◽  
Time Step ◽  
Time Step Size ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
The Impact ◽  
Functional Components

Additive manufacturing (or three-dimensional (3D) printing) is constantly growing as an innovative process for the production of complex-shape components. Among the seven recognized 3D printing technologies, fused deposition modeling (FDM) covers a very important role, not only for producing representative 3D models, but, mainly due to the development of innovative material like Peek and Ultem, also for realizing structurally functional components. However, being FDM a production process involving high thermal gradients, non-negligible deformations and residual stresses may affect the 3D printed component. In this work we focus on meso/macroscopic simulations of the FDM process using abaqus software. After describing in detail the methodological process, we investigate the impact of several parameters and modeling choices (e.g., mesh size, material model, time-step size) on simulation outcomes and we validate the obtained results with experimental measurements.

Plastic and metal additive manufacturing technologies for microwave passive components up toKaband

2018 ◽  
Vol 10 (7) ◽  
pp. 772-782
Author(s):  
Johann Sence ◽  
William Feuray ◽  
Aurélien Périgaud ◽  
Olivier Tantot ◽  
Nicolas Delhote ◽  
...  
Keyword(s):  
Stainless Steel ◽  
Additive Manufacturing ◽  
Dielectric Material ◽  
Mode Converter ◽  
Fused Deposition ◽  
3D Printed ◽  
The Creation ◽  
Manufacturing Technologies ◽  
Plastic Parts ◽  
The Impact

AbstractThis paper illustrates the different possibilities given by additive manufacturing technologies for the creation of passive microwave hardware. The paper more specifically highlights a prototyping scheme where the 3D-printed plastic parts can be used as initial proofs of concept before considering more advanced 3D-printed parts (metal parts, for instance). First, a characterization campaign has been made on common plastics used by a 3D printer using the fused deposition modeling and material jetting (Polyjet©) technologies. The impact of the manufacturing strategy (high-speed or high-accuracy) on the part roughness, as well as on the dielectric material permittivity and loss tangent, has been specifically studied at 10 and 16 GHz. Based on a specifically optimized and deeply explained characterization method, the conductivity of a coating based on silver paint has also been characterized on such plastic parts at 10 and 40 GHz. These plastic materials and coating have been used for the creation of quasi-elliptic and tuning-free bandpass filters centered at 6 and 12 GHz and compared with a similar filter made of stainless steel by selective laser melting. Finally, a compact rectangularTE10to circularTE01mode converter also undergoes one prototyping step out of plastic before moving to an advanced part made out of stainless steel. This mode converter, which is made in a single part, is designed to operate from 28 to 36 GHz as a tuning-free final demonstrator.

Freeform additive manufacturing by vari-directional vari-dimensional material deposition

2018 ◽  
Vol 24 (2) ◽  
pp. 379-394 ◽  
Author(s):  
Che-Chih Tsao ◽  
Ho-Hsin Chang ◽  
Meng-Hao Liu ◽  
Ho-Chia Chen ◽  
Yun-Tang Hsu ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Surface Finishing ◽  
Content Type ◽  
Fused Deposition ◽  
Material Deposition ◽  
Finishing Process ◽  
Part Surface ◽  
3D Assembly ◽  
Deposition Modeling

Purpose The purpose of this paper is to propose and demonstrate a new additive manufacturing approach that breaks the layer-based point scanning limitations to increase fabrication speed, obtain better surface finish, achieve material flexibility and reduce equipment costs. Design/methodology/approach The freeform additive manufacturing approach conceptually views a 3D article as an assembly of freeform elements distributed spatially following a flexible 3D assembly structure, which conforms to the surface of the article and physically builds the article by sequentially forming the freeform elements by a vari-directional vari-dimensional capable material deposition mechanism. Vari-directional building along tangential directions of part surface gives surface smoothness. Vari-dimensional deposition maximizes material output to increase build rate wherever allowed and minimizes deposition sizes for resolution whenever needed. Findings Process steps based on geometric and data processing considerations were described. Dispensing and forming of basic vari-directional and vari-dimensional freeform elements and basic operations of joining them were developed using thermoplastics. Forming of 3D articles at build rates of 2-5 times the fused deposition modeling (FDM) rate was demonstrated and improvement over ten times was shown to be feasible. FDM compatible operations using 0.7 mm wire depositions from a variable exit-dispensing unit were demonstrated. Preliminary tests of a surface finishing process showed a result of 0.8-1.9 um Ra. Initial results of dispensing wax, tin alloy and steel were also shown. Originality/value This is the first time that both vari-directional and vari-dimensional material depositions are combined in a new freeform building method, which has potential impact on the FDM and other additive manufacturing methods.

scholarly journals Impact of additive manufacturing on engineering education – evidence from Italy

2015 ◽  
Vol 21 (5) ◽  
pp. 535-555 ◽  
Author(s):  
Paolo Minetola ◽  
Luca Iuliano ◽  
Elena Bassoli ◽  
Andrea Gatto
Keyword(s):  
Additive Manufacturing ◽  
Product Design ◽  
Mechanical Engineering ◽  
Additive Technologies ◽  
Direct Access ◽  
Fused Deposition Modelling ◽  
Content Type ◽  
Entry Level ◽  
Fused Deposition ◽  
The Impact

Purpose – The purpose of this paper is to evaluate how the direct access to additive manufacturing (AM) systems impacts on education of future mechanical engineers, within a Master’s program at a top Italian University. Design/methodology/approach – A survey is specifically designed to assess the relevance of entry-level AM within the learning environment, as a tool for project development. The survey is distributed anonymously to three consecutive cohorts of students who attended the course of “computer-aided production (CAP)”, within the Master of Science Degree in Mechanical Engineering at Politecnico di Torino. The course includes a practical project, consisting in the design of a polymeric product with multiple components and ending with the production of an assembled prototype. The working assembly is fabricated by the students themselves, who operate a fused deposition modelling (FDM) machine, finish the parts and evaluate assemblability and functionality. The post-course survey covers diverse aspects of the learning process, such as: motivation, knowledge acquisition, new abilities and team-working skills. Responses are analyzed to evaluate students’ perception of the usefulness of additive technologies in learning product design and development. Among the projects, one representative case study is selected and discussed. Findings – Results of the research affirm a positive relationship of access to AM devices to perceived interest, motivation and ease of learning of mechanical engineering. Entry-level additive technologies offer a hands-on experience within academia, fostering the acquisition of technical knowledge. Research limitations/implications – The survey is distributed to more than 200 students to cover the full population of the CAP course over three academic years. The year the students participated in the CAP course is not tracked because the instructor was the same and there were no administrative differences. For this reason, the survey administration might be a limitation of the current study. In addition to this, no gender distinction is made because historically, the percentage of female students in Mechanical Engineering courses is about 10 per cent or lower. Although the answers to the survey are anonymous, only 37 per cent of the students gave a feedback. Thus, on the one hand, impact assessment is limited to a sample of about one-third of the complete population, but, on the other hand, the anonymity ensures randomization in the sample selection. Practical implications – Early exposure of forthcoming designers to AM tools can turn into a “think-additive” approach to product design, that is a groundbreaking conception of geometries and product functionalities, leading to the full exploitation of the possibilities offered by additive technologies. Social implications – Shared knowledge can act as a springboard for mass adoption of AM processes. Originality/value – The advantages of adopting AM technologies at different levels of education, for diverse educational purposes and disciplines, are well assessed in the literature. The innovative aspect of this paper is that the impact of AM is evaluated through a feedback coming directly from mechanical engineering students.

scholarly journals Autonomous 3D geometry reconstruction through robot-manipulated optical sensors

2021 ◽  
Author(s):  
Carmelo Mineo ◽  
Donatella Cerniglia ◽  
Vito Ricotta ◽  
Bernhard Reitinger
Keyword(s):  
Optical Sensors ◽  
Point Cloud ◽  
Simulation Software ◽  
Surface Mapping ◽  
Part Geometry ◽  
Industrial Sectors ◽  
3D Geometry ◽  
Part Surface ◽  
Lot Sizes ◽  
Specific Part

AbstractMany industrial sectors face increasing production demands and the need to reduce costs, without compromising the quality. The use of robotics and automation has grown significantly in recent years, but versatile robotic manipulators are still not commonly used in small factories. Beside of the investments required to enable efficient and profitable use of robot technology, the efforts needed to program robots are only economically viable in case of large lot sizes. Generating robot programs for specific manufacturing tasks still relies on programming trajectory waypoints by hand. The use of virtual simulation software and the availability of the specimen digital models can facilitate robot programming. Nevertheless, in many cases, the virtual models are not available or there are excessive differences between virtual and real setups, leading to inaccurate robot programs and time-consuming manual corrections. Previous works have demonstrated the use of robot-manipulated optical sensors to map the geometry of samples. However, the use of simple user-defined robot paths, which are not optimized for a specific part geometry, typically causes some areas of the samples to not be mapped with the required level of accuracy or to not be sampled at all by the optical sensor. This work presents an autonomous framework to enable adaptive surface mapping, without any previous knowledge of the part geometry being transferred to the system. The novelty of this work lies in enabling the capability of mapping a part surface at the required level of sampling density, whilst minimizing the number of necessary view poses. Its development has also led to an efficient method of point cloud down-sampling and merging. The article gives an overview of the related work in the field, a detailed description of the proposed framework and a proof of its functionality through both simulated and experimental evidences.

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