International Journal of Rapid Manufacturing (9 papers in press)
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.
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
Keywords: Energy conservation; solar thermal energy; metal casting; scrap pre-heating; economics.
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: RDPM2019 Advances in Additive Manufacturing Technology and Applications
Mass optimisation of 3D printed specimens using Multivariable Regression Analysis
by Cristian-Vasile DOICIN, Mihaela-Elena ULMEANU, Allan E.W. RENNIE, Elena LUPEANU
Abstract: Since its introduction in the early 1990s Fused Deposition Modelling (FDM) has become the most popular additive manufacturing technology for a variety of applications. One of the reasons of its popularity amongst users is the affordability of the equipment, materials and the open source software. Given the large variety of combinations optimisation of FDM process parameters can be quite elaborate. The paper provides a method for optimisation of mass calculation using multivariable regression analysis. Layer thickness, printing temperature and printing speed were considered the independent variables for a two-level factorial experimental program. DOE was used to plan 12 sets of programs and analysis was undertaken using Design-Expert
Keywords: Optimised Mass Calculation; Material Extrusion; Design of Experiments; Multivariable Regression Analysis.
The effect of geometry on tensile strength of biodegradable polylactic-acid tensile-test specimens by material extrusion
by Alper Ekinci, Andrew A. Johnson, Andrew Gleadall, Xiaoxiao Han
Abstract: Additive manufactured biomedical devices have been widely used in the biomedical fields due to the development of biomaterials and manufacturing techniques. Biodegradable Polylactic Acid-based polymers are the most common material that can be manufactured using material extrusion, one of the most widely known additive manufacturing methods. However, medical grade polymers are too expensive for degradation studies with common tensile specimens. Therefore, this paper aims to reduce the volume of the material used for manufacturing tensile specimens by introducing a new micro-X tensile specimen developed for steel. The tensile strength of micro-X tensile specimens were compared with the ASTM D1708 standard tensile specimens. Experimental results and statistical analysis showed that there was no significant difference in terms of Tensile Strength. Furthermore, the micro-X tensile specimen reduced the volume and as well as the cost to 1% in comparison to ASTM D638 type V standard tensile specimens.
Keywords: Additive Manufacturing; Material Extrusion; Tensile Strength; Biodegradable PLA; Micro Tensile Test; statistical analysis.
Post-printing Characterisation and Design for Additive Manufacturing Considerations for Conductive Tracks 3D Printed by Material Extrusion
by Marko Chorbikj, Marco Cavallaro
Abstract: The goal of the study is to analyse the post-printing characteristics of conductive tracks 3d printed using Material Extrusion (ME) process with varying slicing strategies. Conductive track samples with constant width and varying heights between 0.4mm and 0.8mm were prepared using two different commercial conductive materials in a single, double and triple layer strategy. Post-printing functional analysis was done by measuring the resistance of samples at different lengths and comparing it to their corresponding counterparts fabricated with different slicing. Post-printing physical characterisation on selected samples was done by measuring the surface area of their cross sections using microscope images and their mass. The conclusions of the study were then transferred in a proposed set of Design for Additive Manufacturing (DfAM) considerations that can be taken into account in the Design and Process Planning phase when manufacturing conductive tracks or objects with such features using ME.
Keywords: material extrusion; design for additive manufacturing; conductive tracks; traces; 3d printing; fused filament fabrication.