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This paper aims to discuss flow pattern transition (FPT) as an important factor in multiple-phase flow measurements. Several methods have been proposed to control FPT, but those methods fail to address the many issues in complex flow conditions that can affect flow patterns.

In this paper, a non-intrusive sensor instrumentation is applied to extract measurable data under different flow conditions. Using these data, a simple theoretical–mathematical method along with an orthogonal design is applied to FPT optimization. Orthogonal experiments are designed and carried out according to theoretical guidelines. Three selected process parameters – phase fraction, gas pressure in the initial independent process and liquid speed – are optimized for FPT results to produce a minimum FPT time.

The following results are obtained: the phase fraction in the initial independent process can lead to significant reductions in FPT time, gas pressure plays an important role and liquid speed has no apparent effect on FPT results. Under optimized conditions, FPT time can be shortened to 0.3-0.6 times by controlling the above three parameters compared with normal conditions.

The proposed method is simple, rapid and efficient for evaluating an FPT process and lays the foundation for further FPT applications.

The purpose of this paper is to provide an optimization schedule of structural parameters for the sound absorption performance of a cellular ceramic foam in the sound frequency range of 200–4,000 Hz.

The cellular ceramic foam with porosity of about 60–75% and the pore size of about 1–7 mm was successfully prepared by using natural zeolite powder as the main raw material. For this ceramic foam, the sound absorption performance was measured, and the absorption structure was optimized by some important structural parameters. With orthogonal experiment, optimization of structural parameters was found for absorption performance. By means of the range analysis method, the main factor is known to influence the performance of ceramic foam.

The present ceramic foam may have good absorption performance although at relatively low frequencies of 400–4,000 Hz while structural parameters of sample are appropriately combined. With orthogonal experiment, optimization of structural parameters for the absorption performance was found to be as follows: sample thickness, 25 mm; porosity, 73.5%; pore size, 4–5 mm and air gap depth, 20 mm. To influence the performance, sample thickness is the main factor, air gap depth is the second and both of pore size and porosity would have a relatively slight effect.

This paper presents a method to optimize the structural parameters of a cellular ceramic foam for sound absorption performance by means of orthogonal experiment.

Currently, the state of practice in experimental design centres on orthogonal designs (Alpizar et al., 2003), which are suitable when applied to surveys with a large sample size. In a stated choice experiment involving interdependent freight stakeholders in Sydney (see Hensher & Puckett, 2007; Puckett et al., 2007; Puckett & Hensher, 2008), one significant empirical constraint was difficult in recruiting unique decision-making groups to participate. The expected relatively small sample size led us to seek an alternative experimental design. That is, we decided to construct an optimal design that utilised extant information regarding the preferences and experiences of respondents, to achieve statistically significant parameter estimates under a relatively low sample size (see Bliemer & Rose, 2006).

The D-efficient experimental design developed for the study is unique, in that it centred on the choices of interdependent respondents. Hence, the generation of the design had to account for the preferences of two distinct classes of decision makers: buyers and sellers of road freight transport. This paper discusses the process by which these (non-coincident) preferences were used to seed the generation of the experimental design, and then examines the relative power of the design through an extensive bootstrap analysis of increasingly restricted sample sizes for both decision-making classes in the sample. We demonstrate the strong potential for efficient designs to achieve empirical goals under sampling constraints, whilst identifying limitations to their power as sample size decreases.

The purpose of this paper is to investigate the effects of parameters on the liquid phase migration (LPM) during the freeze-form extrusion fabrication (FEF) process.

To carry out this study, three factors were systematically investigated using orthogonal design of experiments. These three parameters are the extrusion velocity, the extrusion interval time and the extrusion head length. An orthogonal array with nine test units was selected for the experiments. Range analysis and analysis of variance were used to analyze the data obtained by the orthogonal experiments to identify the order of significant factors on LPM.

It was found that the LPM decreased with the increase of extrusion velocity and increased with the lengthening of extrusion interval time and the length of the extrusion nozzle. The order of significant factors for the LPM were found to be extrusion velocity > extrusion nozzle length > extrusion interval time.

Using an orthogonal design of experiments and a statistical analysis method, the liquid content of extrudate can be predicted and appropriate process parameter values can be selected. This leads to the minimization of LPM during the FEF process. Also, this analysis method could be used to study the LPM in other paste extrusion processes.

This paper suggests that the factors have significant impact on LPM during FEF process. The following analysis in this paper is useful for FEF users when prediction of LPM is needed. This methodology could be easily applied to different materials and initial conditions for optimization of other FEF-type processes. The research can also help to get better understanding of LPM during the FEF process.

Develops a robust maintenance float policy, that considers system design parameter settings that not only satisfy the system performance criteria but are also insensitive to various noise conditions. The experimental design strategy employed in the study involves the use of discrete event simulation. In the study, the strategy proposed involves solving a maintenance float policy using both the inner and outer arrays as advocated by Genichi Taguchi. Initial system variables and their parameter settings were chosen based on a prior study. These system variables were then classified into design factors and noise factors. An experimental design was developed using Taguchi’s orthogonal array, after which a simulation experiment was performed and additional data collected. Based on the results, regression was performed with the significant factors and interactions. From the regression analysis, a robust metamodel was developed. A cost model was also proposed.

The aim of this paper is to proposes a simple and unified method for generating the aliasing pattern of two‐ and three‐level fractional factorial designs be they regular or non‐regular. The paper also demonstrates how the aliasing patterns obtained using the postulated method can be used to render the main measures of aliasing severity.

The proposed method is based on viewing the fractional factorial designs geometrically. It entails regarding the columns of any design as vectors. On the premise that any two vectors are orthogonal if they are at right angle and bearing in mind that aliasing is a form of departure from orthogonality, the proposed method determines the degree of aliasing between any two columns by assessing the extent to which the angle between them differs from 90°.

Three examples were used to illustrate how the proposed method can be applied and to validate its results. The first dealt with a regular two‐level L₈ 2⁵⁻² design whereas the second concerned a non‐regular two‐level L₁₂ design used to study five‐factors, and the third example is based on a non‐regular L₁₈ design employed to examine three‐factors at three‐levels. For each of these, the aliasing pattern generated using the proposed method matches the one obtained using the conventional methods.

A recent empirical study of how experimental design is applied in certain Manufacturing Engineering journals revealed that aliasing is rarely investigated. One possible reason for this is the difficulty associated with comprehending the conventional methods of dealing with aliasing particularly in the cases where non‐regular two‐ and three‐level orthogonal arrays are used. The proposal of a simple and unified method for dealing with aliasing should encourage the researchers and practitioners to assess aliasing when performing their experiments.

The aim of this paper is to circumvent the multi‐distribution effects and small sample constraints that may arise in unreplicated‐saturated fractional factorial designs during construction blueprint screening.

A simple additive ranking scheme is devised based on converting the responses of interest to rank variables regardless of the nature of each response and the optimization direction that may be issued for each of them. Collapsing all ranked responses to a single rank response, appropriately referred to as “Super‐Ranking”, allows simultaneous optimization for all factor settings considered.

The Super‐Rank response is treated by Wilcoxon's rank sum test or Mann‐Whitney's test, aiming to establish possible factor‐setting differences by exploring their statistical significance. An optimal value for each response is predicted.

It is stressed, by example, that the model may handle simultaneously any number of quality characteristics. A case study based on a real geotechnical engineering project is used to illustrate how this method may be applied for optimizing simultaneously three quality characteristics that belong to each of the three possible cases, i.e. “nominal‐is‐best”, “larger‐is‐better”, and “smaller‐is‐better” respectively. For this reason, a screening set of experiments is performed on a professional CAD/CAE software package making use of an L₈(2⁷) orthogonal array where all seven factor columns are saturated by group excavation controls.

The statistical nature of this method is discussed in comparison with results produced by the desirability method for the case of exhausted degrees of freedom for the error. The case study itself is a unique paradigm from the area of construction operations management.

The advancement in modern manufacturing technology generated the need to develop new materials for better wear resistance. The purpose of this paper is to use the Taguchi optimization approach to examine which wear parameter significantly affects weight loss and coefficient of friction for RZ5-TiC composite. It is a simple and efficient method to find performance of wear parameter using minimum experimental runs.

RZ5-TiC composites were prepared using RZ5 as matrix, reinforced with TiC through self-propagating high-temperature synthesis technique. In the present work, an attempt has been made to study the influence of wear parameters like applied load (AL), sliding distance (SD) and Wt.% of TiC (WTC) on responses like weight loss and coefficient of friction of RZ5/TiCp composites. The pin-on-disc apparatus used to conduct abrasive wear test. The wear process parameters are optimized for minimum wear based on L27 Taguchi orthogonal design. The Taguchi technique using design of experiments (DOE) is used to obtain the data. The ANOVA and an orthogonal array are used to examine the influence of wear parameters on responses. The purpose is to examine parametric significances which affect responses.

It observed that wear parameters have the significant influence on responses of RZ5/TiCp composites. The interaction of sliding distance/Wt.% of TiC is observed and found significant influence on both responses. The optimum level of the significant wear parameters is achieved based on the maximum S/N ratio for RZ5/TiCp composites. The optimal interaction for weight loss and coefficient of friction is AL1-SD1-WTC3 and AL3-SD1-WTC3, respectively. Finally, the confirmation test is conducted and the results are obtained within the confidence interval.

The current manuscript provides an optimization of wear parameters using Taguchi approach. The extensive experimental data are used for this purpose and effects of wear parameters on responses are analyzed from the presented results. The results obtained are useful in improving the wear resistance of the RZ5-TiC composite.

Suggests that, in order to detect and correct software defects as early as possible, identifying and generating more defect‐sensitive test cases for software unit and subsystem testing is one solution. Proposes an orthogonal software testing approach based on the quality optimization techniques, Taguchi methods. This orthogonal approach treats the input parameters of a software unit or subsystem as design factors in an orthogonal arrays, and stratifies input parameter domains into equivalent classes to form levels of factors. Describes how test cases are generated statistically for each trial of factorial orthogonal experiments. The adequacy of the generated test cases can be validated by examining testing coverage metrics. The results of test case executions can be analysed in order to find the sensibility of test cases for detecting defects, to generate more effective test cases in further testing, and to help locate and correct defects in the early stage of testing.