Manu Srivastava

Distribution of reinforcement particles in surface composite fabrication via friction stir processing: Suitable strategy

ABSTRACT Fabrication of metal matrix surface composites (SCs) is an emerging trend of friction stir processing applications. Key factors affecting the properties of SCs are process parameters, tool geometry, tool dimensions and reinforcement strategies. In this research, effects of different reinforcement strategies and varying tool offset positions on dispersion of reinforcement particles in the base matrix are investigated. The experiments were performed in two phases using AA6063 as base metal at constant process parameters of 1120 rpm rotational speed, 40 mm/min traverse speed and 2.5° tilt angle. In the first phase, effect of six different reinforcement strategies on the reinforcement particles distribution and defect formation was studied. It was found that groove method with tool offset in retreating side (RS) exhibited better homogeneity in reinforcement distribution out of the six reinforcement strategies considered. In the second phase, effect of variation of tool offset in RS was investigated. Results from second phase of experimentation reflected that the best dispersion of reinforcement powder with larger stir zone area was found with 1.5 mm tool offset which is numerically half of the tool pin radius. The results were supported by macro and microstructural images obtained from the optical microscope and scanning electron microscope.

A Review of Recent Progress in Solid State Fabrication of Composites and Functionally Graded Systems Via Friction Stir Processing

ABSTRACT Friction stir processing (FSP) is a rapidly emerging newer solid-state technique for composite fabrication. It involves surface modification which in turn enables successful adaptation of surface properties through plastic deformations in solid state. During initial years of FSP inception, it was primarily employed in development of metal matrix composites of light metal alloys like aluminum. However, recently, it has gained an alluring role in fabrication of composites of various nonferrous and ferrous metal alloys as well as of polymers. In addition to composite fabrication, FSP has evolved as a revolutionary technique in developing functionally graded systems/surfaces (FGS) of metal matrix. This article covers all aspects of FSP in which reinforcement particles are embedded in the base matrix to develop composites and FGS. It presents a critical review on domains of recent developments, effects of different types of reinforcement particles and properties enhancement of composites, and FGS fabrication. In addition to this, various issues, challenges, and future work that demand attention are systematically addressed.

Investigating Effects of Groove Dimensions on Microstructure and Mechanical Properties of AA6063/SiC Surface Composites Produced by Friction Stir Processing

Friction stir processing forms an innovative and promising technology for surface composite fabrication where their fabrication is accomplished in solid state. In the current research, AA6063/SiC surface composites were fabricated and effect of ratio of groove width (w) to tool pin diameter (d) on dispersion of reinforcement particles and mechanical properties were investigated. Five varying groove widths were chosen at constant levels of tool dimensions and process parameters to observe the exclusive effect of variation of groove width on area of developed SCs. Results reflected that groove width have strong impact on the area of surface composites and a ratio of w/d of 0.5 was found optimum for developing high volume percentage of 40% of SiC reinforced surface composites. The results were supported by macro and microstructural images.

An Integrated RSM-GA Based Approach for Multi Response Optimization of FDM Process Parameters for Pyramidal ABS Primitives

Abstract In this research work, a statistical model is developed for predicting the optimal process parameters of Fused Deposition Modelling (FDM) process for layout optimization. Multi response optimization of process parameters was achieved using Response Surface Methodology technique integrated with Genetic Algorithm. Response Surface Methodology (RSM) was utilized to design and conduct experiments. 86 experiments were conducted according to central composite design considering six process parameters namely raster width, raster angle, contour width, air gap, slice height and orientation to achieve four responses namely build time, model material volume, support structure volume and production cost. RSM-genetic algorithms (GA) integrated optimization is introduced in which GA is constructed including the development of coding strategy, evaluation operator and the fitness function. The constructed GA can meet the requirement of optimization work. The fitness function is defined as the sum of compulsive constraints or responses. All the constraints/responses have assigned same weightage. A Matlab genetic algorithm solver is utilized to predict best fitness values along with the optimal individual parameters in the present work.

Design and Processing of Functionally Graded Material: Review and Current Status of Research

Functionally graded materials (FGMs) are superiorly engineered as well as natural materials with customized properties. These materials offer a variety of advantages over conventional materials in specific engineering applications. High strength, improved ductility, superior mechanical properties and enhanced surface properties are some advantages of FGMs when compared to homogeneous materials of the same type. Engineered FGMs have intrigued numerous researchers in recent years. These materials were conceived as thermal obstruction materials for various critical applications. These are increasingly being employed for numerous conventional as well as advanced applications. Many methods are utilized in developing FGMs possessing specific advantages and disadvantages. This article reviews current trends and developments of functionally graded materials (FGMs). Techniques to attain gradation especially structural and functional are emphasized in the current work. A few real life illustrations are discussed to present a glimpse of different FGM fabrication strategies to the readers.

Integration of Fuzzy Logic with Response Surface Methodology for Predicting the Effect of Process Parameters on Build Time and Model Material Volume in FDM Process

Fused Deposition Modelling (FDM) is a promising additive manufacturing (AM) technique used for various prototyping requirements where relatively cheap yet robust models are required. To improve FDM process effectiveness, appropriate process parameters selection is required for high productivity and cost effectiveness. Build time (BT) and volume of Model material (MMV) required are important responses to measure cost effectiveness. In this work, response surface methodology (RSM) and fuzzy logic (FL) have been applied to reduce the build time and model material volume for experimentation. The process parameters namely contour width, air gap; raster angle and spatial orientation are considered. Also, build time and model material volume has been taken as responses for this study. Thirty experiments were conducted on AcrylobutadieneStyrene (ABS) P400 for conical primitives using full factorial central composite RSM design. The optimum process parameter conditions were obtained from FL. The results obtained provide useful information of the method to control responses and ensure minimal build time and model material volume for prototyping requirements. The assessment outcome provided a scientific reference to obtain minimal values of build time and model material volume utilized, and it was found out that these correspond to a contour width of 0.654 mm, air gap of 0.0254 mm, raster angle of 0° and orientation (rotation about x-axis keeping z height minimum) of 30°.

Estimation of the Effect of Process Parameters on Build Time and Model Material Volume for FDM Process Optimization by Response Surface Methodology and Grey Relational Analysis

In this study, a hybrid optimization approach is proposed for build time and model material volume in Fused Deposition Modeling (FDM) process on a FDM Maxum Modeler. A combination of response surface methodology (RSM) and grey relational analysis (GRA) is proposed and applied to optimize process parameters of FDM process. The significant input parameters such as contour width, air gap, raster angle, and spatial orientation are considered, and build time and model material have been taken as responses for this study. Thirty experiments were conducted on acrylonitrile butadiene styrene (ABS) P400 for conical primitives using full factorial central composite design. The optimum process parameter conditions were obtained from grey relational grade. The results obtained provide useful information of the method to control responses and ensure minimal build time and model material volume for prototyping requirements. The assessment outcome provided a scientific reference to obtain minimal values of build time and model material volume utilized, and it was found out that these correspond to a contour width of 0.654 mm, air gap of 0.0254 mm, raster angle of 0°, and orientation of 0°.