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A considerable portion of the work on mixed orthogonal arrays applies specifically to arrays of strength 2. Although strength t = 2 is arguably the most important case for statistical applications, there is an urgent need for better methods for t ≥ 3. However, the knowledge on the existence of arrays for t ≥ 3 is rather limited. In this paper, new construction methods for symmetric and asymmetric orthogonal arrays (OAs) with high strength are proposed by using lower strength orthogonal partitions of spaces and OAs. A positive answer is provided to the open problem in Hedayat, Sloane and Stufken (Orthogonal Arrays: Theory and Applications (1999) Springer) on developing better methods and tools for the construction of mixed orthogonal arrays with strength t ≥ 3. Not only are the methods straightforward, but also they are useful for constructing symmetric or asymmetric OAs of arbitrary strengths, numbers of levels and various sizes. The constructed OAs can be utilized to generate more OAs. The resulting OAs have a high degree of flexibility and many other desirable properties. Some selective OAs are tabulated for practical uses.

Co-continuous composites have potential in friction and braking applications due to their unique tribological characteristics. The present study involves Taguchi grey relational analysis-based optimization of wear parameters such as applied load, sliding speed and sliding distance, and their effect on dry sliding wear performance of AA6063/SiC co-continuous composite manufactured by gravity infiltration. A Taguchi L9 orthogonal array was designed and nine experimental runs were performed based on the designed experiments. The coefficient of wear and specific wear rate were recorded for each experiment. Based on the average responses computed from Taguchi grey relational analysis, an applied load of 60 N, sliding speed of 1 m/s and sliding distance of 1000 m were estimated to be the optimal parameters. An Analysis of Variance (ANOVA) was conducted to identify the predominant factor and established all the three factors as being significant. The sliding distance was found to have the highest significant influence of 61.05% on the wear of the C4 composite. Confirmation experiments conducted using the optimal parameters indicated an improvement of 35.25% in grey relational grade. Analysis of the worn surfaces of the confirmation experiment revealed adhesive and abrasive wear as the governing mechanisms.

In polymer composites, synthetic fibers are primarily used as a chief reinforcing material, with a wide range of applications, and are therefore essential to study. In the present work, we carried out the erosive wear of natural and synthetic fiber-based polymer composites. Glass fiber with jute and Grewia optiva fiber was reinforced in three different polymer resins: epoxy, vinyl ester and polyester. The hand lay-up method was used for the fabrication of composites. L16 orthogonal array of Taguchi method used to identify the most significant parameters (impact velocity, fiber content, and impingement angle) in the analysis of erosive wear. ANOVA analysis revealed that the most influential parameter was in the erosive wear analysis was impact velocity followed by fiber content and impingement angle. It was also observed that polyester-based composites exhibited the highest erosive wear followed by vinyl ester-based composites, and epoxy-based composites showed the lowest erosive wear. From the present study, it may be attributed that the low hardness of the polyester resulting in low resistance against the impact of erodent particles. The SEM analysis furthermore illustrates the mechanism took place during the wear examination of all three types of composites at highest fiber loading. A thorough assessment uncovers brittle fractures in certain regions, implying that a marginal amount of impact forces was also acting on the fabricated samples. The developed fiber-reinforced polymer sandwich composite materials possess excellent biocompatibility, desirable promising properties for prosthetic, orthopaedic, and bone-fracture implant uses.

We present a mixed integer linear programming approach to orthogonally block two-level, multilevel, and mixed-level orthogonal designs. The approach involves an exact optimization technique which guarantees an optimal solution. It can be applied to many problems where combinatorial methods for blocking orthogonal designs cannot be used. By means of 54-run and 64-run examples, we demonstrate that our approach outperforms two benchmark techniques in terms of the number of estimable two-factor interaction contrasts and in terms of the D-efficiency for models with main effects and some two-factor interaction contrasts. We demonstrate the generic nature of our approach by applying it to the most challenging instances in a catalog of all orthogonal designs of strength 3 with up to 81 runs as well as a small catalog of strength-4 designs. The approach can also be applied to strength-2 designs, but, for these cases, alternative methods described in the literature may perform equally well. Supplementary materials for this article are available online.

Polymer composites with different reinforcements have many applications. By adjusting process settings and adding fibers and fillers, composite properties can be improved. Additive manufacturing is popular in the polymer industry because it can manufacture intricately designed parts with fewer defects and greater strength with less material consumption. Composites use thermoplastics and thermosetting polymers. Thermoset plastics cannot be reused or recycled; therefore, they are disposed in landfills, creating pollution and environmental harm. In this work, thermoplastic ASA (Acrylonitrile Styrene Acrylate) polymer filament is used for FDM 3D printing. The specimens are made by varying five process parameters that affected the materials’ mechanical properties. The tensile, flexural and impact specimens are made using MINITAB software and ASTM requirements. The L18 orthogonal array experimental design, specimens and results were optimized. Infill density and layer height were most influential. Maximum tensile strength of 51.86 MPa, flexural strength of 82.56 MPa and impact strength of 0.180 J/mm2 were obtained by following the software-suggested input factors and compared with the predicted values. Final error percentage was obtained between the predicted and the experimental results and it was found to be under 3%, which is acceptable.

Abrasive powder-mixed electrode-coated electrical discharge machining (APMEC-EDM) is a hybrid manufacturing process that involves using a abrasive powder mixed dielectric fluid and coated electrodes and combining benefits of both mechanical and thermal interactions. Present study aims to use a new performance assessment technique, gray relational analysis (GRA), to assess the influence of optimizing the APMEC-EDM performance on Nimonic80A Superalloy. Here, five control factors are considered as machining parameters: pulse current (A), pulse on-time (T on ), pulse off-time (T off ), Inter Electrode gap (mm), and aluminum powder concentration (g/L). The GRA L27 Orthogonal Array DOE can determine best parameters for multiple responses. GRA is employed to acquire a single performance index, and gray correlational class is used to optimize the APMEC-EDM process using a gray correlation coefficient with a lower tool wear rate, radial overcut, and higher material removal rate. The multi-objective optimization optimum values are Current at 15 A, Inter Electrode Gap at 2 mm, and Powder concentration in dielectric at 9 g/l, T on at 300 μs, and T off at 90 μs.

The application of the fused deposition modeling (FDM) additive manufacturing process has increased in the production of functional parts across all industries. FDM is also being introduced for industrial tooling and fixture applications due to its capabilities in building free-form and complex shapes that are otherwise challenging to manufacture by conventional methods. However, there is not yet a comprehensive understanding of how the FDM process parameters impact the mechanical behavior of engineered products, energy consumption, and other physical properties for different material stocks. Acquiring this information is quite a complex task, given the large variety of possible combinations of materials–additive manufacturing machines–slicing software process parameters. In this study, the knowledge gap is filled by using the Taguchi L27 orthogonal array design of experiments to evaluate the impact of five notable FDM process parameters: infill density, infill pattern, layer thickness, print speed, and shell thickness on energy consumption, production time, part weight, dimensional accuracy, hardness, and tensile strength. Signal-to-noise (S/N) ratio analysis and analysis of variance (ANOVA) were performed on the experimental data to quantify the parameters’ main effects on the responses and establish an optimal combination for the FDM process. The novelty of this work is the simultaneous evaluation of the effects of the FDM process parameters on the quality performances because most studies have considered one or two of the performances alone. The study opens an opportunity for multiobjective function optimization of the FDM process that can be used to effectively minimize resource consumption and production time while maximizing the mechanical and physical characteristics to fit the design requirements of FDM-manufactured products.

The low carbon footprint, biodegradability, interesting mechanical properties, and relatively low price are considered some of the reasons for the increased interest in polylactic acid-based (PLA-based) filaments supplied with natural fillers. However, it is essential to recognize that incorporating natural fillers into virgin PLA significantly impacts the printability of the resulting blends. The complex inter-relationship between process, structure, and properties in the context of fused deposition modeling (FDM)-manufactured biocomposites is still not fully understood, which thus often results in decreased reliability of this technology in the context of biocomposites, decreased accuracy, and the increased presence of defects in the manufactured biocomposite samples. In light of these considerations, this study aims to identify the optimal processing parameters for the FDM manufacturing process involving wood-filled PLA biocomposites. This study presents an optimization approach consisting of Grey Relational Analysis in conjunction with the Taguchi orthogonal array. The optimization process has identified the combination of a scanning speed of 70 mm/s, a layer height of 0.1 mm, and a printing temperature of 220 °C as the most optimal, resulting in the highly satisfactory combination of good dimensional accuracy (Dx = 20.115 mm, Dy = 20.556 mm, and Dz = 20.220 mm) and low presence of voids (1.673%). The experimentally determined Grey Relational Grade of the specimen manufactured with the optimized set of process parameters (0.782) was in good agreement with the predicted value (0. 754), substantiating the validity of the optimization process. Additionally, the research compared the efficacy of optimization between the integrated multiparametric method and the conventional monoparametric strategy. The multiparametric method, which combines Grey Relational Analysis with the Taguchi orthogonal array, exhibited superior performance. Although the monoparametric optimization strategy yielded specimens with favorable values for the targeted properties, the analysis of the remaining characteristics uncovered unsatisfactory results. This highlights the potential drawbacks of relying on a singular optimization approach.

In this paper, by using the Hamming distance, we establish a relation between quantum error-correcting codes ((N,K,d+1))s and orthogonal arrays with orthogonal partitions. Therefore, this is a generalization of the relation between quantum error-correcting codes ((N,1,d+1))s and irredundant orthogonal arrays. This relation is used for the construction of pure quantum error-correcting codes. As applications of this method, numerous infinite families of optimal quantum codes can be constructed explicitly such as ((3,s,2))s for all si≥3, ((4,s2,2))s for all si≥5, ((5,s,3))s for all si≥4, ((6,s2,3))s for all si≥5, ((7,s3,3))s for all si≥7, ((8,s2,4))s for all si≥9, ((9,s3,4))s for all si≥11, ((9,s,5))s for all si≥9, ((10,s2,5))s for all si≥11, ((11,s,6))s for all si≥11, and ((12,s2,6))s for all si≥13, where s=s1⋯sn and s1,…,sn are all prime powers. The advantages of our approach over existing methods lie in the facts that these results are not just existence results, but constructive results, the codes constructed are pure, and each basis state of these codes has far less terms. Moreover, the above method developed can be extended to construction of quantum error-correcting codes over mixed alphabets.

By using difference schemes, orthogonal partitions and a replacement method, some new methods to construct pure quantum error-correcting codes are provided from orthogonal arrays. As an application of these methods, we construct several infinite series of quantum error-correcting codes including some optimal ones. Compared with the existing binary quantum codes, more new codes can be constructed, which have a lower number of terms (i.e., the number of computational basis states) for each of their basis states.