Multiple Performance Characteristics Index Research Articles

Analysis and multi-objective optimization design of sinusoidal DSEM with two different excitation modes based on Gray-Fuzzy-Taguchi method

The nonlinearity of sinusoidal doubly salient electro-magnetic machine (SDSEM) leads to the fuzzy optimization range of its design parameters. And there is a conflict problem in multiple optimization objectives. Therefore, the multi-objective optimization of SDSEM with two different excitation modes is carried out based on the Gray-Fuzzy-Taguchi method. Firstly, the proposed sinusoidal method of square wave back electromotive force (EMF) phase modulation is introduced. And the key parameters to improve the symmetry and sinusoidal degree of the back EMF waveform are pointed out. Then, the sensitivity of key parameters is analyzed and the signal-to-noise (S/N) ratio is calculated by Taguchi orthogonal test. Secondly, the S/N ratio is linearly normalized by grey correlation analysis. Then, fuzzy reasoning is used to synthesize multiple performance indexes of the motor into a multiple performance characteristics index (MPCI) value, and the optimal scheme is obtained. Finally, the optimized SDSEM with concentrated magneto-motive forces (SDSEM-CF) and SDSEM with distributed magneto-motive forces (SDSEM-DF) are simulated and compared. The SDSEM-DF prototype is developed and verified by experiments. The results show that the no-load back EMF of the prototype has a good sinusoidal degree. Based on vector control, the sinusoidal drive of DSEM is realized without increasing the control complexity, which greatly reduces the torque ripple of the flux reluctance motor.

Optimization of Cold-Formed Steel Channel Columns

Sixteen cold-formed steel channel columns with different combinations of edge and web stiffeners under axial compression forces up to failure were numerically investigated using finite element (FE) analysis program, ANSYS. The behavior characteristics; the ultimate load, stiffness, ductility and energy absorption have been selected and separately analyzed in relation to column parameters. To determine the single-performance optimization of each characteristic, Taguchi method was applied. The multi-performance optimization was also investigated using Taguchi method coupled with grey relational analysis to achieve the favorable column characteristics and to investigate the multiple-performance characteristics index of each column. The results indicated that for multi-response and a single response, the predicted results are confirmed and the errors in the predicted values using the Taguchi method with respect to the numerical values using ANSYS are acceptable and also they indicated that broken straight line web stiffener factor (WS3) was the highest contributing parameters for variation of the ultimate load of CFS columns.

Multi-Objective Optimal Cloud Model Design of Vehicle-to-Grid Connected Systems Based on the Multiple Performance Characteristic Index Method

In this paper, a statistical cloud model was proposed for optimal design of the proportional integral derivative (PID) controllers used in current control of vehicle-to-grid connected inverter systems with PID parameters. By collecting the effective control factors and noise factors from a cloud data base, the cloud model can minimize both the reactive power and the total harmonic distortion for the single-phase full-bridge vehicle-to-grid connected system. The multi-objective optimal solution is obtained by using statistical fuzzy-based response surface methodology with multiple performance characteristics index. The testing results showed the validity of the proposed cloud model. It is verified that the statistical cloud model can increase the performance of the single-phase full-bridge vehicle-to-grid connected system in practical vehicle-to-grid applications in the Internet of Things.

Analysis of the optimisation of parameters for the laser machining of timber

Fuzzy-based Taguchi methods were used to optimise the parameters for the CO2 laser machining of timber. An orthogonal array, the signal-to-noise (S/N) ratio, and the analysis of variance (ANOVA) are employed with reference to process factors. Combining the Taguchi method and fuzzy logic, using the multiple performance characteristics index (MPCI), allowed determining the optimal combination of factors for cutting the timber. The confirmatory test was performed to verify the estimated response.

Multi-objective optimisation of dynamic scheduling in robotic flexible assembly cells via fuzzy-based Taguchi approach

This paper presents Taguchi method coupled with fuzzy logic for dealing with multi-objective optimisation problems for dynamic scheduling in robotic flexible assembly cells (RFACs). This is the first study to address these particular problems. In this study, Taguchi optimisation method has been applied to reduce the number of experiments required for scheduling RFACs. The experiments are implemented with four different scheduling factors, namely sequencing rule, dispatching rule, cell utilisation and due date tightness. These factors are difficult to optimise considering the objectives of multiple functions instead of a single objective. Therefore, a multiple performance characteristics index (MPCI) based fuzzy logic approach has been developed to derive the optimal solution. The predicted results of MPCIs have been verified via a confirmation test. Results of the confirmation test show significant improvement in MPCI using the optimal levels of the scheduling factors.

Multi-objective optimization design using amended particle swarm optimization and Taguchi method for a six-phase copper rotor induction motor

ABSTRACTA multi-objective optimization design technique for a six-phase copper rotor induction motor is proposed. The amended particle swarm optimization (PSO) and Taguchi methods combined with finite element analysis are used in this design technique. The objectives in the first-stage optimization are the minimization of manufacturing cost and starting current. In the second-stage optimization, the objectives are the maximization of efficiency, power factor and output torque. The Taguchi method can optimize the machine parameters of performance characteristics in electrical discharge machining. The experimental results are further transformed into the signal-to-noise ratios and amended PSO coefficients based on amended PSO analysis with regard to multiple performance characteristics index values. The results of the optimizations showed significant reduction in terms of the use of magnets as well as improvement in the machine performance. Finally, the experimental results confirm the validity of the proposed optimization design approach.

Optimal Parameter Design for IC Wire Bonding Process by Using Fuzzy Logic and Taguchi Method

Fuzzy logic Taguchi method (FLTM) is used to optimize parameters for wire bonding process. The proposed FLTM integrates orthogonal arrays, signal-to-noise ratios, response tables, analysis of variance (ANOVA), fuzzy logic, and multiple performance characteristics index. The main process parameters for wire bonding are ultrasonication time, ultrasonication power, bond force, bond force time, and search force. The output responses include ball shear and ball size. The orthogonal arrays, signal-to-noise ratios, and response tables reduce the number of experiments needed to find the best factor-level combinations. The significant control factors are determined by ANOVA. In engineering practice, ball size increases as ball shear increases, but an excessively large ball size causes a short circuit, whereas an excessively small ball size cannot provide enough ball shear. Due to the two contradictory output responses, the FLTM is used to find the best process parameters. The experimental results show that the process parameters obtained by the FLTM result in a smaller ball size and a larger ball shear compared with those obtained by statistical methods, artificial intelligence techniques, and previous designs.

Modelling and multi-response optimization of wire electric discharge machining parameters using response surface methodology and grey–fuzzy algorithm

Wire electric discharge machining is a non-conventional machining wherein the quality and cost of machining are influenced by the process parameters. This investigation focuses on finding the optimal level of process parameters, which is for better surface finish, material removal rate and lower wire consumption for machining stainless steel-316 using the grey–fuzzy algorithm. Grey relational technique is applied to find the grey coefficient of each performance, and fuzzy evaluates the multiple performance characteristics index according to the grey relational coefficient of each response. Response surface methodology and the analysis of variance were used for modelling and analysis of responses to predict and find the influence of machining parameters and their proportion of contribution on the individual and overall responses. The measured values from confirmation experiments were compared with the predicted values, which indicate that the proposed models can be effectively used to predict the responses in the wire electrical discharge machining of AISI stainless steel-316. It is found that servo gap set voltage is the most influential factor for this particular steel followed by pulse off time, pulse on time and wire feed rate.

A PSO-Based Fuzzy-Controlled Searching for the Optimal Charge Pattern of Li-Ion Batteries

This paper proposes a searching strategy based on particle swarm optimization, combined with a fuzzy-deduced fitness evaluator (FDFE), to find the optimal multistage charging pattern that delivers the most discharged capacity within the shortest charging time (CT). The objective function of the optimization problem is to maximize the cost effectiveness for the applied charging pattern based on the CT and normalized discharged capacity (NDC). Therefore, this paper proposes an FDFE to combine CT and NDC into a unified cost function to properly evaluate the multiple performance characteristics index in the charge problem. The experimental results show that the obtained pattern is capable of charging the batteries to over 88% capacity within 51 min. Compared with the conventional constant current–constant voltage method, the CT, the obtained life cycle, and the charging efficiency of the lithium-ion (Li-ion) battery for the devised approach are improved by approximately 56.8%, 21%, and 0.4%, respectively. The presented charging approach is suitable for the increasingly applications, in which the batteries are “sealed” inside the products to extend the life span.

Multiobjective Design of Turbo Injection Mode for Axial Flux Motor in Plastic Injection Molding Machine by Particle Swarm Optimization

This paper proposes a turbo injection mode (TIM) for an axial flux motor to apply onto injection molding machine. Since the injection molding machine requires different speed and force parameters setting when finishing a complete injection process. The interleaved winding structure in the motor provides two different injection levels to provide enough injection forces. Two wye-wye windings are designed to switch two control modes conveniently. Wye-wye configuration is used to switch two force levels for the motor. When only one set of wye-winding is energized, field weakening function is achieved. Both of the torque and speed increase under field weakening operation. To achieve two control objectives for torque and speed of the motor, fuzzy based multiple performance characteristics index (MPCI) with particle swarm optimization (PSO) is used to find out the multiobjective optimal design solution. Both of the torque and speed are expected to be maximal at the same time. Three control factors are selected as studied factors: winding diameter, winding type, and air-gap. Experimental results show that both of the torque and speed increase under the optimal condition. This will provide enough large torque and speed to perform the turbo injection mode in injection process for the injection molding machine.

Implementation of a Coreless Axial-Flux PM Generator for Vertical-Axial Wind Turbine

In this paper, a rigorous and efficient approach, using the fuzzy-Inference Taguchi method with the multiple performance characteristics index (MPCI), is employed for obtaining the rigorous design of a small-scale direct-drive coreless axial-flux permanent-magnet (AFPM) generator for a vertical-axis wind turbine (VAWT) with both larger induced voltage and higher efficiency. The proposed method first establishes the orthogonal array (OA) recommended by the Taguchi method, then multiple targets are coordinated by the fuzzy inference mechanism to obtain a better combination of geometric parameters for achieving multiple quality targets. The three-dimensional (3-D) electromagnetic finite element method (FEM) is used as the tool for analyzing the performance of the coreless AFPM generator. The results have shown the proposed method can obtain the suitable generators geometric parameters for enhancing the induced voltage of the generator while keeping efficiency as high as possible under the rated speed.

Fuzzy Multiple Performance Characteristics Index Based Optimization in TFTLCD Short Bar Attach Process

Fuzzy Multiple Performance Characteristics Index Based Optimization in TFTLCD Short Bar Attach Process

Multi-objective optimization of yield rate and tact time of ACF in the TFT-LCD short-bar attach process using the fuzzy dominant directed graph method

This paper proposes a fuzzy-DDG method to solve the multi-objective optimization problem in regard to the anisotropic conductive film (ACF) attach process for thin-film transistor liquid crystal display (TFT-LCD). As such, this paper has been motivated by a desire to decrease the usage of ACF materials in the ACF attach process. Herein, the experimental Taguchi method will be used to find the optimal solution for this problem. This paper will study the optimization problem of yield rate and tact time with respect to control factors of TFT-LCD. In using the Taguchi method, five test cases are discussed: the first involves the optimal yield rate problem; the second, the optimal tact time problem; and the third, solving multiple problems by simultaneously considering yield rate and tact time. Additionally, the conventional multiple performance characteristics index (MPCI) method is used, although it exhibits a less than optimal fuzzy inference structure, and fuzzification as well as defuzzification processes are required; in the fourth and the fifth cases, a new fuzzy DDG method is used to determine the multiple objective problems. Notably, the conventional fuzzy inference structure is not required in this algorithm and only graph-based matrix operations are required. Testing results show that the fourth and the fifth cases are more convenient in regard to arithmetical operations, compared to the third case. The fourth case illustrates the problem with the vertex order included only; only crisp potential values are derived. The fifth case illustrates the problem with the vertex S/N ratio values included and fuzzy potential values derived. Experimental results are provided to verify the validity of the proposed fuzzy DDG method.

Optimization of hot extrusion process for AZ61 magnesium alloy carriers

This study applies fuzzy-base Taguchi method to investigate the optimal process parameters of the multiple performance characteristics index (MPCI) for the hot extrusion process of AZ61 magnesium alloy products. Flattening strength, fracture strength and extrusion load are taken as the input data of MPCI. Since the optimal combination of process parameters for Taguchi method varies with individual quality characteristic, the optimal combination of parameters for different quality characteristics may be contradictory to each other. In order to consider the larger-the-better quality characteristic of flattening strength and T-slot fracture strength values as well as the smaller-the-better quality characteristic of extrusion load, the fuzzy-base Taguchi method is used to analyze and to obtain the optimal combination of process parameters for the MPCI. First of all, orthogonal array is applied to arrange the experimental combination of extrusion process. The signal-to-noise (S/N) ratios of the three quality characteristics of flattening strength, T-slot fracture strength and extrusion load for the products acquired from experiments are calculated. The S/N ratio serves as the input variable of fuzzy control unit, whereas MPCI serves as a single output variable. The acquired MPCI is employed to analyze the optimal process parameters. In this study, an optimal combination of process parameters of AZ61 carrier for MPCI is obtained, and the verification experiments are conducted to prove the accuracy. Moreover, mechanical properties of AZ31 and AZ61 magnesium alloy carriers are tested for further comparison.

Adhesive features of bonded interfaces subjected to temperature shock

Defects on interfaces can gradually degrade the interfacial adhesion of IC package layers. This can be attributed to an unmatched coefficient of thermal expansion in the materials subjected to the temperature change. This study employed a fuzzy controller to stabilize both delamination force and energy absorption in order to represent adhesion strength. The three controllable factors were: dwell time, solder mask thickness and shock temperature; and the two uncontrollable factors were: delamination force and energy absorption. Temperature shock was used to simulate environmental temperature destruction, and delamination force was employed to simulate a shear test. Dropped destruction (energy absorption) was reproduced in an impact test. An analysis of variance (ANOVA) was conducted to determine significant factors, the optimal quality, and the most damaging conditions. Finally, the delamination force and energy absorption were combined using fuzzy logic in order to analyze the multiple performance characteristics index (MPCI). The MPCI is the only index of specimen quality levels that can determine the effects of temperature on the interfacial adhesion strength of a substrate/solder mask under certain conditions.

Application of fuzzy-based Taguchi method to the optimization of extrusion of magnesium alloy bicycle carriers

By using fuzzy-base Taguchi method, this study investigates the optimal process parameters that maximize multiple performance characteristics index (MPCI) for hot extrusion of AZ31 and AZ61 magnesi...