Advanced Materials Research Vols. 622-623

Abstract: Simultaneous optimization of conflicting type responses like material removal rate (MRR) and average surface roughness (Ra) in stochastic type electrical discharge machining (EDM) process is a matter of concern to the process engineers. In this paper, EDM is first modeled by response surface methodology (RSM). Current setting, pulse on time and pulse off time were taken as the input parameters while material removal rate and average surface roughness as the responses. Multi-objective simulated annealing (MOSA) is then applied on these models. Pareto optimal solution set is thus developed. It would assist a process engineer to take decision regarding the optimal setting of the process parameters for a specific need-based requirement.

Abstract: The paper presents a Neuro-fuzzy study of Flexible Manufacturing System subject to different design and control strategies. Adaptive Neuro-Fuzzy inference system (ANFIS) techniques have been used to evaluate the performance. The objective of our work is to evaluating the performances of system in terms of Make Span Time at different levels of Routing and Machine flexibilities.

Abstract: Though Cellular Manufacturing System (CMS) has been an active area of research for past few decades, but, still it has not received the requisite attention so far. Despite of a useful manufacturing strategy based on the group technology (GT), it is yet to be established on a larger scale. The CMS allows the grouping of the facilities on the basis of similarity in manufacturing processes and design considerations of the products to be manufactured. A lot of researchers have worked for various developments related to various issues of CMS, but for last decades, the modern optimization tools like genetic algorithm (GA), artificial neural networks (ANN) have changed the scenario and research work has been accelerated related to CMS. The present paper is an attempt to discuss the GA related research work by various researchers for CMS. Research work along with their impact of past researchers has been discussed and reported here.

Abstract: he major problem that deals with practical engineers is the mechanical design and creativeness. Mechanical design can be defined as the choice of materials and geometry, which satisfies, specified functional requirements of that design. A good design has to minimize the most significant adverse result and to maximize the most significant desirable result. An evolutionary algorithm offers efficient ways of creating and comparing a new design solution in order to complete an optimal design. In this paper a type of Genetic Algorithm, Real Coded Genetic Algorithm (RCGA) is used to optimize the design of helical gear pair and a combined objective function with maximizes the Power, Efficiency and minimizes the overall Weight, Centre distance. The performance of the proposed algorithms is validated through LINGO Software and the comparative results are analyzed.

Abstract: The objective of this research was to predict drying behavior of hot air drying using an empirical model (EM) and an artificial neural network model (ANN). Rubber sheet with initial moisture content ranging of 23-40% dry-basis was dried by temperature ranging of 40-70°C and air flow rate of 0.7 m/s. The desired final moisture content was set at 0.15% dry-basis. The results showed that drying rate of rubber sheet dried with hot air convection was faster than conventional natural aeration. The EM and ANN were simulated to describe the drying behavior of products. Furthermore, prediction results between EM and ANN were compared with the experimental data. In this research, it was obviously found that ANN can describe the drying behavior effectively. Additionally, it was also found that predicted results of Multilayer feed forward Levenberg-Maqurdt’s Back-propagation ANN were good agreement with the experimental results compared to those results of EM. It is the optimum architecture for prediction the evolution of moisture transfer for hot air drying.

Abstract: Energy saving in the electro-hydraulic system (EHS) that currently exists in most inverter used to adjust speed of the asynchronous motor (ASM) which drive a fixed displacement pump. The most controller commonly used control system such as PID and multi-input single-output (MISO) fuzzy controller. In this paper, a multi-input multi-output (MIMO) fuzzy controller is used to improve the energy saving performance of the EHS. The proposed controller is designed to control the pressure of the EHS to suit the actual needs of the load. The two inputs of controller received signals from the error and change in error of the load pressure of the EHS. For the two outputs of the controller, one output is used to control the inverter to adjust speed of an ASM which drive hydraulic pump, and one output that is used for control proportional pressure relief valve. The proposed controller was implemented to pressure control of compression machine. The experimental result showed that using a proposed controller can reduce power consumption was higher than compared with PID and MISO fuzzy controllers. Particularly, a MIMO fuzzy controller can reduce power consumption by up to 70.22% when compared to the conventional system.

Abstract: One of the most important rules in electric power system operation and control is Load Frequency Controller (LFC). Many problems are subject to LFC such as a generating unit is suddenly disconnected by the protection equipment and suddenly large load is connected or disconnected. The frequency gets deviated from nominal value when the real power balance is harmed due to disturbances.LFC is responsible for load balancing and restoring the natural frequency to its natural position. In this paper, PSO-fuzzy logic technique for Load Frequency Control system was proposed. PSO optimization method is used to tuning the input and output gains for the fuzzy controller. The proposed method has been tested on two symmetrical thermal areas of an interconnected electrical power system. The simulation results are carried out in term of effectiveness of the frequency time response on its damping and compared it to common PID controller. The results show the performances of the proposed controller have quite promising compared to PID controller.

Abstract: Finishing is crucial for maximizing the service life and overall in-service performance of gears. This paper presents the parametric optimization of Electrochemical Honing (ECH) of helical gears using Response Surface Methodology (RSM) and Genetic Algorithm (GA) to predict the surface quality of gear teeth profile. A three factors three levels Box Behnken Design (BBD) of Response Surface Methodology (RSM) has been designed to investigate and analyze the effects of input variables: voltage, rotating speed and electrolyte concentration on measures of process performances: percentage improvement in average and maximum surface roughness (PIR_a / PIR_tm) value. Typical ranges of input parameters were investigated and regression models were developed and used respectively as constraints and objective function for parametric optimization using GA. The results established the feasibility of using the process to improve the surface quality of gear teeth profile.

Abstract: Flow stress is a vital input data for machining simulations, which is experimentally measured from Split Hopkinson pressure bar (SHPB) tests. However such flow stress does not fit machining conditions of strain, strain rate and temperatures and lead to serious simulation errors. In this research work an integrated Taguchi – Finite element (FE) methodology is adopted to optimize the flow stress of AISI 1045 steel material for orthogonal machining. The flow stress computed from the optimization approach along with thermo physical material properties are input into the FE code. The FE cutting forces and chip thickness ratio (CTR) showed an improvement of 6-8% and 2-4% over conventional Johnson – Cook (JC) models. An optimum set of JC model parameters were found from the study. The JC parametric analysis indicated high cutting force sensitivity to yield strength and CTR sensitivity to yield strength, strain hardening and thermal softening.

Abstract: The purpose of this research is to raise the initial hydrolysis rate of polylactic acid (PLA) during the entire decomposing process, and then enhance the decomposition rate of PLA in natural environment. This research uses Taguchi method to do the parameter design of PLA hydrolysis. And then main effect analysis is applied to find out the significant factors and the optimal hydrolysis conditions for PLA. By the results of the confirmation experiments, the optimal conditions of the PLA hydrolysis rate got by these experiments are all located on the 95% confidence interval. This indicates that these experiments are with reproducibility and reliability.