Optimization of Drilling Process Parameters on Die Steel (H13) using Carbide Coated Drill by Design of Experiment Concept

This experimental work presents the optimization of process parameter of surface roughness with using coated carbide drill on H13 steel. Taguchi design of experiments was implemented for executing the process parameter of Drilling process on H13 steel plates. The drilling parameters including 2 Factors such as spindle speed (rpm) and feed rate (mm/min) are optimized using response performance characteristic of surface roughness of H13 die steel plates.H13 steel play an important role in many applications such as Shaft, axle, gears and fasteners due to their strength to weight ratio. The process parameters of spindle speed and feed rate are influenced by machining accuracy during drilling process. The main objectives of experimental works have been identified by lower roughness during drilling process of H13 steel plates. Orthogonal array (L16) of Taguchi Design of experiments and Analysis of Variance (ANOVA) are utilized to analyze the effect of drilling parameters on Quality of drilled holes. The result of experiments indicate is a dominating parameter of surface roughness of H 13 steel plates in Drilling process

Time-Varying Gaussian Process Bandit Optimization

We consider the sequential Bayesian optimization problem with bandit feedback, adopting a formulation that allows for the reward function to vary with time. We model the reward function using a Gaussian process whose evolution obeys a simple Markov model. We introduce two natural extensions of the classical Gaussian process upper confidence bound (GP-UCB) algorithm. The first, R-GP-UCB, resets GP-UCB at regular intervals. The second, TV-GP-UCB, instead forgets about old data in a smooth fashion. Our main contribution comprises of novel regret bounds for these algorithms, providing an explicit characterization of the trade-off between the time horizon and the rate at which the function varies. We illustrate the performance of the algorithms on both synthetic and real data, and we find the gradual forgetting of TV-GP-UCB to perform favorably compared to the sharp resetting of R-GP-UCB. Moreover, both algorithms significantly outperform classical GP-UCB, since it treats stale and fresh data equally.Comment: To appear in AISTATS 201

Optimization of EDM process parameters for Al-SiC reinforced metal matrix composite

Volume 8 Issue 2 (February 201

Bidirectional optimization of the melting spinning process

This is the author's accepted manuscript (under the provisional title "Bi-directional optimization of the melting spinning process with an immune-enhanced neural network"). The final published article is available from the link below. Copyright 2014 @ IEEE.A bidirectional optimizing approach for the melting spinning process based on an immune-enhanced neural network is proposed. The proposed bidirectional model can not only reveal the internal nonlinear relationship between the process configuration and the quality indices of the fibers as final product, but also provide a tool for engineers to develop new fiber products with expected quality specifications. A neural network is taken as the basis for the bidirectional model, and an immune component is introduced to enlarge the searching scope of the solution field so that the neural network has a larger possibility to find the appropriate and reasonable solution, and the error of prediction can therefore be eliminated. The proposed intelligent model can also help to determine what kind of process configuration should be made in order to produce satisfactory fiber products. To make the proposed model practical to the manufacturing, a software platform is developed. Simulation results show that the proposed model can eliminate the approximation error raised by the neural network-based optimizing model, which is due to the extension of focusing scope by the artificial immune mechanism. Meanwhile, the proposed model with the corresponding software can conduct optimization in two directions, namely, the process optimization and category development, and the corresponding results outperform those with an ordinary neural network-based intelligent model. It is also proved that the proposed model has the potential to act as a valuable tool from which the engineers and decision makers of the spinning process could benefit.National Nature Science Foundation of China, Ministry of Education of China, the Shanghai Committee of Science and Technology), and the Fundamental Research Funds for the Central Universities

Optimization of Process Parameters in WEDM by using Taguchi Method

This research represents the parametric optimization of Wire EDM on machining die steel DC53. The objective of the present work was to investigate the effects of the various Wire EDM process parameters using Taguchi on the machining quality and to obtain the optimal sets of process parameters so that the quality of machined parts can be optimized. The machining parameters selected for present research were Pulse on time, pulse off time and wire feed. A series of nine experiments were conducted using Wire EDM. The ANOVA was employed to analyze the influence of these parameters on Material removal rate during machining process. The results showed that the input parameters setting of pulse on time at 120µs, pulse off time at 60µs and wire feed at 6mm/min have given the best results for optimization of Material removal rate

Optimization Of Process Parameters On Tensile Shear Load Of Friction Stir Spot Welded Aluminum Alloy (Aa5052-h112)

Optimization of the process was still the issue in manufacturing. Investigation on the process parameters that effects to the property of welded structure were necessary. In this study, the AA5052-H32 sheets of 2 mm thick were welded using friction stir spot welding (FSSW) and tested via tensile shear load test to investigate the influence of spindle speed, tool depth, and dwell time to the tensile shear load of the joints. The result shows that in every set of parameter combination, exhibit interesting influence to the tensile shear load. The effect of spindle speed of 1000 rpm shown the good property in average 18.33 KN especially at tool depth of 3.5 mm. Furthermore, the effect of tool depth brought significant effect to the tensile shear load especially at 3.5 mm for each set of spindle speed and dwell time. The set of dwell time to parameter combination had no significant effect to the tensile shear load. The good tensile shear load could be achieved in the range of 17.7-19.3 KN at 3.5 mm of plunge depth and 1000 rpm of spindle speed, where the best one was 19.3 KN at 7s of dwell time

Thermal food processing computation software

The objective of this research consisted of developing the two following thermal food processing software: “F-CALC” is software developed to carry out thermal process calculations based on the well-known Ball's formula method, and “OPT-PROx” is software for thermal food processing optimization based on variable retort temperature processing and global optimization technique. Time-temperature data loaded from Excel-file is used by “F-CALC” software to evaluate the heat penetration parameters jh and fh, as well as to compute process lethality for given process time or vice versa. The possibility of computing the process time and lethality for broken heating curves is included. The diversity of thermal food processing optimization problems with different objectives and required constraints are solvable by “OPT-PROx” software. The adaptive random search algorithm coupled with penalty functions approach, and the finite difference method with cubic spline approximation are utilized by “OPT-PROx” for simulation and optimization thermal food processes. The possibility of estimating the thermal diffusivity coefficient based on the mean squared error function minimization is included. The “OPT-PROx” software was successfully tested on the real thermal food processing problems, namely in the case of total process time minimization with a constraint for average and surface retentions the “OPT-PROx” demonstrates significant advantage over the traditional constant temperature processes in terms of process time and final product quality. The developed user friendly dialogue and used numerical procedures make the “F-CALC” and “OPT-PROx” software extremely useful for food scientists (research and education) and engineers (real thermal food process evaluation and optimization)