Taguchi Parameter Design Method Research Articles

Optimizing the concrete materials by L9 orthogonal array

This manuscript presents the outcome of an experimental investigation conceded out to optimize the mix proportions of the concrete by the Taguchi method of parameter design. In order to reduce the number of mix combination in concrete, the Taguchi method is used. In this project the cement sand and aggregate are partially replaced by cement as fly ash, river sand as M-sand and the compression values are taken and the value is compared with the conventional concrete special concrete compression value is compared with the conventional concrete and S/N value is taken from the compression value and the comparison of the values are done. In order to attain good strength and to avoid cracks, sisal fiber is added in the concrete with a percentage of (1, 1.5, and 2).

A hybrid augmented ant colony optimization for the multi-trip capacitated arc routing problem under fuzzy demands for urban solid waste management.

Nowadays, urban solid waste management is one of the most crucial activities in municipalities and their affiliated organizations. It includes the processes of collection, transportation and disposal. These major operations require a large amount of resources and investments, which will always be subject to limitations. In this paper, a chance-constrained programming model based on fuzzy credibility theory is proposed for the multi-trip capacitated arc routing problem to cope with the uncertain nature of waste amount generated in urban areas with the aim of total cost minimization. To deal with the complexity of the problem and solve it efficiently, a hybrid augmented ant colony optimization algorithm is developed based on an improved max-min ant system with an innovative probability function and a simulated annealing algorithm. The performance of hybrid augmented ant colony optimization is enhanced by using the Taguchi parameter design method to adjust the parameters' values optimally. The overall efficiency of the algorithm is evaluated against other similar algorithms using well-known benchmarks. Finally, the applicability of the suggested methodology is tested on a real case study with a sensitivity analysis to evolve the managerial insights and decision aids.

Dynamic supplier selection through optimal ranking under two-echelon system

PurposeWith the increasing competition among the industries, they remain under pressure as how to select the best set of suppliers for the competitive edge. Often, it has been challenging to develop an effective set of suppliers due to varied and asymmetric mode of criteria. The purpose of this paper is to develop a responsive chain under original equipment manufacturer (OEM).Design/methodology/approachThis study proposes a responsive chain under a two-echelon system (TES) of OEM, which needs to collaborate with a set of suppliers at each echelon through an integrated methodology of AHP and TOPSIS. According to the OEM’s criteria, demands and suppliers’ capacity vary with time, therefore they are not static for a longer period. Hence, supplier selection (SS) problem possesses dynamicity in real practice. For this, MILP is used for finding optimal order quantities based on the optimal ranking at each echelon in the multi-period scenario. Subsequently, sensitivity analysis (SA) is conducted through Taguchi method of parameter design (TMPD) to achieve an optimal ranking in the TES.FindingsThis study suggests optimal criteria’s weight, percentage contribution, and flexibility for the suppliers and manufacturers involving through maximum demand strategy at each echelon of OEM. It also provides robust group of suppliers and manufacturers in the TES through optimal ranking and simultaneously in the order allocations. Furthermore, it restricts the number of suppliers and manufactures at each echelon through proposed methodology to obtain the solution in a very short running time.Originality/valueTo validate this model, a real data set for the case of chain conveyor company is used. This adopted methodology can suggest the organization that how the approach should be implemented.

Optimizing the Concrete Materials by Taguchi Optimization Method

This manuscript presents the outcome of an experimental investigation conceded out to optimize the mix proportions of the concrete by the Taguchi method of parameter design. The concrete mix design is done by the L9 orthogonal array that is 34. When a new material is used in the concrete all the mix variables are taken into account so that it may cost so much, it means more need for money, material, personnel and time. In order to reduce the number of mix combination in concrete, the Taguchi method is used. In this project the cement sand and aggregate are partially replaced by cement as fly ash, river sand as M-sand and the compression values are taken and the value is compared with the conventional concrete special concrete compression value is compared with the conventional concrete and S/N value is taken from the compression value and the comparison of the values are done. In order to attain good strength and to avoid cracks, sisal fiber is added in the concrete with a percentage of (1, 1.5, and 2).

Robust Design of a Low-Cost Permanent Magnet Motor with Soft Magnetic Composite Cores Considering the Manufacturing Process and Tolerances

This paper uses the Taguchi method to optimize the manufacturing process and robust design of a low-cost permanent magnet motor with soft magnetic composite (SMC) cores. For the manufacturing process, SMC cores are produced by using the molding technology without any wire cutting costs. To maximize the relative permeability and minimize the core loss, the Taguchi method is employed to identify the best control factor values for the heat treatment of SMC cores based on a series of experimental results. Due to the manufacturing tolerances, there are significant uncertainties in the core densities and motor dimensions, which will result in big performance variations for the SMC motors in the batch production. To obtain a robust design less sensitive to these tolerances, the conventional Taguchi parameter design method and a sequential Taguchi optimization method are presented to maximize the average torque and minimize the core loss of a low-cost PM motor. Through comparison, it is found that the proposed optimization method is efficient. It can provide an optimal design with better motor performance and manufacturing quality. The proposed method will benefit the industrial production of cost-effective PM-SMC motors with robust and compact designs.

An improved ant colony optimization for the multi-trip Capacitated Arc Routing Problem

The urban waste collection problem and its disposal activities are among the most important municipal services involving many operational issues. In this paper, a mixed-integer linear programming (MILP) model was developed for the multi-trip Capacitated Arc Routing Problem (CARP) in order to minimize total cost. In the proposed model, depots and disposal facilities were located in different places. In order to validate the proposed model, several small-sized instances were solved by the CPLEX solver of GAMS software. Then, a hybrid algorithm using the Taguchi parameter design method was developed based on an improved Max-Min Ant System (IMMAS) to solve well-known test problems and large-sized instances. Computational results show high efficiency for the proposed algorithm.

Experimental investigations of curling phenomenon in selective laser sintering process

Purpose This paper aims to investigate the curling behaviour of selective laser sintered polyamide/glass bead composites with changes in material compositions, part bed temperature, powder base thickness, laser power and layer cooling time. Design/methodology/approach The Taguchi parameter design method (design of experiments, DOE) and analysis of variance (ANOVA) technique were applied in the investigation to determine the optimal process parameter settings. Findings The results of statistical analysis and ANOVA provided evidence for the effectiveness of filler content and its surface treatment on reducing the amount of curling. Research limitations/implications Warping and curling phenomena is one of several aspects of this work that can be pursued further. The present investigation could be expanded to explore other fillers and interface adhesion using other modifiers. Experiments could be conducted with other complicated geometries, various sizes, different positions and locations to widen the knowledge base of geometric accuracy of selective laser sintering process. Practical implications This experimental work is beneficial for materials development and accuracy characterisation in rapid manufacturing techniques. The experimental techniques adopted are readily transferable to virtually any material system used in rapid manufacturing. Originality/value Although many materials have been developed, there is still a need for research into new materials. This work demonstrates that it is possible to improve the geometric accuracy of selective laser sintered components from glass bead- filled polyamide 12 and achieve near-zero curling by adding rigid multiphase-coated particle to the material system.

Optimisation of green sand casting process parameters for enhancing quality of mild steel castings

In this paper, an attempt has been made to obtain an optimal parameter setting of green sand casting process to enhance the quality of mild steel castings by reducing the percentage of casting defects. Taguchi method of parameter design is used to set the optimal process parameters. Minimisation of casting defects is set as quality target. Analysis of variance (ANOVA) is then performed on the signal-to-noise ratio to find the optimal parameter levels and to identify the statistical significance and contribution of each factor on the casting defects. Finally, a confirmation test is performed using the optimal parameter setting, which shows that the casting defects can be minimised, effectively, by using the method proposed in the study.

Multi-criteria optimization and predictive modeling of turning forces in high-speed machining of yttria based zirconia toughened alumina insert using desirability function approach

An attempt has been made to apply the Taguchi parameter design method and multi-response optimization using desirability analysis for optimizing the cutting conditions (cutting speed, feed rate and depth of cut) on machining forces while finish turning of AISI 4340 steel using developed yttria based zirconia toughened alumina inserts. These zirconia toughened alumina inserts were prepared through wet chemical co-precipitation route followed by powder metallurgy process. The L9 (4) orthogonal array of the Taguchi experiment is selected for three major parameters, and based on the mean response and signal-to-noise ratio of measured machining forces, the optimal cutting condition arrived for feed force is A1, B1 and C3 (cutting speed: 150 m/min, depth of cut: 0.5 mm and feed rate: 0.28 mm/rev) and for thrust and cutting forces is A3, B1 and C1 (cutting speed: 350 m/min, depth of cut: 0.5 mm and feed rate: 0.18 mm/rev) considering the smaller-the-better approach. Multi-response optimization using desirability function has been applied to minimize each response, that is, machining forces, simultaneously by setting a goal of highest cutting speed and feed rate criteria. From this study, it can be concluded that the optimum parameters can be set at cutting speed of 350 m/min, depth of cut of 0.5 mm and feed rate of 0.25 mm/rev for minimizing the forces with 78% desirability level.

Surface Roughness Prediction Model using Zirconia Toughened Alumina (ZTA) Turning Inserts: Taguchi Method and Regression Analysis

In the present study, an attempt has been made to apply the Taguchi parameter design method and regression analysis for optimizing the cutting conditions on surface finish while machining AISI 4340 steel with the help of the newly developed yttria based Zirconia Toughened Alumina (ZTA) inserts. These inserts are prepared through wet chemical co-precipitation route followed by powder metallurgy process. Experiments have been carried out based on an orthogonal array L9 with three parameters (cutting speed, depth of cut and feed rate) at three levels (low, medium and high). Based on the mean response and signal to noise ratio (SNR), the best optimal cutting condition has been arrived at A3B1C1 i.e. cutting speed is 420 m/min, depth of cut is 0.5 mm and feed rate is 0.12 m/min considering the condition smaller is the better approach. Analysis of Variance (ANOVA) is applied to find out the significance and percentage contribution of each parameter. The mathematical model of surface roughness has been developed using regression analysis as a function of the above mentioned independent variables. The predicted values from the developed model and experimental values are found to be very close to each other justifying the significance of the model. A confirmation run has been carried out with 95 % confidence level to verify the optimized result and the values obtained are within the prescribed limit.

Assessing the Success of Six Sigma: An Empirical Study

In response to the ever increasing demand of customer and prompt changing economic conditions, various industrial engineering and quality management strategies such as ISO 9000, total quality management (TQM), lean manufacturing, manufacturing recourse planning, modular design, reengineering, flexible manufacturing system (FMS), etc., are adopted by the corporations to compete in the current competitive market. However, from the last three decades a new paradigm, known as “Six Sigma”, has made its primeimpact in the area of manufacturing strategies to solve the problems related to the quality and productivity. In this paper, a case of Indian foundry unit has been presented to explore the effectiveness of six sigma methodology. The DMAIC (Define- Measure-Analyze-Improve-Control) approach of six sigma has been followed here to reduce percentage of defects in green sand casting process. In addition, Taguchi method of parameter design is used to set the optimal process parameters in the ‘Improve phase’. Analysis of variance (ANOVA) is then performed to find the optimal parameter levels and to identify the statistical significance and contribution of each factor on the casting defects. Finally, a confirmation test is performed using the optimal parameter setting, which shows that the casting defects can be minimized, effectively. The results show that after successful deployment of six sigma, the percentage of casting defects is reduced by 25.44%.

Optimization of degree of sphericity of primary phase during cooling slope casting of A356 Al alloy: Taguchi method and regression analysis

The present work presents the results of experimental investigation of semi-solid rheocasting of A356 Al alloy using a cooling slope. The experiments have been carried out following Taguchi method of parameter design (orthogonal array of L9 experiments). Four key process variables (slope angle, pouring temperature, wall temperature, and length of travel of the melt) at three different levels have been considered for the present experimentation. Regression analysis and analysis of variance (ANOVA) has also been performed to develop a mathematical model for degree of sphericity evolution of primary α-Al phase and to find the significance and percentage contribution of each process variable towards the final outcome of degree of sphericity, respectively. The best processing condition has been identified for optimum degree of sphericity (0.83) as A3, B3, C2, D1 i.e., slope angle of 60°, pouring temperature of 650°C, wall temperature 60°C, and 500mm length of travel of the melt, based on mean response and signal to noise ratio (SNR). ANOVA results shows that the length of travel has maximum impact on degree of sphericity evolution. The predicted sphericity obtained from the developed regression model and the values obtained experimentally are found to be in good agreement with each other. The sphericity values obtained from confirmation experiment, performed at 95% confidence level, ensures that the optimum result is correct and also the confirmation experiment values are within permissible limits.

Optimization of a Porous Ducted Air Induction System Using Taguchi's Parameter Design Method

Optimization of a Porous Ducted Air Induction System Using Taguchi's Parameter Design Method

Improving the Biodegradability of Polylactic Acid at Alcaligenes Faecalis and Staphylococcus Aureus Using the Optimization Method

The degradation of polylactic acid (PLA) can be divided into the hydrolysis, the degradation and metabolism. The hydrolysis reaction is caused by chain breakdown of the polymers of polylactic acid, resulting in the degradation of polylactic acid. Therefore, this study aims to improve the hydrolysis rate of PLA at the early stage of degradation process and then it increases the degradation rate of the PLA in the natural environment. We employed Taguchi method for parameter design of PLA hydrolysis, focusing on the control factors that affect the conditions of the hydrolysis rate of PLA, such as temperature, bacteria, ventilation degree, and nutrients and we also used orthogonal array to precede experiments, in conjunction with analysis of variance (ANOVA) to identify significant factors and optimal hydrolysis conditions for PLA. By analysis of variance, we know that temperature and bacteria as significant factors, and the factor of temperature contributed 96.882%. Finally, we employed confirmation Experiment to verify the reproducibility of the experiments. Our results have shown that the best condition of PLA hydrolysis rate experience with the reliability of its representatives are in compliance with the 95% of confidence interval, CI, which indicates the reliability of our study.

Construction of a 3C Product Mold Manufacturing Process Predictive Optimization Model

Mold trials are critical in the mold development process; therefore, it is necessary to develop predictive models that can control processing results and solve problems in processing parameter optimization to ensure manufacturing efficiency and processing quality. Using the six sigma method, this research constructed an optimized 3C (Computer, Communication, and Consumer electronic) product mold manufacturing process predictive model, and conducted an empirical study on the largest electronic products foundry. The Taguchi parameter design method, the back propagation network (BPN) prediction method, and genetic algorithms (GAs) were used to establish an optimization search module. The surface quality was inferred by the network predictive model as a limiting condition for acquiring the maximized material removal rate in milling. The optimized milling processing parameters of the maximum fitness degree can be determined by GA. The findings can serve as a practical reference for quality improvements and decision planning.

Taguchi method for parameter design in ACO algorithm for distribution–allocation in a two-stage supply chain

In a distribution–allocation problem, when fixed cost for a transportation route is also taken into account in addition to the unit transportation cost, the problem is known as fixed charge transportation problem (FCTP). It is not possible to solve an FCTP optimally in polynomial time. This forces the researchers and practitioners to develop efficient non-traditional optimisation techniques that can provide near-optimal solutions in lesser time. This paper presents a solution methodology using ant colony optimisation (ACO) for a distribution–allocation problem in a two-stage supply chain with fixed cost for a transportation route. Taguchi method for robust design is adopted for finding the optimum combination of parameters of the ACO algorithm. A comparative analysis between the predicted signal-to-noise (S/N) ratio and the actual S/N ratio reveals that the error deviation in the experiment is minimal. From the confirmation tests, a good agreement between the predicted S/N ratio and the actual S/N ratio is observed. This validates the proposed experiment based on Taguchi method for parameter design.

The Quality Cost Reduction in Hollow Glass Manufacturing by Taguchi Method

This paper presents the results of an experimental investigation carried out to optimize the weight of a glass manufacturing bottle of a product called CC35 by Taguchi method of parameter design. The experiments have been designed using an L16 orthogonal array with thirteen factors and two levels each. So the effects of each control factor level on the performance characteristic are analyzed using signal-to-noise ratios, mean response data and analysis of variance (ANOVA). Hence, an experimental setting is established; and to measure the performance of the Taguchi method on the manufacturing process before and after the experiment, three tools are used. The Xbar and range charts measure the stability of the process, the capability index estimates the process ability to deliver a good product in regard to the target value and customer specifications. The quality loss function (QLF) was used to determine the reduction in quality cost due to the elimination of deviation of the quality characteristic (weight) from the target value. Experiment shows that the Taguchi method applied on the glass bottle’s manufacturing process (CC35) ensures best stability and capability of the manufacturing process and reduces the weight which results in the quality cost down to 92%. Keywords: Hollow glass manufacturing; Taguchi; Quality loss function (QLF); Design of experiments; Optimization; Capability; ANOVA; Signal-to-noise ratio. © 2012 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved. doi: http://dx.doi.org/10.3329/jsr.v4i1.7900J. Sci. Res. 4 (1), 155-172 (2012)

Artificial neural network based approach for dynamic parameter design

The Taguchi parameter design method has been recognized as an important tool for improving the quality of a product or a process. However, the statistical methods and optimization procedures proposed by Taguchi have much room for improvement. For instance, the two-step procedure proposed by Taguchi may fail to identify an optimum design condition if an adjustment parameter does not exist, the optimal setting of a design parameter is determined only among the levels included in the parameter design experiment, and, for the dynamic parameter design, the signal parameter is assumed to follow a uniform rather than a general distribution. This paper develops an artificial neural network based dynamic parameter design approach to overcome the shortcomings of the Taguchi and existing alternative approaches. First, an artificial neural network is trained to map the relationship between the characteristic, design, noise and signal parameters. Second, Latin hypercube samples of the signal and noise parameters are obtained and used to estimate the slope between the signal parameter and characteristic as well as the variance of the characteristic at each set of design parameter settings. Then, the dynamic parameter design problem is formulated as a nonlinear optimization problem and solved to find the optimal settings of the design parameters using sequential quadratic programming. The effectiveness of the proposed approach is illustrated with an example.

Selection of Process Parameters for Optimizing the Weld Strength in Laser Transmission Welding of Acrylics

In this paper, an experimental investigation into laser transmission welding of acrylics is carried out. The Taguchi method of parameter design is used as a statistical design of experiment technique to set the optimal process parameters. Experiments are designed and conducted by using Taguchi's L16 orthogonal array. Maximization of weld strength is selected as the quality target. The signal-to-noise ratio and the analysis of variance are used to find the optimum levels within the window of parameters selected and to identify the order of importance of the process parameters. With the frame of this work the effects of process parameters on weld strength is also discussed. Finally, a confirmation test is conducted, which verifies that optimal laser transmission welding parameters can be determined effectively so as to improve weld strength through the Taguchi method.

DESIGN FOR RELIABILITY AND ROBUSTNESS: A CASE STUDY

Resistance welding is to bond two pieces of metal materials together by melting the materials in the contact area. An elevated temperature is generated by contact resistance when electrical current flows through the contact area of the two materials. Generally, a current is applied through two close electrodes. Sometimes, however, it is necessary to set the two electrodes far apart when the contact area is physically unreachable. The far separation of the electrodes makes difficult to generate reliable welds. This paper describes a reliability and robustness design method for the welding process. In particular, a concept design was conducted to avoid welding failure modes. The critical dimensions of a work piece were defined to make a successful weld. Then the welding processes for various dimensions of the work pieces were optimized using Taguchi's parameter design method. A thermal cycle test was performed to evaluate the reliability of the welds. It is shown that the welding process is robust and the welds have high reliability.