Applied Mechanics and Materials Vol. 612

Abstract: Thermal mechanism cover the mechanics of Hit Sink, Airflow mechanics, and Ambient Temperature Mechanism to reduce junction temperature in design of Finite Duration Impulse Response (FIR) Filter. In this work, we are implementing FIR Filter on 28nm FPGA. After implementation of FIR Filter, we analyze the effect of in-built mechanism of Air Flow Controller and their produced Airflow on the junction temperature of FPGA. The mechanism of Ambient Temperature controller also play significant role in leakage power dissipation as well as junction temperature of FPGA. Finally, the mechanical structure of Hit Sink is considered for control of junction temperature of FPGA. There is 73.38% reduction in Leakage Power on 55 C ambient temperature when we increase airflow from 250 LFM to 500 LFM. Along with 500 LFM airflow, if we provide high profile hit sink then there is 78.31% reduction in leakage power. There is 37.68% reduction in junction temperature of FPGA when we increase airflow from 250LFM to 500LFM. Along with 500 LFM airflow, if we provide high profile hit sink then there is 41.76 % reduction in junction temperature on 45C ambient temperature. There is no effect of airflow on clock power. Whereas there is significant reduction in Logic Power, Signal Power, DSPs Power and IOs Power with change in Airflow.

Abstract: The power generated by solar photovoltaic system depends on insolation, temperature and shading situation etc. These days’ solar PV arrays are mainly building integrated. Therefore PV array are often under partial shadow. The feature of these shadows can be either easy-to-predict (like neighbour’s chimney, nearby tree or neighbouring buildings) or difficult-to-predict (passing clouds, birds litter).Thus output power obtained by PV arrays decreases in a considerable manner. In this paper, output powers, currents and voltages for SP & TCT topologies are calculated for different patterns of easy-to-predict partial shading conditions on a 4×4 PV field.

Abstract: Non-conventional process like Photochemical Machining (PCM) is found to show a promise for machining very thin metal components. In the present study, the effect of various selected parameters such as time of etching, temperature of etchant and concentration of etchant on material removal rate, undercut in PCM of phosphor bronze has been investigated by using multi-objective grey relational analysis and their optimal conditions are evaluated. Full factorial (L27) orthogonal array (DoE) has been used to perform the experiments. GRG value indicates most significant parameters affecting the PCM process. The above factors are selected on the basis of effect - cause analysis and literature survey. Mathematical models relating to the machining performance and machining parameters have been formulated. Optimal settings for each performance measure have also been obtained. The results obtained after conference test prove that improvement in the quality will take place is if the setting of parameters are done at optimum level predicted by multi-objective grey relational analysis. The ANN model is prepared to predict the result by training neural which can be compared with actual experiments to confirm the satisfactory performance during the experimentation.

Abstract: Flow stress during hot deformation depends mainly on the strain, strain rate and temperature, and shows a complex nonlinear relationship with them. In this work, experimental flow stress have been predicted for Ti-6Al-4V alloy using isothermal uniaxial tensile tests ranging from 323K to 673K at an interval of 50K and strain rates 10^-5, 10^-4, 10^-3 and 10^-2 s^-1. Based on the input variables strain, strain rate and temperature, a back propagation neural network model has been developed to predict the flow stress as output. The whole experimental data is randomly divided in two parts: 90% data as training data and 10% data as testing data. The artificial neural network enhanced with differential evolution algorithm is successfully trained based on the training data and employed to predict the flow stress values for the testing data, which were compared with the experimental values. Correlation coefficient for training and testing data is found to be 0.9997 and 0.9985 respectively. Based on the correlation coefficient, it indicates that predicted flow stress by using artificial neural network is in good agreement with experimental results.

Abstract: The main objective of this paper is to improve the productivity of a carburetor production processes using lean manufacturing technique. The current system of the carburetor production process has been mapped using electronic Value Stream Mapping (eVSM) tool which is a lean manufacturing tool and the wastages in the current system are identified. Then future state was drawn by using eVSM tool which has an enhanced process ratio by decreasing maximum possible waste in the production process. The current and future state of the carburetor production has been created as model and simulated using Arena software. The simulation shows a significant decrease in Non-Value added time and production lead time, thereby indicating increase in productivity and better work flow in production processes.

Abstract: This paper deals with the improving lay of finish and the superfinishing of the nozzles which is used in plasma cutting operation. This is basically alternative solution to present finish obtained by turning, drilling and reaming of the profiled bores and orifices. The advance micromachining process were developed, known as Abrasive Flow Machining (AFM) which is capable to altering the orifice (nozzle of plasma cutting machines) so that present process is to be improved without altering the geometry of the component. The effects of different process parameters such as number of cycles, concentration of abrasive, abrasive mesh size and media flow speed, surface finish are studied here. The design of the experiments 16(2⁴) provides two levels for each variable. These levels are taken into consideration for finding out the effect of variation of parameters on the surface roughness of the copper orifice. The objective of paper is to learn how each parameter is considered for Abrasive Flow Machining such as: abrasive concentration in media, number of cycles, abrasive mesh size and media flow speed affects the surface roughness of copper orifice also to find out the mathematical relationship between surface roughness value and process parameters. Analysis of Variance (ANOVA) for the experimental data has been carried out and optimizations of abrasive flow machining process parameters were done. Also Analytic Hierarchy Process (AHP) done here for selecting hierarchy process parameter .Capabilities of the machine ultimately improved with the new technology developed.

Abstract: In incremental sheet forming (ISF) the tool moves along the specified trajectory and deforms the sheet in to required shape. In the present paper incremental forming process is simulated using explicit finite element software LS-DYNA. The computational time for the simulation of ISF is very long due to long tool paths used in the process. To overcome this problem time scaling and mass scaling are used in the present paper. The effect of time scaling and mass scaling on forming forces, plastic strain, internal energy, kinetic energy, thickness distribution and computational time is studied. A continuously varying wall angle conical frustum is simulated for this study. Extra deep drawn steel, which is most commonly used in automotive applications, has been used as a blank material. Thickness distribution obtained with different mass and time scaling factors is compared with experimentally measured thickness distribution.

Abstract: Simulation can be used in industrial field allowing the systems behavior to be learnt and tested. This work involves simulation and analysis of the engine assembly line. An engine assembly line contains three subsystems namely engine assembly, hot test line and paint shop. A simulation model built up in modeling software-WITNESS by considered entire set of data. The model validated and several what-if scenarios generated. The different scenario has been analyzed. Finally the throughput, optimum number of pallet and bottleneck identified. This paper discusses the need and uses of discrete event simulation in the design for final engine assemblies.

Abstract: In recent years, there has been a tremendous increase in the use of adhesively bonded joints for the structural components as they offer various advantages such as low structural weight, low fabrication cost, and improved damage tolerance. One of the major concerns in their use is the crack produced at the interface of adhesive and adherend surface causing the failure of the joint. A study on the determination of crack growth can contribute momentously to avoid the joint failure. In this study the crack growth caused in adhesive due to displacement controlled loading has been analyzed by ABAQUS/Explicit software. Crack growth was modeled in the double cantilever beam (DCB) using traction separation law by element-based cohesive behavior. The analysis showed that: (1) The adhesive joint behaves linearly before the first cohesive element failure and after that the failure continues to increase even on decreasing the load untill it fails completely, (2) The noise during the failure of adhesive is caused due to the stress wave which is produced as a result of sudden loss in traction between the adhesive and the adherend.

Abstract: Many glass fiber reinforced plastic (GFRP) composite components made from primary melt processes require additional machining to meet the requirements of assembly and accurate dimensional tolerances. Importance of woven fabric based glass fibre reinforced composites is widely known in many industrial applications. However, very little is known about machinability of these composites. Cutting force is treated as one of the primary measures for determining the machinability of any material.This paper presents an investigation into the longitudinal turning of woven fabric and epoxy based GFRP composites, using polycrystalline diamond tool, so as to analyze the effect of cutting parameters and insert radius on the cutting force. The force was measured through longitudinal turning, according to the experimental plan, as developed on the basis of Taguchi methodology. The signal to noise ratio and analysis of variance were applied to the experimental data, in order to determine the effect of the process variables on tangential cutting force. Statistical results indicated that the cutting force is significantly influenced (at a 95% confidence level) by feed rate, followed by depth of cut, whereas, cutting speed and insert radius have a smaller influence. The cutting force also increases with the increase in feed rate and depth of cut.