Fused deposition modelling (FDM) is a fast growing rapid prototyping (RP) technology due to its ability to build functional parts having complex geometrical shapes in reasonable build time. The dimensional accuracy, surface roughness, mechanical strength and above all functionality of built parts are dependent on many process variables and their settings. In this study, five important process parameters such as layer thickness, orientation, raster angle, raster width and air gap have been considered to study their effects on three responses viz., tensile, flexural and impact strength of test specimen. Experiments have been conducted using central composite design (CCD) and empirical models relating each response and process parameters have been developed. The models are validated using analysis of variance (ANOVA). Finally, bacterial foraging technique is used to suggest theoretical combination of parameter settings to achieve good strength simultaneously for all responses.

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Powder mixed electro-discharge machining (EDM) is being widely used in modern metal working industry for producing complex cavities in dies and moulds which are otherwise difficult to create by conventional machining route. It has been experimentally demonstrated that the presence of suspended particle in dielectric fluid significantly increases the surface finish and machining efficiency of EDM process. Concentration of powder (silicon) in the dielectric fluid, pulse on time, duty cycle, and peak current are taken as independent variables on which the machining performance was analysed in terms of material removal rate (MRR) and surface roughness (SR). Experiments have been conducted on an EZNC fuzzy logic Die Sinking EDM machine manufactured by Electronica Machine Tools Ltd. India. A copper electrode having diameter of 25 mm is used to cut EN 31 steel for one hour in each trial. Response surface methodology (RSM) is adopted to study the effect of independent variables on responses and develop predictive models. It is desired to obtain optimal parameter setting that aims at decreasing surface roughness along with larger material removal rate. Since the responses are conflicting in nature, it is difficult to obtain a single combination of cutting parameters satisfying both the objectives in any one solution. Therefore, it is essential to explore the optimization landscape to generate the set of dominant solutions. Non-sorted genetic algorithm (NSGA) has been adopted to optimize the responses such that a set of mutually dominant solutions are found over a wide range of machining parameters.

Machining of metal-matrix composites (MMCs) is difficult owing to their superior characteristics compared with the their parent materials. A specific application of modern laser technology is the drilling of cooling holes in aircraft engine 'hot-end components' such as combustion chambers, nozzle guide vanes, and turbine blades, which are made up of MMCs. Laser-drilled holes in aero-engine components must comply with strict quality standards that determine them suitable for in-service use. The current paper presents an effective approach for the optimization of neodymium-yttrium aluminium garnet (Nd:YAG) laser drilling of aluminium matrix/silicon carbide particulate (Al/SiC p ) MMCs in regard to multiple characteristics, i.e. taper, spatter, and heat-affected zone (HAZ), based on response surface methodology and grey relational grades. Twenty runs based on the response surface methodology are performed to determine factorial interactions and decide the best factor level settings. In addition to response surface methodology, grey relational grades and desirability functions are used for multiple response optimizations. Laser drilling parameters such as pulse width and number of pulses, and MMC parameters like concentration of SiC p , are optimized with consideration to taper, spatter, and HAZ. By analysing the grey relational grade, optimal parametric settings for various responses are determined.

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