Sanat Agrawal

Selection of selective laser sintering materials for different applications

Purpose – The purpose of this paper is to propose and evaluate the selection of materials for the selective laser sintering (SLS) process, which is used for low-volume production in the engineering (e.g. light weight machines, architectural modelling, high performance application, manufacturing of fuel cell, etc.), medical and many others (e.g. art and hobbies, etc.) with a keen focus on meeting customer requirements. Design/methodology/approach – The work starts with understanding the optimal process parameters, an appropriate consolidation mechanism to control microstructure, and selection of appropriate materials satisfying the property requirement for specific application area that leads to optimization of materials. Findings – Fabricating the parts using optimal process parameters, appropriate consolidation mechanism and selecting the appropriate material considering the property requirement of applications can improve part characteristics, increase acceptability, sustainability, life cycle and relia...

Physical modeling of catchment area by rapid prototyping using GIS data

Purpose – The purpose of the present work is to develop a methodology for making physical models of catchment areas and terrains by rapid prototyping (RP) using geographic information systems (GIS) data. It is also intended to reduce data loss by minimising intermediate data translations.Design/methodology/approach – The GIS data of a catchment area or a terrain were directly translated to an stereo lithography (STL) file. The STL surface was then manipulated in Magics‐RP to obtain a solid STL part, which can then be downloaded to a RP machine to obtain a physical model or representation of a terrain or catchtment area.Findings – Intricate geometries of landforms were created with ease and great accuracy in RP machines. Terrain models were created in less time and lower cost than with conventional methods.Research limitations/implications – DEM ASCII XYZ (digital elevation model) data were used to input the required GIS data of specific terrains. Software can be developed for translation and manipulation ...

Analysis of mechanical error in a fused deposition process using a stochastic approach

A stochastic model has been developed for studying the mechanical error in different rapid prototyping (RP) processes. Tolerances and clearances, which cause mechanical error, have been assumed to be random variables. The coordinates of a point on the work surface traced by the laser beam or the tip of the extruder head is expressed as a function of the random variables involved in the process. Using a unified approach for the RP processes, the mechanical error in the fused deposition process is analysed. In a numerical example, the mechanical error has been found for a grid of points traced by the nozzle tip. The three-sigma bands of the error in tracing example curves are plotted. This is the band in which the nozzle tips of 99.73% of machines, produced on a mass scale, lie for the given tolerances and clearances. Stringent values of tolerances and clearances reduce the error at the nozzle tip, but the cost of manufacturing and assembling the machines may become prohibitive.

Artificial intelligence based modeling and optimization of heat affected zone in Nd:YAG laser cutting of duralumin sheet

Duralumin is an alloy of aluminium which has some unique properties such as high strength to weight ratio, high resistance to corrosion, light in weight, and more demanding alloy in various sectors such as space craft, marine, chemical industries, construction and automobile. These applications require very precise and complex shapes which may not be obtained with conventional machining. Pulsed Nd:YAG laser cutting may be used to fulfill these objectives by using optimum setting of process parameters. The present research paper has experimentally investigated the modeling and optimization of heat affected zone in the pulsed Nd:YAG laser cutting of Duralumin sheet with the aim to minimize heat affected zone. The quality is improved by the proper control of different process parameters such as gas pressure, pulse width, pulse frequency and scanning speed. Artificial intelligence (AI) algorithms have been used to solve the many engineering problems successfully through development of Genetic Algorithm (GA), Fuzzy Logic (FL) and Artificial Neural Network (ANN) systems. The optimization of heat affected zone has been carried out by using Hybrid Approach of Multiple Regression Analysis (MRA) and GA. In this methodology, the second order regression model has been developed by using MRA with the help of experimental data obtained by L27 orthogonal array (OA). Further this equation has been used as objective function in GA based optimization. The significant factors have been found with further discussion of their effect on the heat affected zone.

Conversion of a GIS surface data directly to a 3D STL part for terrain modeling

Purpose – This paper aims to convert surface data directly to a three-dimensional (3D) stereolithography (STL) part. The Geographic Information Systems (GIS) data available for a terrain are the data of its surface. It doesn’t have information for a solid model. The data need to be converted into a three-dimensional (3D) solid model for making physical models by additive manufacturing (AM). Design/methodology/approach – A methodology has been developed to make the wall and base of the part and tessellates the part with triangles. A program has been written which gives output of the part in STL file format. The elevation data are interpolated and any singularity present is removed. Extensive search techniques are used. Findings – AM technologies are increasingly being used for terrain modeling. However, there is not enough work done to convert the surface data into 3D solid model. The present work aids in this area. Practical implications – The methodology removes data loss associated with intermediate fil...

Direct generation of STL files from USGS DEM data for additive manufacturing of terrain models

ABSTRACT Geographical information system (GIS) data in digital elevation model (DEM) format contains surface data of terrain on the Earth. This surface data needs to be converted into a 3D faceted file before uploading to an additive manufacturing (AM) machine. Commercially available software packages perform this task indirectly by translating and modifying data through different file formats. This paper discusses a methodology to convert the United States Geological Survey (USGS) 7.5-minute and 1-degree DEM file formats directly to 3D stereolithography (STL) ASCII format. A software program in C is developed to create a base and walls around the surface data to make a 3D STL part of the terrain. The STL file was uploaded to an AM machine (EOSP395) to fabricate a physical scale model of the terrain. This work not only removes intermediate steps and the associated data loss but can generate an STL part in relatively less time.

Optimization of Multiple Quality Characteristics in Laser Cutting of Difficult-to-Laser-Cut Material

This paper presents experimental study of laser cutting of Aluminium alloy sheet with the aim to optimize multiple quality characteristics such as cut edge surface roughness and kerf deviation, simultaneously. The Taguchi method combined with Grey relational analysis has been used for parameter optimization. The Principal component analysis and entropy measurement method have been used for eliminating co-linearity and deciding the weighting factors, respectively. The results indicate considerable improvements in multiple quality characteristics.

Parameter optimisation in laser cutting of aluminium alloy sheet

Being a thermal energy-based advanced cutting process, the capability of laser beam cutting depends mainly on optical and thermal properties of materials to be cut rather than mechanical properties. Highly reflective and thermally conductive sheetmetals are known as difficult-to-laser-cut materials. This paper presents an experimental approach to investigate the optimum laser cutting parameters, which minimise the surface roughness during pulsed laser cutting of difficult-to-laser-cut aluminium alloy sheet. Robust parameter design has been used for deciding the optimal parameter levels for straight cut profiles. An empirical model for surface roughness has also been developed. On the basis of optimisation results, it has been found that the optimal parameter level suggested give minimum surface roughness in present operating conditions. The results have also been verified by running some confirmation tests.

Analysis of geometrical error in the stereolithography process using a stochastic approach

The geometrical error in the stereolithography process is analysed using a stochastic approach. This approach is based on a unified methodology, developed by the authors, for studying the mechanical error in different rapid prototyping processes. The tolerances and clearances have been assumed to be random variables. The coordinates of a point on the resin surface, traced by the laser beam, are expressed as a function of random variables. In a numerical example, the geometrical error has been found for a grid of points traced by the laser beam. The three-sigma error bands are plotted when tracing example curves. This is the band in which the laser beams of 99.73% of machines, produced on a mass scale, lie on the work surface for the given tolerances and clearances. Stringent values of tolerances and clearances reduce the error at the tool tip, but the cost of manufacturing and assembling the machines may become prohibitive.