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Calcium phosphate (CaP) compounds like hydroxyapatite and tricalcium phosphates are considered to be very important biomaterials. This study used RF-magnetron sputtering (RF-MS) to deposit CaP onto 316L SS. Due to the complex nature of the effect of different sputtering parameters on the quality and integrity of the coatings, there is a need to further investigate those parameters collectively. An L₉(3⁴) orthogonal array was employed to design the experiment that was used to investigate four important coating parameters which include RF-power, argon gas flow rate, deposition time and post-heat treatment conditions. The coating composition and structure were evaluated using XRD, EDX and FTIR. The mechanical property was measured in terms of the adhesion strength using a microscratch testing machine. The response graph of the results revealed that the interfacial strength of CaP was mainly influenced by the deposition power, while the coating thickness was predominantly affected by the argon gas flow rate. High adhesion strength was achieved when the coatings have at least 2 μm thickness and deposited at a working pressure of 12 m Torr. ANOVA on the control factors helped rank the parameters accordingly in order of importance. Based on the response of the control factors, it was found that optimum adhesion strength could be achieved by depositing the coatings using the following parameters: 10 sccm of argon gas flow rate; 150 W of RF power; and 16 h of deposition.

Quantum orthogonal arrays are combinatorial designs with a remarkable class of genuinely multipartite highly entangled states. In this paper, we propose the method for constructing maximally multi-qubit entangled state through phase parameters of orthogonal arrays. Using this method, we not only determine that maximally n-qubit entangled state, but also find the $n-1$ orthogonal array that gives maximally $n-1$ entangled states. Such states play an important role in quantum theory with a high degree of multipartite entanglement.

Low-frequency noise is regarded as special environmental noise problem which has a serious impact on people’s lives. The traditional technology cannot effectively insulate the low-frequency noise, while the emergence of acoustic metamaterial makes it come true. This paper studies the acoustic insulation of membrane-type acoustic metamaterial. Due to different weights of the factor, an analytical method based on analytic hierarchy process (AHP) is proposed to analyze the affecting factors of acoustic insulation performance. The orthogonal array results show that the main factors affecting acoustic insulation are membrane thickness, membrane preload force and attached mass. A factor-weighted k-Nearest Neighbor (kNN) classification approach is proposed to predict different levels of acoustic insulation, which also provides a reference for the analysis of acoustic insulation. The experimental results demonstrate that when k = 3, the maximum classification accuracy of acoustic insulation is 98.2% by using AHP-kNN approach, which makes the accuracy for acoustic insulation is higher than other three baselines.

Two-level fractional factorial design is an efficient technique for experiments considering a large number of factors. To evaluate the efficiency and analyze the data for such a design, we need to know the generators for the design, so that, using the generators, we can generate its defining relation and alias structure. Although knowing the generators is important for a two-level fractional factorial design, it is not unusual in actual industrial situations for the generators used in the design to be lost or overlooked while the design is performed. Since Taguchi methods has been widely applied in industry, in this research, an efficient algorithm based on Taguchi orthogonal arrays (OA's) and interaction tables is developed to identify the generators for given designs. Furthermore, with the investigation of the insights of Taguchi OA's and interaction tables, this research may provide ideas for making Taguchi methods a simple tool for developing optimal designs for 2^{k - p} experiments.

In this paper, the machinability aspects of Ti-5553 have been experimentally investigated during Electro-Discharge Machining using three different geometrical shapes of copper electrodes i.e. cylindrical, triangular, and square. TIMETAL (Ti-5553) is a titanium-based alloy extensively used for special aerospace and marine applications due to its high strength and higher hardenability. By changing each of the aforementioned process parameters at three distinct levels, experiments based on the ${\text{L}}_{27}$ orthogonal array (OA) design of the experiment (DOE) were carried out. The machining performance has been carried out by utilizing different input parameters i.e. current, pulse off time ($T_{\text{off}}$), flushing pressure ($F_p$), tool shape ($T_s$), and voltage (V) to examine machining performance characteristics like material removal rate (MRR), tool wear rate (TWR), surface roughness (Ra), white layer thickness (WLT), and surface crack density (SCD). Surface integrity in contents of surface morphology and surface topography is discussed herein. In this MRR, TWR, and Ra have been optimized by using a methodology (combining Grey relational analysis method and Taguchi’s philosophy) and found the optimal parameters that will have more MRR and less TWR, Ra. Later SCD and WLT were investigated by employing the optimal setting (A3, B2, C2, D2, E1, F3) and arbitrary setting (A3, B2, C1, D3, E3, F2) and concluded that SCD and WLT are less by utilizing optimal settings for machining as compared to arbitrary settings. Among all three different geometrical shapes of copper electrodes, the cylindrical tool has been found to be the best suitable tool for machine Ti-5553.

Objective: The minimum detectable difference (MDD) of computed tomography (CT) scanned images was quantified and optimized according to an indigenous hepatic phantom, line group gauge and Taguchi ${\text{L}}_{18}$ optimization analysis in this work. Methods: Optimal combinations of CT scan factors in every group with the level organization were judged using the Taguchi analysis, in which every factor was organized into only 18 groups, creating evaluated outcomes with the same confidence as if every factor was analyzed independently. The five practical factors of the CT scan were (1) kVp, (2) mAs, (3) pitch increment, (4) field of view (FOV) and (5) rotation time for one loop of CT scan. Insofar as each factor had two or three levels, the total number of 162 (i.e., $2\times 3\times 3\times 3\times 3$) combinations was considered. Results: The optimal setting was 120kVp, 300mAs, 0.641 pitch, 320mm FOV and 1.0s of rotation time of CT scan. The minimal MDD was 2.65mm under 0.39mm of the slit depth from the revised Student’s $t$-test with a 95% confidence level. In contrast, the MDD of conventional and the best one (no. 7) among all original 18 groups were 3.27mm and 2.93mm for 0.43mm and 0.41mm slit depths, respectively. Conclusion: The Taguchi analysis was found very lucrative for the design of imaging analysis in practical diagnosis. The indigenous line group gauge and hepatic phantom also proved to be suitable in simulating the human body in real hepatic carcinoma examination.

A comprehensive review of applying Taguchi’s optimization methodology to medical facilities was evaluated in this study. Taguchi’s optimization methodology is one kind of robust designation and is reputed for integrating multiple factors to pursue one goal. According to Taguchi’s suggestion, the efficient and reliable arrangement of experimental groups with numerous factors shortened the observed timing and provided bountiful statistical data. Although this method is widely used in mechanical, civil, and chemical engineering fields, it became adopted in medical facilities only in the last decade. Most of Taguchi’s analyses focused on optimizing the imaging quality for diagnosis. The medical facilities include regular X-ray, cardiac X-ray, CT (computed tomography), CTA (computed tomography angiography), LINAC (medical linear accelerator), or gamma camera scans. The images were all manipulated according to various radiation-induced interactions; thus, the optimization process of imaging resolution can offer an essential contribution to this kind of facility. In this study, we summarized the Taguchi-related papers in medical facilities and evaluated common principles in organizing the unique orthogonal array, assigning various signal-to-noise ratios, using quantified gauges, and ranking or grading the obtained imaging quality in the datum analysis process. The further elaboration on how to preset the user demanded goal in the optimization process, the necessity of focusing on cross interaction among factors, dynamic analysis superiority over static one preset in Taguchi’s analysis, and how to preset an ideal signal-to-noise ratio to satisfy the researcher demand, the importance of verification or testification in clinical cases or the assistance of ANOVA to depict a complete concept of applying Taguchi’s optimization methodology.

This study optimized spatial resolution of mammography imaging quality using a CIRS-016A commercial line gauge and the Taguchi methodology. The line gauge with a precise line pair from 5lp/mm to 20lp/mm was placed on top of triangular PMMA plates to simulate the female breast undergoing mammography. Five factors: target/filter, kVp, mAs, PMMA plate thickness, and compression force, were organized into 18 groups according to the Taguchi L${}_{18}$ orthogonal array. Tactically, the 18 various combinations of factors could provide similar confidence levels, as those following the full factorial combination in reality. Seven experienced radiology experts judged the 18 imaging qualities based on contrast, sharpness, and spatial resolution. Then the signal-to-noise ratio was calculated according to the “the larger, the better” ranking order. The optimal preset of mammography was verified from the unique fish bone plot and the follow-up analysis of variance (ANOVA) test. The optimal combination of factors was as follows: Rh/Ag as target/filter, 32kVp, 36mAs, a 45mm thick PMMA plate, and a 13daN compression force in routine diagnosis. The concurrent resolution of 6lp/mm or about a 0.09mm minimum detectable difference (MDD) was superior to 5lp/mm of the conventional preset or combinations of factors of either highest Avg or lowest std. Compared to other studies with various facilities, this was the finest resolution among the routine X-ray, cardiac X-ray or computed tomography (CT), and computed tomography angiography (CTA).

Traveling Wire Electro-Chemical Spark Machining (TW-ECSM) process is a new innovative thermal erosion-based machining process suitable for cutting electrically nonconductive materials using tool electrode in the form of wire. This article attempts experimental modeling of TW-ECSM process using a hybrid methodology comprising Taguchi methodology (TM) and response surface methodology (RSM). The experiments were carried out on borosilicate glass using L${}_{27}$ orthogonal array (OA) considering the input parameters like applied voltage, pulse on-time, pulse off-time, electrolyte concentration and wire feed velocity along with process performances such as material removal rate (MRR), surface roughness (R${}_{\text{a}})$ and kerf width (K${}_{\mathit{\text{w}}})$. The interaction influence of input parameters on process performances was also discussed. Further, multi-objective optimization (MOO) of response performances of TW-ECSM process is executed using a coupled approach of grey relational analysis (GRA) and principal component analysis (PCA). The optimal process parameter setting illustrates the improvement of MRR by 171%, diminution of R_a and K${}_{\mathit{\text{w}}}$ by 27% and 8% against the initial parameter settings. Moreover, irregular cutting of kerf width and surface characteristics were also scrutinized using scanning electron microscope (SEM).

New superalloys are potential materials in aircraft and power plant industries because of their properties like high-temperature strength, creep life and resistance to corrosion and oxidation at elevated temperatures. Because of the superior properties of superalloys, machining them using the conventional processes is a difficult task that is associated with high cost and poor accuracy. In this study, an attempt has been made to machine NIMONIC 75 superalloy by the electro discharge machining (EDM) process, using the Taguchi-based Gray Relational Analysis method for multi-objective optimization of material removal rate (MRR), tool electrode wear rate (TEWR) and surface finish (SF). The experiments conducted were based on $L_{18}$ (2${}^1\times 3^5$) orthogonal array. Six input parameters namely tool material, peak current, gap voltage, pulse on-time, pulse off-time and tool lift time were considered in this study. The validation results proved that the parametric setting of tool material as copper, peak current as 12A, gap voltage as 50V, pulse on-time as 200$\mu$s, pulse off-time as 15$\mu$s and tool lift time as 2s, yields optimized values of the performance characteristics. SEM images indicate the presence of numerous surface irregularities, whereas the XRD test shows the formation of various carbides on the EDMed surface.

Numerous constructions of the best known covering arrays are effective only for specific numbers of symbols. Fusion replaces numerous symbols by one, and can thereby employ such constructions to produce useful covering arrays on fewer symbols. Augmentation instead replaces one symbol by many, permitting the construction of covering arrays from those with fewer symbols. Until this time, augmentation has been of limited value because it introduces substantial redundant coverage. Here a general augmentation method is improved upon by analyzing the classes of interactions to be covered and employing variants of covering arrays, quilting arrays, to reduce the redundancy introduced. For strengths four, five, and six, quilting arrays are produced that can be used in the refined augmentation to produce many best known covering arrays.

This study determined the optimum HSS cutting tool technique parameters for milling W-Al-Si-C rods using Taguchi methodology. This paper explains the empirical results of the selection of appropriate cutting settings that assure lower power consumption in high-end Computer Numerical Control (CNC) machines. An experiment employing the Taguchi methodology on an extruded W-Al- Si-C rod was performed on a CNC lathe with cutting speed, feed rate, and depth of cut as the process parameters. The performance characteristics (energy usage) were quantified by a data collection system. Minor energy process parameters were selected after data analysis. Experimental results are presented to demonstrate the worth of the chosen methodology. A total of 350rpm, 0.37mm/rev feed rate, and 1mm of cut depth produced the best MRR result. The maximum material removal rate (MRR) is obtained at lower levels of spindle speed and depth of cut, i.e., 1.452g/sec.

Granularity and perfect balance are defined and discussed for multiple factor designs. The granularity of a design is related to its discrepancy, an important concept in uniform experimental design. It indicates how fine a structure in the dependence of the response on the factors can be resolved. The balance of a design is similar to the resolution of fractional factorial designs, but it is defined for a much broader class of designs. The granularities and balance of various designs, including simple random designs, orthogonal arrays, digital nets, and integration lattices are compared. Two applications, the simple pendulum and blood glucose monitoring, are used to illustrate how granularity and balance can identify good designs.

When an orthogonal array (OA) of n rows is used as the design matrix in an experiment, n is the number of runs. In an OA of q levels, n is an integer multiple of q². In an experiment, if the number of runs cannot be set exactly equal to the number of rows of an OA because of constraints in resources or other reasons, the experimenter may use a design matrix formed by omitting some rows of an OA. If such a design matrix is used, the number of observed response obtained may not be enough for estimation of all the effects corresponding to columns of the orthogonal array. A lean design is a design matrix formed by deleting some rows and columns of an OA, which still allows efficient estimation of the effects of the factors corresponding to the remaining columns of the OA. In this article, the authors discuss lean designs of 2 and 3 levels, and provide D-optimal OA's from which lean designs can be formed.

This paper elaborates the kernel selection problem in the majorization framework by Zhang, Fang, Li & Sudjianto (2004) for experimental designs. For designs with qualitative factors, the row-wise coincidence distribution and its raw, central and factorial moments are studied. Under the effects hierarchy principle, two protocols are recommended to employ power and exponential kernels, which are shown equivalent to some classical criteria for fractional factorial designs and uniform designs, respectively. In addition, an extension of majorization framework is given to uniform designs with quantitative factors under wraparound discrepancy criterion.