Showing papers on "Orthogonal array published in 2008"

The Taguchi methodology as a statistical tool for biotechnological applications: A critical appraisal

Abstract: Success in experiments and/or technology mainly depends on a properly designed process or product. The traditional method of process optimization involves the study of one variable at a time, which requires a number of combinations of experiments that are time, cost and labor intensive. The Taguchi method of design of experiments is a simple statistical tool involving a system of tabulated designs (arrays) that allows a maximum number of main effects to be estimated in an unbiased (orthogonal) fashion with a minimum number of experimental runs. It has been applied to predict the significant contribution of the design variable(s) and the optimum combination of each variable by conducting experiments on a real-time basis. The modeling that is performed essentially relates signal-to-noise ratio to the control variables in a 'main effect only' approach. This approach enables both multiple response and dynamic problems to be studied by handling noise factors. Taguchi principles and concepts have made extensive contributions to industry by bringing focused awareness to robustness, noise and quality. This methodology has been widely applied in many industrial sectors; however, its application in biological sciences has been limited. In the present review, the application and comparison of the Taguchi methodology has been emphasized with specific case studies in the field of biotechnology, particularly in diverse areas like fermentation, food processing, molecular biology, wastewater treatment and bioremediation.

Multi response optimization of machining parameters of drilling Al/SiC metal matrix composite using grey relational analysis in the Taguchi method.

Abstract: This paper presents a new approach for the optimization of drilling parameters on drilling Al/SiC metal matrix composite with multiple responses based on orthogonal array with grey relational analysis. Experiments are conducted on LM25-based aluminium alloy reinforced with green bonded silicon carbide of size 25 μm (10% volume fraction). Drilling tests are carried out using TiN coated HSS twist drills of 10 mm diameter under dry condition. In this study, drilling parameters namely cutting speed, feed and point angle are optimized with the considerations of multi responses such as surface roughness, cutting force and torque. A grey relational grade is obtained from the grey analysis. Based on the grey relational grade, optimum levels of parameters have been identified and significant contribution of parameters is determined by ANOVA. Confirmation test is conducted to validate the test result. Experimental results have shown that the responses in drilling process can be improved effectively through the new approach.

Grey-based taguchi method for optimization of bead geometry in submerged arc bead-on-plate welding

Abstract: A multi-response optimization problem has been developed in search of an optimal parametric combination to yield favorable bead geometry of submerged arc bead-on-plate weldment. Taguchi’s L25 orthogonal array (OA) design and the concept of signal-to-noise ratio (S/N ratio) have been used to derive objective functions to be optimized within experimental domain. The objective functions have been selected in relation to parameters of bead geometry viz. bead width, bead reinforcement, depth of penetration and depth of HAZ. The Taguchi approach followed by Grey relational analysis has been applied to solve this multi-response optimization problem. The significance of the factors on overall output feature of the weldment has also been evaluated quantitatively by analysis of variance method (ANOVA). Optimal result has been verified through additional experiment. This indicates application feasibility of the Grey-based Taguchi technique for continuous improvement in product quality in manufacturing industry.

Designing an integrated multi-echelon agile supply chain network: a hybrid taguchi-particle swarm optimization approach

Abstract: The present paper attempts to explore the integration of production, distribution and logistics activities at the strategic decision making level where, the objective is to design a multi-echelon supply chain network considering agility as a key design criterion. The design network conceived here addresses a class of five echelons of supply chains including suppliers, plants, distribution centers, cross-docks and customer zones. The problem has been mathematically formulated as a multi-objective optimization model that aims to minimize the cost (fixed and variable) and maximizes the plant flexibility and volume flexibility. The notion of cross-dock has been introduced as an intermediate level between distribution centers and customer zones to increase the profitability of manufacturing and service industries. In order to solve the underlying problem, a novel algorithm entitled hybrid taguchi-particle swarm optimization (HTPSO) has been proposed that incorporates the characteristics of statistical design of experiments and random search techniques. The main idea is to integrate the fundamentals of taguchi method i.e. orthogonal array and signal to noise ratio (SNR) in the PSO meta-heuristic to minimize the effect of the causes of variations. The proposed model has been authenticated by undertaking problem instances of varying size. Extensive computational experiments are conducted to validate the same and also the efficacy of the proposed HTPSO algorithm. The results obtained reveal that proposed solution methodology is an effective approach to solve the underlying problem.

A new approach to surface roughness and roundness improvement in wire electrical discharge turning based on statistical analyses

Abstract: In this paper, the effects and the optimization of machining parameters on surface roughness and roundness in the turning wire electrical discharge machining (TWEDM) process are investigated. In the TWEDM process, a new machining parameter, such as rotational speed, is introduced, which changes the normal machining conditions in conventional wire electrical discharge machining (WEDM). By the Taguchi method, a complete realization of the process parameters and their effects were achieved. The Taguchi method has not been used in TWEDM by other researchers. The surface roughness and roundness were measured to verify the process. In addition, the open-circuit voltage, pulse-off time, open arc voltage, and the inter-electrode gap size, which are replaced by power, time-off, voltage, and servo, respectively, and also wire tension, wire speed, and rotational speed were chosen for evaluation by the Taguchi method. An L18 (21 × 37) Taguchi standard orthogonal array was chosen for the design of experiments. The level of importance of the machining parameters on the surface roughness and roundness was determined by using analysis of variance (ANOVA). The optimum machining parameters combination was obtained by using the analysis of signal-to-noise (S/N) ratios. The variation of surface roughness and roundness with machining parameters was mathematically modeled by using the regression analysis method. Finally, experimentation was carried out to identify the effectiveness of the proposed method. The presented model is also verified by a set of verification tests.

Robust parameter design and multi-objective optimization of laser beam cutting for aluminium alloy sheet

Abstract: The application of laser beam for precise cutting of sheet metals, in general, and reflective sheet metals, like aluminium, in particular, has become of interest in the recent past. The optimum choice of the cutting parameters is essential for the economic and efficient cutting of difficult to cut materials with laser beams. In this paper, a robust design and quality optimization tool called the Taguchi methodology has been applied to find the optimal cutting parameters for cutting of a reflective sheet made of aluminium alloy with a Nd:YAG laser beam. All the steps of the Taguchi method, such as a selection of orthogonal array, computation of signal-to-noise ratio, decision of optimum setting of parameters, and the analysis of variance (ANOVA), have been done by a self-developed software called computer aided robust parameter design (CARPD). A considerable improvement in the kerf taper (KT) and material removal rate (MRR) has been found by using Taguchi method-based predicted results. Confirmatory experimental results have shown good agreement with predicted results. Further, the Taguchi quality loss function has also been used for multi-objective optimization of laser beam cutting of Al-alloy sheet. The results of multi-objective optimization are compared with the single-objective optimization and it has been found that the kerf taper was increased by 1.60% in multi-objective optimization while the MRR was same in both cases.

Optimization of parameters for the fabrication of gelatin nanoparticles by the Taguchi robust design method

Abstract: The Taguchi method is a statistical approach to overcome the limitation of the factorial and fractional factorial experiments by simplifying and standardizing the fractional factorial design. The objective of this study was to optimize the fabrication of gelatin nanoparticles by applying the Taguchi design method. Gelatin nanoparticles have been extensively studied in our previous works as an appropriate carrier for drug delivery, since they are biodegradable, non-toxic, are not usually contaminated with pyrogens and possess relatively low antigenicity. Taguchi method with L16 orthogonal array robust design was implemented to optimize experimental conditions of the purpose. Four key process parameters – temperature, gelatin concentration, agitation speed and the amount of acetone – were considered for the optimization of gelatin nanoparticles. As a result of Taguchi analysis in this study, temperature and amount of acetone were the most influencing parameters of the particle size. For characterizing the n...

Modeling and optimization of features of bead geometry including percentage dilution in submerged arc welding using mixture of fresh flux and fused slag

Abstract: Quality has now become an important issue in today’s manufacturing world. Whenever a product is capable of conforming to desirable characteristics that suit its area of application, it is termed as high quality. Therefore, every manufacturing process has to be designed in such a way that the outcome would result in a high quality product. The selection of the manufacturing conditions to yield the highest desirability can be determined through process optimization. Therefore, there exists an increasing need to search for the optimal conditions that would fetch the desired yield. In the present work, we aim to evaluate an optimal parameter combination to obtain acceptable quality characteristics of bead geometry in submerged arc bead-on-plate weldment on mild steel plates. The SAW process has been designed to consume fused flux/slag, in the mixture of fresh flux. Thus, the work tries to utilize the concept of ‘waste to wealth’. Apart from process optimization, the work has been initiated to develop mathematical models to show different bead geometry parameters, as a function of process variables. Hence, optimization has been performed to determine the maximum amount of slag--flux mixture that can be used without sacrificing any negative effect on bead geometry, compared to the conventional SAW process, which consumes fresh flux only. Experiments have been conducted using welding current, slag-mix percentage and flux basicity index as process parameters, varied at four different levels. Using four3 full factorial designs, without replication, we have carried out welding on mild steel plates to obtain bead-on-plate welds. After measuring bead width, depth of penetration and reinforcement; based on simple assumptions on the shape of bead geometry, we calculated other relevant bead geometry parameters: percentage dilution, weld penetration shape factor, weld reinforcement form factor, area of penetration, area of reinforcement and total bead cross sectional area. All these data have been utilized to develop mathematical models between predictors and responses. Response surface methodology (RSM), followed by the multiple linear regression method, has been applied to develop these models. The effects of selected process parameters on different responses have been represented graphically. Finally grey relational analysis coupled with the Taguchi method (with Taguchi’s orthogonal array) has been applied for parametric optimization of this welding technique. Confirmatory experiments have been conducted to verify optimal results.

Using Orthogonal Arrays in the Sensitivity Analysis of Computer Models

Abstract: We consider a class of input sampling plans, called permuted column sampling plans, that are popular in sensitivity analysis of computer models. Permuted column plans, including replicated Latin hypercube sampling, support estimation of first-order sensitivity coefficients, but these estimates are biased when the usual practice of random column permutation is used to construct the sampling arrays. Deterministic column permutations may be used to eliminate this estimation bias. We prove that any permuted column sampling plan that eliminates estimation bias, using the smallest possible number of runs in each array and containing the largest possible number of arrays, can be characterized by an orthogonal array of strength 2. We derive approximate standard errors of the first-order sensitivityindices for this sampling plan. We give two examples demonstrating the sampling plan, behavior of the estimates, and standard errors, along with comparative results based on other approaches.

Wide-Sense Estimation on the Special Orthogonal Group

Abstract: In this paper we consider a simple estimation problem on the special orthogonal group SO(n) and indicate a possible way to construct approximate filters which is much in the same spirit of the “wide sense” approach to linear filtering theory. Our interest is mainly motivated by applications to computer vision.

A Novel GA-Taguchi-Based Feature Selection Method

Abstract: This work presents a novel GA-Taguchi-based feature selection method. Genetic algorithms are utilized with randomness for "global search" of the entire search space of the intractable search problem. Various genetic operations, including crossover, mutation, selection and replacement are performed to assist the search procedure in escaping from sub-optimal solutions. In each iteration in the proposed nature-inspired method, the Taguchi methods are employed for "local search" of the entire search space and thus can help explore better feature subsets for next iteration. The two-level orthogonal array is utilized for a well-organized and balanced comparison of two levels for features--a feature is or is not selected for pattern classification--and interactions among features. The signal-to-noise ratio (SNR) is then used to determine the robustness of the features. As a result, feature subset evaluation efforts can be significantly reduced and a superior feature subset with high classification performance can be obtained. Experiments are performed on different application domains to demonstrate the performance of the proposed nature-inspired method. The proposed hybrid GA-Taguchi-based approach, with wrapper nature, yields superior performance and improves classification accuracy in pattern classification.

Orthogonal array application for optimal combination of software defect detection techniques choices

Abstract: In this paper, we consider a problem that arises in black box testing: generating small test suites (i.e., sets of test cases) where the combinations that have to be covered are specified by input-output parameter relationships of a software system. That is, we only consider combinations of input parameters that affect an output parameter, and we do not assume that the input parameters have the same number of values. To solve this problem, we propose interaction testing, particularly an Orthogonal Array Testing Strategy (OATS) as a systematic, statistical way of testing pair-wise interactions. In software testing process (STP), it provides a natural mechanism for testing systems to be deployed on a variety of hardware and software configurations. The combinatorial approach to software testing uses models to generate a minimal number of test inputs so that selected combinations of input values are covered. The most common coverage criteria are two-way or pairwise coverage of value combinations, though for higher confidence three-way or higher coverage may be required. This paper presents some examples of software-system test requirements and corresponding models for applying the combinatorial approach to those test requirements. The method bridges contributions from mathematics, design of experiments, software test, and algorithms for application to usability testing. Also, this study presents a brief overview of the response surface methods (RSM) for computer experiments available in the literature. The Bayesian approach and orthogonal arrays constructed for computer experiments (OACE) were briefly discussed. An example, of a novel OACE application, to STP optimization study was also given. In this case study, an orthogonal array for computer experiments was utilized to build a second order response surface model. Gradient-based optimization algorithms could not be utilized in this case study since the design variables were discrete valued. Using OACE novel approach, optimum combination of software defect detection techniques choices for every software development phase that maximize all over Defect Detection Effectiveness of STP were determined.

Algebraic strategy to generate pairwise test set for prime number parameters and variables

Abstract: Generating pairwise test set when the total number of variables is prime numbers has a remarkable property in that the test case generation process can be simplified by applying straightforward strategy that does not require any storage. This paper discusses the said algebraic strategy and compares the results with the well-known orthogonal array strategy. Additionally, this paper also demonstrates the applicability and simplicity of the strategy as compared to orthogonal array to obtain optimal test set for pairwise testing.

A Study of Taguchi and Design of Experiments Method in Injection Molding Process for Polypropylene Components

Abstract: This study analyzes contour distortions, wear mass losses and tensile properties of polypropylene (PP) composite components applied to the interior coffer of automobiles. The specimens are prepared under different injection molding conditions by changing melting temperatures, injection speeds, and injection pressures via three computer-controlled progressive strokes. The contour distortions, wear and tensile properties are selected as quality targets. The arrangement of sixteen experiments is based on an orthogonal array table. Both the Taguchi method and the design of experiments (DOE) method are applied to determine an optimal parameter setting. In addition, a side-by-side comparison of two different approaches is provided. In this study, regression models that link the controlled parameters and the targeted outputs are developed, and the mathematic models can be utilized to predict the contour distortions, wear and tensile properties at various injection molding conditions.

Machining parameters optimization on the die casting process of magnesium alloy using the grey-based fuzzy algorithm

Abstract: The present investigation focuses on finding the optimal machining parameters’ setting for the die casting process of magnesium alloy using the grey-based fuzzy algorithm. This proposed algorithm, coupling the grey relational analysis with the fuzzy logic, obtains a grey-fuzzy reasoning grade to evaluate the multiple performance characteristics according to the grey relational coefficient of each performance characteristic. One of the real case studies performed in the die casting process, thin-walled cover components of liquid crystal display (LCD) panel, verifies that the proposed optimum procedure is feasible and effective. The casting density, warpage and flow mark of finished product are adopted to evaluate the machiniablity performances. Various die casting parameters, such as the die temperature, the pressure of injection, the plunger velocity (first and second stage) and the filling time are explored in the experiment. The table of orthogonal array is used in the experimental design. The response table, response graph and analysis of variance (ANOVA) are used to find the optimal setting and the influence of machining parameters on the multiple performance characteristics. Under the circumstances of the optimal machining parameters, the confirmation tests indicate the effectiveness of the proposed algorithm. Experimental results have shown that the required performance characteristics in the die casting process have great improvements by using this proposed algorithm.

Determination of Optimal Parameters for SKD11 CNC Turning Process

Abstract: This study investigated the optimization of a CNC turning process for SKD11 (JIS). The design of experiments (DOE) method with an orthogonal array was applied. Nine experimental runs were performed based on the orthogonal array. The surface properties of roughness average and roughness maximum and the roundness were studied; the analysis of variance (ANOVA) was adapted to investigate which parameters had the most influence on the CNC turning process for SKD11 (JIS). Also, models for predictions of the roughness average, roughness maximum, and roundness had been developed in terms of cutting speed, feed rate, depth of cut, and the mixture ratio of cutting fluids.