International Journal of Rapid Manufacturing (27 papers in press)
Experimental Investigation on Mechanical Properties of Reinforced Al6061 Composites and its Prediction Using KNN-ALO Algorithms
by A. Thirumoorthy, T.V. Arjunan, K.L. Senthil Kumar
Abstract: Metal Matrix Composites (MMC) are widely practicing material for
improving the surface property. Stir casting is one of the most straightforward
processes of manufacturing MMC and attains higher advantages on material
processing cost, more comfortable handling of material, size, design and
excellent stability of matrix structure. In this research work, MMC of Al6061
with blended MgO and Si3N4 composite mixtures is produced using stir
casting process. One of the factors affecting the material homogeneity in the
casted material is the tensile rupture, where the proposed composite material
subjected to tensile stress and yielding. The structural property of the material
tested under Universal Testing Machine and Brinell hardness tester. This paper
proposes a novel hybrid approach to evaluate the tensile property of
composites. The prediction of the tensile property of the MMC performed by
the K-Nearest Neighbour Algorithm (KNN) and Ant Lion Optimization (ALO)
algorithm, which is numerically modelled and experimented in the running
platform of MATLAB and compared with Decision Tree (DT) classifier
algorithm for better performance outcome. Predicted test results show that the
proposed KNN-ALO is an efficient method for predicting the tensile and
hardness properties of stir cast aluminium composites.
Keywords: Metal Matrix Composites; Stir Casting; Tensile Strength; Brinell Hardness; K-Nearest Neighbour Algorithm.
Fabrication and micro-hardness properties of nano-Al2O3 reinforced aluminum metal matrix composite by Field-assisted sintering technique (FAST)/Spark plasma sintering (SPS) Processing Route.
by Pranav Dev Srivyas, M.S. Charoo
Abstract: Aluminum metal matrix composites are the advanced composites materials which are developed using different micro/nano reinforcements and metal matrix. The reinforcement may be ceramic or any other material which provides outstanding properties to those composite materials for various structural and functional applications. In this research work spark plasma sintering fabrication route was used for consolidation of pre-alloyed Al-Si alloy reinforced with different concentration of nano-Al2O3 i.e. 0, 2, 4, 6 and 8 wt%. The powder was ball milled in high energy planetary ball mill for 12 hours and then the fabrication was done at the optimum temperature of 450˚c with heating rate of 100˚c/min at normal loading pressure of 50 MPa and holding time of 10 min. SEM, EDS, XRD and Optical Microscopy was done for micro-structural analysis of the powder and the sample. Density measurement and micro-hardness of the sintered samples were also done using digital densimeter and micro-hardness tester respectively. It is concluded that the FAST/SPS fabrication route is an outstanding technique for the processing of aluminum matrix composites with better properties.
Keywords: SPARK PLASMA SINTERING (SPS); MECHANICAL ALLOYING (MA); MICRO-HARDNESS; REINFORCEMENT.
Effect of hardness and CNC milling roughness behaviour of A6061 aluminium alloy reinforced with TiC metal matrix composite
by G. Alagarsamy, M. Kathiresan
Abstract: Titanium Carbide (TiC) is added to Aluminium Alloy (Al6061) with
various weight proportion of 3%, 6% and 9% using stir casting method. This
work investigates hardness and CNC milling surface roughness for three
different weight proportion of AA6061 Metal Matrix Composite with 3%, 6%
& 9% of TiC. CNC milling operation is carried out with the cutting speed 75
m/min, 85 m/min, 105 m/min (2500, 3000, 3500 rpm), feed rate (0.3, 0.7, 0.9
mm/rev) and constant depth of cut (0.1mm) for the 10 mm slot in three places
and it average roughness value were calculated. Finally it is concluded that the
result not only the cutting parameters are given the minimum value, but
percentage of material contribution also inovlved in surface roughness value
indicated by the experimental result. Scanning Electron Microscope (SEM)
analysis and Energy Dispersive Analysis of X-rays (EDAX) spectrum also
crried out for the AA6061alloy and other 3% TiC with AA6061 composite.
Keywords: MMC; Hardness; Surface Roughness; SEM.
Surface Modification of AZ61 Magnesium alloy with nano-Al2O3 using Laser Cladding Technique: Optimization of wear properties through Hybrid GRA-PCA
by S. Sundaraselvan, N. Senthilkumar
Abstract: The aim of this research is to investigate the wear behaviour of surface modified AZ61 Magnesium alloy with nanoceramic reinforcement (Al2O3), done by laser cladding technique. Nano Al2O3 is added in three different weight proportions viz., 5%, 10% and 15% on to the surface of AZ61 using Nd:YAG laser. Dry sliding wear behaviour of the surface modified AZ61 material is studied considering various reinforcement of nanoceramic particles and by varying the speed and axial load in the pin-on-disc apparatus. Experiments were designed using Taguchis design of experiments and the measured outputs viz., wear, coefficient of friction and frictional force were analyzed using Grey Relational Analysis (GRA), coupled with Principal Component Analysis (PCA) for multi-variate optimization by calculating multi-response performance index (MRPI). Using SEM image, distribution of particles in the magnesium alloy matrix is studied. It is observed that the % reinforcement of nanoceramic particles on the surface of AZ61 alloy is the most critical factor that contributes by 79.30% towards the MRPI, followed by 9.91% contribution by load and speed by 7.94%, as determined from Analysis of Variance (ANOVA). From confirmation experiment, the optimized condition shows an improved wear resistance obtained from the surface modified magnesium alloy.
Keywords: AZ 61 Magnesium alloy; Laser Cladding; Grey Relational Analysis; Principal Component Analysis; Pin-on-disc.
Soft computational modeling and regression analysis for thermal properties of nanofluids
by Kavitha Sridhar, P. C. Mukesh Kumar
Abstract: An emerging feature of nanofluids is thermo physical properties, which leads to develop an enormous applications in various fields. The enhancement of thermal conductivity of nanofluids, induce to use as an engine coolant in air conditioning, automobile radiators and in refrigeration. Thermal properties of nanofluids were found by experimental models and by various mathematical models. There is no accordance between these two models. To ease the process of prediction and for better accuracy soft computing tools were utilized. To enhance accurate prediction, various machine learning algorithms were used. In this paper to predict the thermal conductivity ratio of CNT/H2O, Gaussian process regression (GPR) methods with different kernel functions otherwise called as co-variance functions were proposed. The predictions were evaluated by various evaluation criterion. The present modeling has been carried out using MATLAB 2017 b. Among all other kernel functions, squared exponential co-variance function, rational quadratic co-variance function possesses accurate prediction and good generalization behavior. To optimize the proposed GPR model, hyper parameters were used. The Root Mean Square Error (RMSE) value of squared exponential co-variance function with hyper parameter is 0.014926, and Regression coefficient value (R2) for overall data is 0.98. The prediction of thermal conductivity ratio values by using GPR model and the experimental values possess very good agreement between them. GPR model with fewer data set, possess generalization behavior, accurate prediction and low computational complexity. The outcome of the predicted model will reduce the experimental test runs and ease to predict the thermal conductivity ratio of nanofluids and helps to increase the usage of it in various fields especially in automotive sector.
Keywords: Nanofluids;thermal conductivity;soft computation;gaussian process regression; co-variance function.
Experimental investigations on optimization of parameters to produce W-TiC composites using powder metallurgy route
by SUKUMAR SELVARAJ, ELATHARASAN G
Abstract: In this research work, the effect of Titanium Carbide (TiC) in Tungsten (W) matrix to be analyzed. The W matrix composites contain different weight percentage (0, 4 & 8) TiC particles were produced by ball milling and powder metallurgy methods. The required quantity of powders were milled and compacted in a hydraulic press with a suitable punch and die. The sintering was done at a temperature of 1400
Keywords: Microstructure; Ball milling; Sintering; Powder metallurgy; Taguchi analysis.
ANALYSIS OF COMPLIANT DAMPER AND ITS EFFECT ON TURNING OPERATION FOR IMPROVING SURFACE QUALITY
by G.SATHYAPRIYA GANESAN, U.NATARAJAN
Abstract: This article investigates the parameters affecting the roughness of surfaces produced during turning operation using a vibration isolating compliant damper. The vibration is considered to be a major challenge in the production industry while deciding the optimum machining parameters. The use of compliant damper is more economical in vibration isolation compared to the conventional dampers. To avail the best result, an appropriate optimization technique may be used. However, it is the designing of damper that makes it critical such that no specific procedure or formulation has been identified. In this work, several approaches were made in the design stage itself and the model with the significant vibration absorption capacity was manufactured. The very reason where a compliant damper can be utilised in order to reduce this unnecessary vibration and improves the surface texture of the finished product. The experimental results were analysed for the importance of compliant damper and the influence of machining vibration in product quality. A significant reduction of about 18% of vibration and 47% of surface roughness was observed when using compliant damper made of mild steel material. rnrn
Keywords: Keywords: Complaint damper; vibration reduction; surface roughness; machining parameters; response surface analysis.
Analysis of Mechanical and micro structural property of Aluminium metal matrix (LM25) composite hybrid with Nano silicon carbide and Nano alumina as reinforcement particles.
by DEEPAK ARAVIND V, Gopal P, Viswanathan A
Abstract: The effect of reinforcement of Silicon Carbide Nano Particle (SiCnp) and Nano Alumina Particle (Al2O3np) in base matrix composite of Aluminium (LM25) alloy is studied. By using stir casting method the hybrid Aluminium Metal matrix Nano Composite Samples (AMNC) are made. The addition of nano particles in a base matrix increases the strength compared to Pure LM25 Aluminium alloy. The distributions of reinforcement particles are evident in the EDAX and SEM analysis. Both the density test and compression test results of AMNC samples are compared with the pure LM25 Aluminium alloy. The result suggests that Sample 3 of AMNC is having high density and compression strength when compared to other two AMNC samples and Pure Sample. By increasing the percentage of reinforcements in matrix phase influences the increase in their mechanical properties. Aluminium matrix based nano composites (AMNC) having high density, Compression strength and wear resistance than pure Aluminium. Particularly LM25 based Aluminium series. The above results indicates that the AMNC have excellent corrosion resistance and good fluidity but limited strength in high temperature. Now a days LM25 based AMNC samples are widely used in aerospace and automobile industries due to its good mechanical properties, better corrosion resistance, high specific strength and low thermal co-efficient of expansion compared to other metals and alloys applications.
Keywords: : LM25 Al Metal Matrix Nano Composite Sample (AMNC); Silicon Carbide Nano particle (SiCnp); Nano Alumina Particle (Al2O3np); Scanning Electron Microscope (SEM); Energy Dispersive X ray Spectroscope (EDAX); Micro meter (.
Effect of Optimized Cutting Constraints by AlCrN/Epoxy Coated components on Surface roughness in CNC Milling
by BOVAS HERBERT BEJAXHIN, G. Paulraj
Abstract: Here in this work, the milling slots are produced on EN32 MS plate machined with coated HSS end milling cutters and Fusion Bonded Epoxy coated BT40 tool holders. Tool coatings TiN, TiAlN, and AlCrN are preferred in the process of PVD method. This experiment benefited to differentiate the surface roughness for various speed, feed, and depth of cut. The prediction of effective stress for tool work interaction through the dynamic simulator Deform3D. An L27 array is designed with a controllable response to machining conditions, coating types which affect the desired output Ra. Taguchi and ANOVA approach supports to determine the most significant parameters. The influence of coated tools pooled with Fusion Bond Epoxy (FBE) coated taper end BT40 milling tool holder used to elevate Ra. Thus the optimized values of surface roughness were obtained and the effect of input parameters was identified on specimen roughness. Comparisons have made in between the roughness and stress effective of simulator tool for inspiring the clear solution.
Keywords: Coating; CNC Milling; Surface roughness; Epoxy; Taguchi.
Additive Manufacture of TiB2/Ti-6Al-4V Metal Matrix Composite by Selective Laser Melting
by Peter Farayibi, Taiwo Abioye
Abstract: Since the advent of layer based and blown powder methods for additive manufacture the geometrical design freedoms which these processes allow have been widely applied. However, limited research has been undertaken investigating the design freedoms that are granted through these manufacturing processes to date. Furthermore, there has been little investigation into the development of materials specifically formulated for additive processes. In this study a new material combination is evaluated for use with selective laser melting (SLM) methods of additive manufacturing. A 10 wt.% fine TiB2 powder was satellited onto the surface of a 90 wt.% Ti-6Al-4V powder to prevent segregations and promote homogeneity during processing. Solid structures of TiB2/Ti-6Al-4V were built using SLM Realiser 50 machine. Thereafter, the built structures were subjected to microstructural examination using optical and scanning electron microscopies. The hardness of the structure was determined using Vickers hardness tester. Results revealed that there was a reactive decomposition of the TiB2 powder which led to the formation of short (length ≤ 10 μm) and long (20 25 μm) TiB whiskers as reinforcements in the composites. The composite hardness was measured to vary from 440 503 HV0.3, signifying 30% increase when compared to Ti-6Al-4V hardness (350 HV0.3). The study thus demonstrated that miniature functional parts, requiring synergetic properties achievable with composites, can be manufactured using SLM.
Keywords: Selective Laser Melting; Additive Manufacture; Microstructure; Hardness; Composite; Reinforcement; TiB; Ti-6Al-4V; TiB2; Whiskers.
Effect of Process Parameters on Microstructural and Mechanical Properties of Friction Stir Welded Dissimilar Aluminium Alloys AA 6061 and AA 7075
by Manikandan R, Elatharsan G
Abstract: Frictions stir welding of dissimilar alloys are an efficient way to industrial applications. The effect of joining dissimilar alloys (AA6061-AA7075) to improve the strength of the joint materials of efficient stir weld. This work micro-hardness and mechanical properties of frictions stir welded dissimilar alloys has investigated. Aluminium alloy which is heat treatable and subjected to either hot working or cold-working. The heat treatment followed by revolutionizing and precipitation hardening. Micro hardness has measured at various zones of the welded joints. The tensile properties of dissimilar joints are characterized .Tensile test results will published and the stress-strain curve indicated the mechanical properties causes the frictions stir welding parameters. . Cylindrical threaded profile has to do important role among the other tool profiles. It contributes 93% to the overall efficiency. High strength of 172 MPa attained the tool made up of cylindrical threaded pin profiled tool. This work inferred that the rotational speed transverse speed, and D/d ratio for cylindrical threaded has considered more efficient. Maximum tensile strength could be obtained from the cylindrical threaded tool and it has comparatively high as other than materials. Tensile and hardness measurement done on this part of material characterization.
Keywords: FSW; Micro hardness; dissimilar alloys; heat treatment; cylindrical.
FATIGUE BEHAVIOUR OF ALUMINIUM REINFORCED METAL MATRIX HYBRID COMPOSITES (Al 6061+SiC+Mg+TiO2)
by KRISHNARAJ S, ELATHARASAN G
Abstract: In this paper researched the Metal Matrix composites (MMCS) by blend throwing procedure and distinguished the disfigurement quality of the material. This system used to produce good strength of the aluminum 6061 with fortified with SiC, TiO2 and magnesium (Mg).The weariness execution exceptionally hard to comprehend for the new composite materials. That approach to describe the new composites utilizing Scanning Electron Microscope (SEM) and malleable ductile weariness test has analyzed. The hybrid composites are increased the strength for a contribution of reinforced particles. The fatigue behaviour of developed composites has analyzed at the room temperature for the low cycle fatigue. The fatigue cyclic loading conditions obtained the better yielded strength of the new hybrid composites. The working conditions pursued by the low cycle weariness recurrence level 1 to 25 HZ and also of HCF. The diminishing existence of the metal framework in view of the LCF strain sufficiency for the room and hoisted temperature 3000 C and R= (εmin/εmax) =0. The experiments deliberate with continuous amplitude for a prearranged strain of amplitude. The disfigured assessment of weariness standard and thoroughly considered the mean pressure an incentive as far as weakness life acquired in the test results. Although forecast the fatigue life based on the experiments conducting this observed the fact of plastic energy and elastic energy.
Keywords: Fatigue life; Metal Matrix Composites; Aluminium Reinforcement.
OPTIMIZING THE WEAR PERFORMANCE OF HVOF THERMAL SPRAY
COATED TI-6AL-4V ALLOY BY GREY RELATIONAL APPROACH
by THIRUMALVALAVAN S, SENTHILKUMAR N
Abstract: In this present investigation, wear studies on uncoated Ti-6Al-4V alloy and HVOF coated alloy was studied. For improving the wear resistance of titanium alloy, ceramic coating is performed on the surface. Ti-6Al-4V alloys with SiC ceramic coating have significant attention due to improved tribological properties without affecting the corrosion and wear resistance of the alloy. Characterization of uncoated and coated surface was also made by means of micro hardness test and tensile test. Dry sliding wear behavior is studied with the help of pin-on-disc apparatus. The experiments were designed by using Taguchis design of experiment (DoE); an L16 (4^4) orthogonal array is selected for four parameters varied through four levels. The experimental work depicts the influence of control factors such as load, speed, distance and track diameter on the dry sliding wear behavior of uncoated and SiC coated Ti-6Al-4V alloy. For evaluating the measured output responses, grey relational analysis is applied for performing multi-objective optimization. From experimental results; wear loss decreased by 35.71% due to SiC thermal spray coating compared to uncoated material. Application of statistical tool, analysis of variance (ANOVA) for grey relational grade suggests that, among all four parameters speed contributes by 54% on SiC coated, and track diameter contributes by 42.97% on uncoated Ti-6Al-4V alloy, towards responses and are the most influencing factor on the wear loss of the tested specimen. Confirmation experiment performed with optimum conditions provides lower wear loss. To investigate the wear surfaces SEM micrographs and EDS analysis is carried out.
Keywords: Ti-6Al-4V alloy; HVOF; Pin-On-Disk; Taguchi’s DoE; Grey Relational Analysis; ANOVA.
Experimental investigation and Fuzzy logic modeling of CO2 laser cutting parameter for AA 6061-T6 sheet
by Parthiban Alagesan, Sathish Shan, Ravikumar Rangasamy, Prakash Pons
Abstract: The laser machining is thermal energy based process. The aluminium alloy is highly reflective material to difficult to cut by using laser cutting process. The present paper are experimentally investigated about the CO2 laser cutting of Aluminium AA 6061-T6 alloy material with to improvement of geometrical accuracy of the curved profile at the same time to minimize the top, bottom kerf width and kerf deviations. The experiments carried out by using fuzzy logic approach and to predict the effect of CO2 laser cutting quality based on the cutting parameters on laser power, Cutting speed, Gas Pressure and focal position. The fuzzy logic model is used on Fuzzy logic tool box of MATLAB using Mamdani technique. The relationship between experimental value and fuzzy model are compared. Finally based on the results the proposed fuzzy logic models are minimized Top, Bottom kerf width and Kerf deviations of CO2 laser cutting of AA6061-T6 aluminium alloys.
Keywords: Fuzzy Logic; CO2 Laser Cutting; AA6061-T6; Kerf Width.
Investigation on Corner Accuracy in Wire Cut EDM of AISI D3 tool steel
by G. Selvakumar, V. Balasubramanian, N. Lenin
Abstract: Wire cut Electrical Discharge Machining (WEDM) of AISI D3 tool steel has been reported in this study. The AISI D3 steel is extensively used in tool and die making industries. The machining of ulta-precision dies with the required corner accuracy and surface finish is only possible through WEDM process. It is known fact that the wire deflection and the wire rupture are the problems associated with the WEDM process (Lin et al. (2001), Sarkar et al. (2011)). The wire deflection at the corner is causing corner error. The objective of the present work is to minimize the corner error by modifying the programmed path of the wire.
The experiments were conducted based on Taguchis L-27 orthogonal array. The influence of the control factors namely workpiece thickness, flushing nozzle height, corner angle, pulse on time, pulse off time, peak current and wire tension on the process responses such as Area removal rate (ARR), surface roughness (Ra) and corner error (CE) were studied. A set of pilot experiments were carried out by modifying the programmed path (wire path) in view of improving the corner accuracy of the profile. A good improvement in corner accuracy (about 25%) has been achieved.
Keywords: WEDM; AISI D3 tool steel; Corner error; wire path modification.
Special Issue on: 21st Century Manufacturing
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.
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;.
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: Cyber Manufacturing – Emerging Frontiers in Sensing, Modelling and Control
Krill Herd Based Optimal Neural Network (KHNN) For Analyzing Safety and Quality Performance at Construction Site
by Balamurugan S.
Abstract: In construction exertion, an organization's capacity to convey a quality item in a protected way is the way to business achievement. In order to better comprehend what adds to productive quality and safety programs in construction. The vast majority of the researchers have focused on examining optimization models to create optimal construction site format offered inspired algorithms. In this paper analyzed the safety measures in a construction site for high-quality. Here two distinctive soft computing methodologies are Artificial Neural Network (ANN) and optimization model. This expectation investigation considers two distinct parameters like reworkers and defects in a construction site. For improving the performance enhance hidden layer and neurons in ANN structure utilizing Krill herd optimization strategy so the proposed model as Krill Heard Neural Network (KHNN). From this examination get least Mean Square Error (MSE) and maximum accuracy as 88, 95.26% compared with our existing techniques.
Keywords: Construction; safety; neural network; optimization.
Quality assurance in additive manufacturing of thermoplastic parts: predicting consolidation degree based on thermal profile
by Mriganka Roy, Olga Wodo
Abstract: Additive manufacturing is one of the most prominent and promising technologies in the field of manufacturing. However, its current dissemination is largely limited to the prototyping role due to inadequate quality assurance. The detailed process-geometry-properties relationships are still to be unveiled, even though AM is based on highly repetitive process. In this work, we aim to address this gap by leveraging the numerical prediction of the thermal behavior of the deposition to predict the properties of the printed part. In particular, we present a prediction of consolidation strength in fused filament fabrication. The proposed protocol is universal and can be applied for any deposition condition and geometry. This contribution has important implication for prefabrication quality assurance in AM as it allows to link process parameters with part properties for any geometry hence opening new avenues for process optimization.
Keywords: quality assurance; additive manufacturing; fused filament fabrication; finite element method; reptation; consolidation; bonding; thermoplastics.
Data-Driven Calibration for Infrared Camera in Additive Manufacturing
by Jack Francis, Mojtaba Khanzadeh, Haley Doude, Vince Hammond, Linkan Bian
Abstract: Non-contact infrared (IR) measurement devices are currently used to monitor the thermo-physical processes during additive manufacturing (AM). A common IR device for thermal monitoring, the IR camera, requires a blackbody calibration in order to be used effectively, as the camera measures the radiant energy (irradiance) instead of the true temperature. This calibration is difficult, expensive, and requires specialized equipment. Therefore, this article details a data-driven calibration for IR cameras by comparing the lengths of cutoff regions captured by the pyrometer and IR camera. After scaling and interpolating pyrometer images, a similarity metric is developed that characterizes the relationship between irradiance and temperature. An application of the IR camera for monitoring thermo-physical processes is discussed in detail. rnKeywords: Infrared Camera, Additive Manufacturing, Calibration, Pyrometer, Sensor Fusionrn
Keywords: Infrared Camera; Additive Manufacturing; Calibration; Pyrometer; Sensor Fusion.
Collaborative Robot Selection using Analytical Hierarchy Process (AHP)
by Christopher Greene, Silpa Subash
Abstract: The research addresses the deficiency of a structured methodology for the selection of collaborative robots or cobots, a type of an industrial robot that can perform tasks in cooperation with a human operator in a shared workspace. Without a standard procedure, manufacturing and service industries may experience difficulty determining a suitable cobot for their collaborative robot application. The decision to select a suitable cobot requires multiple requirements that may need to be considered along with the multiple choices of cobot alternatives available from various manufacturers. This decision may be difficult because there has been no literature that addresses the requirements that needs to be considered for cobot selection. Identifying the requirements may serve as the standard criteria for evaluation of the various cobots available as of now. The research is focused on determining the specific criteria useful for evaluation of various cobots. Subsequent to the determination of the criteria for cobot selection, an improved multi-criteria decision-making (MCDM) algorithm will be utilized to illustrate the methodology for the selection of a cobot suitable to the manufacturing or service industry.
Keywords: Collaborative Robot; Cobot; Cobot Selection; Multi-Criteria Decision-Making; Analytical Hierarchy Process.