Mechanical Engineering

One of the most challenging problems encountered by a fluidized-bed designer is assessing how changes in bed geometry and operating conditions affect the gasifier performance while scaling up to demonstration / commercial size. Typically, commercial gasifier designs are based on operating experience from small pilot plants. A cold model of a gasifier represents an inexpensive and convenient platform for conducting detailed hydrodynamic studies that would otherwise be impossible in the hostile high pressure and temperature environment of fluidized bed gasifier. A perspex three dimensional semicircular cold model test rig of ID 940mm which is hydro dynamically scale down model of a demonstration plant of 168 TPD pressurized fluidized bed gasification (PFBG) plant is established and hydro dynamic parameters viz Froude no., bubble rise velocity, and bubble diameter are presented which are used for further scale up. Besides performance of the gasification process involves knowledge of dynamics of two phases viz. solid (coal) and gaseous for scale-up of the gasifier. The measurement of mean residence time (MRT) and degree of axial mixing of solid phase is required for evaluation of PFBG .The paper presents the residence time distribution (RTD) studies carried out in a pilot scale hot model of PFBG of 200 mm dia and verified in a hydro dynamically similar cold model .The coal particles labeled by radio tracer Lanthanum -140 was used to measure RTD by collimated scintillating detectors located at ash extraction points at the bottom and gas outlet at the top of the gasifier .The measured RTD data of coal / ash particles were treated and normalized for arriving at the mean residence time (MRT). The treated RTD data were simulated using gamma distribution model and found that model predicated MRTs of cold and hot model tests were in good agreement. The paper suggest the parameters which assist to minimize the bypassing of the coal particles in the gasifier thus improving the carbon conversion efficiency and hence enable scale-up of the PFBG.

In this work the combined effect of injector orientation and nozzle hole geometry on performance, emissions and combustion were analyzed. Experiments were carried out on a single cylinder DI diesel engine for different orientation of injector located nearer to intake and exhaust valve in the combustion chamber. Effects of increase in injector opening pressure and injection timing advance were also analyzed. Experiments were carried out by plugging one of the two injector mounting holes. It was observed that for the injector located nearer to the exhaust valve, the combination of static injection timing 26o BTDC and injector opening pressure of 230 bar was found effective in reducing NOx levels with no significant drop in performance. Advancing the injection timing to 29° BTDC with 230 bar injector opening pressure resulted in marginal increase in performance and reduction in Smoke levels by 0.4 Bosch Smoke Unit Number (BSN). NOx emissions were slightly higher than that of baseline. Drop in brake thermal efficiency and increase in smoke emission levels observed for the injector located nearer to intake valve. Performance and smoke levels are inferior to that of conventional baseline reading even after the injection timing advance. Increase of smoke by 1.6 Bosch Smoke Number (BSN) is observed at full load for the injection timing of 29° BTDC. Significant increase in Hydrocarbon and Carbon Monoxide emissions were also observed. In general it is observed that the injector location nearer to the exhaust valve has a very good potential for reducing Oxides of Nitrogen emissions without affecting the performance.

Failures of equipments and process costs money. The reasons for failure could be either a bad design, improper working conditions, failure of system components as they approaches the wear out stage or a combination of these factors. There is no way of completely eliminating failures. However, a better understanding of the causes and mechanisms of equipment failure can allow failure control measures to be developed and implemented. Unreliability is the costly part of the economic equation and adopting measures to improve reliability and availability of the system will ultimately result in economic gain. The present work attempts to provide an estimate of the net effect of modification that is required for a system by using the control chart procedure. The method involves plotting control charts for each of the components using the time to fail. The central line of the control chart corresponds to the Mean Time Between Failure (MTBF) and the control limits are placed at a distance of from the mean line and is based on t- distribution. The components that require an improvement with regard to failure rate is identified by analysing the control charts. The desired change in the component availabilities as well as the system availability can be obtained and an estimate of the net effect of modification is also arrived. The model can provide a measure of the performance of the components as well as that of the system. The quantification of the improvements required, if any, can be obtained using the model. A 11 step algorithm is also developed based on the model. It is hoped that the developed model and algorithm will prove to be a powerful tool in process reliability analysis.

In the realistic situation, the total expenditure on the inventory may be limited to certain extent for a store house to maintain inventory of multiple items having independent ordering costs and holding costs. That is, less than a predetermined maximum permissible amount which may be vague to certain extent. In fact all the parameters in an inventory model are normally variable, uncertain and imprecise. These fuzzy variables like objective goal, costs and constraints are considered with linear and parabolic membership functions in fuzzy logic and the model is solved by fuzzy non-linear programming method using Lagrange multipliers and illustrated with numerical examples.

CNC Wire cut electrical discharge machining (WEDM) has become an important non-traditional machining process which is used to manufacture intricate shapes with great accuracy and good surface roughness. Due to large number of process parameters and response characteristics, lots of researchers have attempted to model and optimize the process. This paper reviews the research trends in relation between different process parameters and different performance measures including Surface roughness (Ra),material removal rate (MRR), Dimensional deviation (DD), kerf width (KW) and wire wear ratio (WWR). In addition, this paper highlights different optimization methods and discusses their role in CNC WEDM process.

This paper presents effective method and to determine optimal machining parameters in a turning operation on annealed Beryllium copper alloy to enhance the metal removal rate and minimize the surface roughness. The scope of this work is extended to Multi objective optimization. Response Surface Methodology is opted for preparing the design matrix. Artificial Neural Networks are used to train and validate the data prepared through experimentations. Multi Objective Genetic Algorithm is used for optimization of the performance measures of the process. A powerful model would be obtained with high accuracy to analyse the effect of each parameter on the output. The input parameters considered in this work are cutting speed, feed and depth of cut.

Carburizing, though a widely used industrial thermo chemical diffusion process, it is associated with the problem of shape and size distortion in the carburized parts.  These distortions are troublesome as they adversely affect the performance of the parts in terms of life, and trouble free operation. The main objective of our present work is to optimize the distortion level, optimum case depth, and surface hardness value of the carburized parts made of EN 353 material. Taguchi’s mixed level series Design of Experiment was selected for optimization.  The significance of our study was that all the three stages of carburizing (Pre carburizing, Carburizing and Post carburizing) were considered for optimization.  An orthogonal array and ANOVA were employed to investigate the influence of major parameters on the three response variables namely Distortion level, Surface hardness and Case depth and optimum conditions were arrived at by applying high penetration depth, high hardness and low distortion are better as the strategies.

Gas carburizing is the most widely used surface hardening process for number of automobile and other heavy duty machinery components made up of ferrous material. Itis a complex process and many literatures shows that the defects are due to shape distortion and volume change. This work attempts to minimize the extent of those defects in gas carburized automobile parts through Taguchi’s DOE approach. The optimum combination of parameters which will alleviate the distortion problems are obtained through the response graph method. The results are compared with that obtained from S/N ratio method. The studies are validated through experiments. In addition the present study shows that the introduction of optimal conditions and elimination of straightening operation saves time and money.

CNC Wire Electric Discharge Machining is the process of material removal using electrical discharge erosion action, with a wire electrode travelling longitudinally through the work piece. The work piece and wire electrode both are immersed in a dielectric fluid. The relative moving passage between the wire electrode and work piece is controlled by a CNC system that is pre-programmed. The Wire Electrical Discharge Machining performance mainly depends on various machining parameters like generator parameters, drawing parameters and user parameters. But the most prominent parameters are generator parameters as they are very important for sparking principles. Reference Voltage (V), Pulse on-time (Ton), Pulse off-time (Toff) fluid injection pressure mode (Inj), Wire tension (WB), Wire velocity (WS) are the crucial machining process parameters which has influence on the machining performance characteristics such as Material Removal Rate (MRR), Surface Roughness (Ra), Spark Gap (SG) and Dimensional Deviation (DD) while processing / slicing of ingot. Variation in machining performances causes both functional, profit and loss for any manufacturing organisation. Hence, an attempt has been made to study and optimize these machining parameters for minimizing the variations in multiple machining performances and process model (empirical relationship/regression model) between the process parameters (V, Ton, Toff, Inj, WB, WS) and the performance characteristics (MRR, Ra, SG and DD) has been developed. These process model can predict the level of performance that the machine would render for a given set of process parameters, thereby providing prior knowledge of desired machining performance before actually producing the part. The process model is able to show the dependency of machining performance on process parameters, which will be useful for both machine designers and the machine users.

This paper describes the study of coefficient of thermal expansion (CTE) of as-cast and heat treated aluminium 7075/ SiC composites. These composites were subjected to different aging durations. The stir casting technique is used to prepare the castings. Castings were machined in accordance with ASTM standards followed by heat treatment process. All the castings were aged to different periods of 1hr, 3hr, 5hr at an aging temperature of 175 oC. Coefficient of thermal expansion tests were performed in both as-cast and heat treated conditions. In each case the coefficient of thermal expansion values were found to increase with increase in aging durations. Solution heat treatment at 530 oC followed by artificial aging at 175 oC found to increase in dimension change of every specimen tested. The coefficient of thermal expansion curves exhibited some residual strains, which were decreased with the increase in aging durations.