International Journal of Rapid Manufacturing (15 papers in press)
Power Consumption Investigation for Fused Filament Fabricated Specimen
by Hunter Hinshaw, Shane Terry, Ismail Fidan
Abstract: This paper describes a research project comparing various settings of current 3D printers and the effect on part quality and machine efficiency. The goal of this research is to determine the most appropriate parameters with which to 3D print any component. The chosen settings should provide a final product of quality while being efficient within three categories: print completion time, part weight, and Kilowatt-per-hour consumption. The purpose being to establish a set of parameters that will provide the sought-after efficiency on any Fused Filament Fabrication (FFF) 3D printer, in any application, for any production part. These parameters could prove to benefit Additive Manufacturing (AM), saving time, material, and electrical energy cost. This study provides results for the most efficient settings across three parameters: layer height, infill ratio, and shell count. Through testing, given the experimental set-up and parameters, 0.3mm, 3 Shells, 25% Infill was the most efficient array of settings in this application.
Keywords: additive manufacturing; 3d printing; efficiency; electrical; case study; slicing; print profiles.
Special Issue on: 21st Century Manufacturing
PHANTOM HOLES: OPTIMIZED INTERNAL STRUCTURAL DESIGN FOR USE WITH ADDITIVE MANUFACTURING, TYPICAL FUSED FILAMENT FABRICATION SYSTEMS
by Eric Wooldridge
Abstract: It is understood that additive manufacturing (AM) allows the designer to control the exterior shape and internal structure for the design and fabrication of products. However, although AM allows for some internal structural control, how the designer controls that internal structure is limited to the options of the slicing software and the equipment. The designer does not have options within current slicer software to create customized shapes of concentrated material within the internal structure. Designers have to increase the infill throughout the entire object to address a limited area material failure zone. This paper introduces a methodology known as the Phantom Hole (PH) technique that will allow designers to create custom shaped, solid, internal structures within objects fabricated by many Fused Filament Fabrication (FFF) machines. In initial shear and flexural testing, the PH technique resulted in a 39% improvement in specimen loading performance over specimens fabricated with higher infill percentages.
Keywords: Additive Manufacturing; FFF; Fused Filament Fabrication; FDM; Fused Deposition Modeling; 3D Printing; Phantom Holes; Desktop 3D Printers; 3D Printer; Optimized Internal Structure; Infill; Slicer; topology; Internal Topology; optimized topology; Internal reinforcement; Perimeter shells; Phantom Hole technique;.
A smart decision making tool for cleaning process planning in remanufacturing
by Juan Martinez, Zhenhua Wu, Jianzhi Li, Miguel Gonzalez
Abstract: Equipping stakeholders with advanced tools to make better decisions for sustainable production is key to research in smart manufacturing in the 21st century. A smart decision tool to select the optimal cleaning processes for remanufacturing is presented in this paper. The approach started from formulating the process selection problem to a linear programming model to minimize the cost while observing the constraints of part cleaning level, processing time, and energy consumption. In order to model the vague and uncertain information associated with contamination, cost, time and energy consumption, fuzzy sets were applied. Finally, a genetic algorithm was proposed to search for the optimal solution to the mathematical model. Further, a software prototype was coded in Matlab
Keywords: smart decision; cleaning; process planning; remanufacturing.
A Statistical Approach for Process Optimisation of Digital Light Processing (DLP) 3D Printing Process
by Ergin Erdem, Arif Sirinterlikci
Abstract: This study focuses on experimental design based approach for process optimisation of a custom-made digital light processing 3D printer. Output measures are developed taking precision and accuracy into consideration. Initial runs were conducted to identify the prominent factors which might play role on output measures. The results indicate that the layer thickness plays a significant role for the two of the developed output measures, photopolymerisation time for one measure, and sequence time for two measures as the interaction-effects also play a role to some. A composite figure that considers all three output measures simultaneously are also developed and a stepwise regression analysis is conducted to identify significant factors. The regression model has moderate R2 value (68.12%), also indicating that layer thickness and photopolymerisation period play a role. The recommended levels for layer thickness is found to be 0.2 millimetres and photopolymerisation period as 12 seconds based on the composite figure.
Keywords: Process optimisation; design of experiments; digital light processing; 3D Printing; stepwise regression.
Mass production strategy for additive manufacturing by stacking the product at design phase
by Arivazhagan Pugalendhi, Rajesh Ranganathan, M.P. Sreekanth
Abstract: Mass production is usually aimed to reduce the costs involved in product development by increasing the number of units without compromising the quality. Additive manufacturing (AM) technology can reduce the manufacturing lead time; however, it is widely seen as a non-mass production system due to its build volume restrictions and many other factors. In this paper, a strategy named as stacking of parts during modeling/design phase is recommended to overcome the above-mentioned limitation. Objet260 Connex PolyJet AM machine is used for this study. A square component and a washer are used for experimental purpose. From the study, it is evident that by adopting a different strategy during the design phase, mass production approach can be adopted in AM. The sample work of a square component proved that model material is reduced by 61.05% and support material is saved by 91.53% for square component with stacking (8 x 8 x 33) in the design phase when compared to building a single component. Alternatively, there is a reduction in material consumption for washer by 73.46% for model and 87.14% for support (8 x 8 x 48), as compared to manufacture of single washer component. Further, the number of parts which can be built with stacking in the design phase have increased drastically compared with the case of the array made using Objet studio. Finally, mechanical properties were also analysed in terms of the parts quality. This research paper provides a unique way of meeting the mass production strategy of AM machine, with a novel approach adopted during the pre-processing stage.
Keywords: Mass production; Additive manufacturing; PolyJet; stacking; build volume; material consumption.
Teaching leadership in additive manufacturing: doing the right thing, before doing it right
by Jennifer Loy
Abstract: As additive manufacturing matures, there is sufficient critical mass in the industry and market place to justify the development of more comprehensive and cohesive educational strategies. This article is informed by research into the emerging educational landscape for the technology. The article highlights the breadth of educational strategies currently employed and considers drivers for additive manufacturing education and their development in the context of supporting the education of both an effective, as well as efficient, workforce for the future.
Keywords: Education; engineering; industrial design; strategy; workforce; future; Industry 4.0; production; training; teaching; leadership; additive manufacturing; 3D printing.
Investigation of the Tensile Properties in Fiber-Reinforced Additive Manufacturing and Fused Filament Fabrication
by Yolnan Chen, Cesar Ortiz Rios, Astrit Imeri, Nicholas Russell, Ismail Fidan
Abstract: This research project examines how fiber orientation affects the strength of a part produced by Fiber-Reinforced Additive Manufacturing (FRAM) process. Tensile specimens with varying fiber orientations were made using a 3D printer capable of printing with carbon fiber (CF), Kevlar (KV), and fiberglass (FG). Various tensile tests have been performed for different fiber orientation and materials. The strongest fiber orientations, in descending order, were two ring concentric with isotropic fill and five ring concentric fill. While fiber orientation and infill percentage could be specified for each layer, the fiber starting location was automatically determined which sometimes resulted in decreasing strength of the part by introducing stress concentration. Currently, industrial trends in the utilization of Fused Filament Fabrication (FFF) printers are mostly on PLA and ABS based polymer materials. And, there is no comprehensive study available investigating the relations between these traditional FFF processes and continuous FRAM processes. The aim of this study is to provide an in-depth tensile property analysis showing the advantageous of FRAM compared to conventional FFF technologies.
Keywords: Fiber-Reinforced Additive Manufacturing; Tensile Test; Concentric; Isotropic; Fused Filament Fabrication.
Experimental and numerical investigation on the effect of layer thickness during laser powder-bed fusion of stainless steel 17-4PH
by Zhidong Zhang, Usman Ali, Yahya Mahmoodkhani, Yuze Huang, Shahriar Imani Shahabad, Adhitan Rani Kasinathan, Ehsan Toyserkani
Abstract: Layer thickness is one of the most important input process parameters in Laser Powder-Bed Fusion (LPBF) additive manufacturing (AM) since it directly affects the level of defects in the final products, such as porosity and cracks and also the manufacturing rate. In this work, three-dimensional finite element heat transfer model was employed to compare and evaluate two different powder layer thicknesses (20 μm and 40 μm) at varying laser power and scanning speeds. A layer-thickness dependent laser absorptivity approach was considered to improve the prediction accuracy of the proposed model. Single track experiments with stainless steel 17-4PH were conducted to validate the simulation model. Simulation results show good agreement with the experimental results with different layer thicknesses. The corresponding averaged melt pool error for width and depth were 4.2% and 9.1%, respectively. It is found that the melt pool dimensions with different layer thicknesses are similar for the most part with slight variations in the melt pool dimensions using varying laser power and scanning speed. However, the morphology of the melt pool track shows visible changes between different thicknesses.
Keywords: Additive manufacturing; Laser powder-bed fusion; Layer thickness; 3D-Heat transfer modeling.
A comparison framework to support the selection of the best additive manufacturing process for specific aerospace applications
by Alberto Garcia-Colomo, Dudley Wood, Filomeno Martina, Stewart Williams
Abstract: Additive Manufacturing (AM) is a cutting-edge technology that provides up to 100% of material efficiency and significant weight reduction which will positively impact aircraft fuel consumption in addition to high design freedom. Consequently, many aerospace companies are considering implementing AM thanks to these benefits. Therefore, the aim of this research is to assist aerospace organisations with a selection among different AM technologies. To enable this, primary data from (8) experts in the field of AM was collected through semi-structured interviews and cross-referenced with secondary data to identify the key factors for consideration in the selection of AM equipment for aerospace applications. Four AM technologies Laser Powder Bed Fusion (LPBF), Electron Beam Powder Bed Fusion (EBPBF), Wire Arc AM (WAAM) & Laser Metal Deposition (LMD) were highlighted by the experts as the most appropriate for aerospace applications. The main outcome of this study is the development of a comparison framework that helps companies select their AM technology depending on their main business or specific application.
Keywords: Additive Manufacturing; aerospace; business drivers; decision-making.
Special Issue on: ICONEEEA-2K19 Impact of Nanomaterials in Rapid Manufacturing for Industrial Challenges
Tool Wear Investigation of Micro-textured and Non-Textured Carbide inserts for Machining Industrial Component
by Sathiya Narayanan Nagarajan, Baskar N, Metin KOK, Rohit Sankaran, AanandhaManikandan G
Keywords: Micro-Texturing; Cross-Chevron; Tool Wear; Dimensional accuracy; surface finish; Industrial Component.
Process Evaluation and Optimization of Friction Welding Parameters on Aluminium Grade 6061 by Direct Drive Friction Welding Method
by Karthikeyan Sambandham, Baskar N., Ganesan M., Gayatri R., Z.W.Zhong
Abstract: The expansion of joining processes is very essential in the field of manufacturing to satisfy the industrial needs and customer expectations. Friction welding processes is one of the solid-state welding processes in which similar/dissimilar materials are joined without the use of filler materials. In this experimental investigation, Aluminium Grade 6061 is used as the test specimen for the welding process because of its wide variety of applications in manufacturing and automobile industries. In this research work, a radial drilling machine is used for joining the similar combination materials of Aluminium Grade 6061. The input process parameters such as specimen diameter, upset time and spindle speed are used to evaluate the output response like axial shortening, hardness and impact strength. The input process parameters are selected and investigated using the Taguchi Design of Experiments (DoE) method based on L9 orthogonal array and Particle Swarm Optimization (PSO) Techniques. The major plan of this investigational work is to optimize the friction welding process parameters on axial shortening, impact strength and hardness of the friction bonded specimen.
Keywords: Friction Welding Process; Input Process Parameters; Output Responses; Optimization Techniques.
Performance Analysis of Untreated Tungsten Carbide Tool and Cryogenically Treated With Oil Quenched Tungsten Carbide Tool While Turning Of Inconel 713c
by Vijayakumar S, Parthiban V
Abstract: Inconel 713C bars are widely used in aviation industries and engineering applications. Machining of Inconel 713C superalloy has been performed by using untreated and cryogenically treated with oil quenched tungsten carbide (WC-Co) tools. The performance enhancement of untreated WC-Co carbide tool and cryogenically treated with oil quenched WC-Co tool were checked and they were estimated for their properties through Vicker hardness (untreated tools 1601 HV, cryogenically treated with oil quenched tools 1881 HV), and also were administered to machining of difficult to cut material Inconel 713Csuperalloy under dry condition. The acquiesced cutting speed ranges from 70 to 110m/min which shows its unique parameters of cutting speed in machining Inconel 713C with WC-Co tool. The effect of untreated and cryogenically treated with oil quenched WC-Co carbide tool was evaluated in turning of Inconel 713C on tool wear by using scanning electron microscope (SEM). The sedimental chip morphology is observed in untreated WC-Co tools and the chip morphology of cryogenically treated with oil quenched WC-Co carbide tools are uniform. Obviously cryogenically treated tungsten carbide tools indicated better execution when contrasted and untreated WC-Co tools.
Keywords: Inconel 713C; dry machining; cryogenic treatment; chip morphology.
Comprehensive Analysis on Aluminum in Sand Casting by Using Intelligent Techniques
by Mahesh Ganesan, K.Murugu Mohan Kumar, S. Bharathi Raja, Z.W. Zhong
Abstract: Today's foundry intentions are to succeed the cost-effective casting process. As a consequence of this goal, most of the researchers established numerical models for effective outputs. Numerical models of casting parameters have more considerable outputs for the foundry planner. Generally, the sand casting process comprises numerous parameters interdependently. If the parameters are not measured properly, the mould cavity is forced to reach the defects like porosity and blowholes. To overcome these defects, an extensive study on these factors is needed. During solidification, the important parameters like furnace, sand and vent holes affect the material properties. The molten temperature, pouring time and holding time are most significant parameters in sand casting. Aluminium is one of the highly desirable materials in sand casting. In this work, the various furnace parameters are analysed and compared using artificial neural network (ANN) and fuzzy logic models. The hardness and surface roughness are analysed and the work pieces are tested by using NDT techniques.
Keywords: Aluminum; sand casting; DOE; ANN; FUZZY; NDT.
Experimental prediction and investigation of spring back in V bending profile process modeling using Artificial Neural Network
by KATHIRVEL CHINNAYADEVAR, M. Saravanan, K. Vetrivel Kumar
Abstract: The model which is used to speak to including yield connections to wide a wide range of parameter space for foreseeing responses repeatedly is an Artificial Neural Network (ANN).Several researchers focused on the improvement of investigative, semi-logical and numerical models to anticipate the springback and curve force in air bend. The huge researches are abridged quickly.ANN has high adaptability in fitting an informational collection and, therefore, they are used regularly in making inexact models. The qualities of ANN, for example, vigor, adaptation to non-critical failure, parallel usage and capacity to delineate non-straight connections and collaborations of process parameters, make it a promising device for displaying many assembling issues. In this research ANN has picked up noticeable quality as an expectation U bending profile among the researchers of sheet metal bend as the information included are mind boggling and the relations of parameters are very non-straight to comparing RSM .
Keywords: Artificial neural network [ANN]; Extensive parameter; logical parameters; V bending process.
Special Issue on: ICONEEEA-2K19 Impact of Nanomaterials in Rapid Manufacturing for Industrial Challenges
Performance Analysis of Solar box Preheaters for Energy Conservation in Metal Casting
by P.Sathis Kumar, Baskar N, Metin KOK
Abstract: In metal casting, the melting process uses around 70 % of the total energy consumed by the entire industry. If this energy consumption can be reduced, it will go a long way in addressing the energy security needs of the current society. This research work aims at reducing this energy consumption by pre-heating the raw material in a solar box set-up. Mild steel raw material in the form of billets of different thicknesses were subjected to sunlight at controlled conditions to absorb the radiant heat to get preheated. The main objectives were to understand the relationship between the energy absorption by the metal scrap and the factors that influence it (such as solar flux density, scrap thickness and the duration of exposure) and to estimate the conservation potential of this method on the energy and economic fronts. The experimental results showed that the metal scrap achieved a preheat temperature of 140 °C during the peak solar irradiance. This translates to 56.50 kJ/kg of savings in melting energy. When this method is extended to the Indian foundries scenario, the energy (electricity) savings would be around 523.96 million kWh, which gives rise to economic savings to the tune of Rs.471.56 crores a year. Thus, this technique of solar thermal preheating holds promise for future energy and environment related problems and hence deserves further studies for industrial implementation.
Keywords: Energy conservation, solar thermal energy, metal casting, scrap pre-heating, economics