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This study aims to investigate the relationship between material properties and alloying elements of carbon steels through predictive modeling. Aircraft control cables are usually made of steel materials and subjected to deformation because of the motion of control surfaces such as aileron, rudder, elevator and trailing edge flaps. Investigation of the relationship between material properties and alloying elements would therefore be explored.

This study is focused on the modeling of mechanical properties of carbon steels concerning the content of alloying elements by using response surface methodology with false discovery rate (FDR) correction approach. SAS Institute JMP data analysis software was used to develop response and argument relationships in various carbon steels without including thermomechanical treatment effect. Mechanical properties were considered as tensile strength, yield strength, ductility, and Brinell hardness. Carbon (0.28 Wt.%-0.46 Wt.%) and manganese (0.7 Wt.%-0.9 Wt.%) proportions were gathered from ASM Handbook. Linear regression models were tested for the statistical adequacy by using analysis of variance and statistical significance analysis. A posterior probability, which refers to Benjamini–Hochberg FDR (BH-FDR), was embedded as multiple testing corrections of the t-test p-values.

Predictive modeling of the material properties for aircraft control cables was successfully achieved by using the response surface method with BH-FDR significance level of 0.05.

The effect of statistically developed graphical interactions of alloying elements on the common mechanical properties of such steels would provide prompt comparison to material suppliers and part manufacturers except those subjected to thermomechanical treatment applications.

In this article, a practical design methodology is proposed for discrete sizing optimization of high-rise concrete buildings with a focus on large-scale and real-life structures.

This framework relies on a computationally efficient approximation of the constraint and objective functions using a radial basis function model with a linear tail, also called the combined response surface methodology (RSM) in this article. Considering both the code-stipulated constraints and other construction requirements, three sub-optimization problems were constructed based on the relaxation model of the original problem, and then the structural weight could be automatically minimized under multiple constraints and loading scenarios. After modulization, the obtained results could meet the discretization requirements. By integrating the commercially available ETABS, a dedicated optimization software program with an independent interface was developed and details for practical software development were also presented in this paper.

The proposed framework was used to optimize different high-rise concrete buildings, and case studies showed that material usage could be saved by up to 12.8% compared to the conventional design, and the over-limit constraints could be adjusted, which proved the feasibility and effectiveness.

This methodology can therefore be applied by engineers to explore the optimal distribution of dimensions for high-rise buildings and to reduce material usage for a more sustainable design.

The purpose of this study is to optimize single-bath dyeing process of wool and silk blend, to achieve uniform colour strength for both the fibre after the dyeing process. Due to different absorption characteristics of wool and silk, two-stage dyeing is preferred in the industry. If the fibres are dyed together, the wool fibre becomes darker and the silk fibre becomes lighter after the dyeing process. Solid dyeing effect can be achieved using a single-bath dyeing process.

The dye-acceptor sites in the wool fibre are first blocked using one commercial syntan Mesitol HWS. Then, the syntan-treated wool and silk fibres (80:20 blend ratios) are dyed with Telon Navy AMF dyes in the presence of sodium sulphate. To explore the influence of Syntan, sodium sulphate and the experimental conditions on the dyeing process and to optimize the process, central composite design (CCD) of four factors and three levels was tested.

The design process is optimized using four independent variables: Mesitol HWS concentration, sodium sulphate concentration, pH of dyebath and temperature of dyeing. Three levels of Mesitol HWS concentration (5, 10 and 15 per cent), sodium sulphate concentration (10, 20 and 30 per cent), pH (2.5, 4 and 5.5) and temperature of dyeing (70, 80 and 900°C) were selected for this study. These variables are optimized using response surface regression equation of the ratio of K/S wool and K/S silk. The predicted equation matched well with the experimental data.

This paper proposes the use of one-bath dyeing process of wool and silk blend fabric to reduce the dyeing time, process step and to save water.

The purpose of this paper is to speak about the production of biodiesel from waste cooking oil which serves as an alternate fuel in the absence of conventional fuels such as diesel and petrol. Though much research work was carried out using non-edible crops such as Jatropha and Pongamia, cooking oil utilized in bulk quantity is discarded as a waste. This is reused again as it contains more of esters that when combined with an alcohol in presence of an enzyme as a catalyst yields triglycerides (biodiesel).

The lipase producing strain Rhizopus oryzae and pure enzyme lipase is immobilized and treated with waste cooking oil for the production of FAME. Reaction parameters such as temperature, time, oil to acyl acceptor ratio and enzyme concentration were considered for purified lipase and in the case of Rhizopus oryzae, pH, olive oil concentration and rpm were considered for optimization studies. The response generated through each run were evaluated and analyzed through the central composited design of response surface methodology and thus the optimized reaction conditions were determined.

A high conversion (94.01 percent) was obtained for methanol when compared to methyl acetate (91.11 percent) and ethyl acetate (90.06 percent) through lipase catalyzed reaction at oil to solvent ratio of 1:3, enzyme concentration of 10 percent at 30°C after 24 h. Similarly, for methanol a high conversion (83.76 percent) was obtained at an optimum pH of 5.5, olive oil concentration 25 g/L and 150 rpm using Rhizopus oryzae when compared to methyl acetate (81.09 percent) and ethyl acetate (80.49 percent).

This research work implies that the acyl acceptors methyl acetate and ethyl acetate which are novel solvents for biodiesel production can also be used to obtain high yields as compared with methanol under optimized conditions.

This study considers the five factors of a car rotation system: angle (F1), arm length (F2), toe in and out (F3), width (F4) and length (F5). The purpose of this paper is to fine tune the design so it produces the smoothest response to various rotation angles.

In the case of Ackerman’s principle, the response surface methodology (RSM) was used to analyze data when encountering different quality characteristics at various rotation angles.

In this study, RSM was used to obtain the best factor and the best reaction value for the five factors of a car rotation system.

In this study, the four-wheel steering of a car is taken as an example. When the current wheel is turned, the intersection of the left and right wheels of the front axle falls on the extension line of the rear wheel. In this case, the steering will be the smoothest. In this example, we selected angle (F1), arm length (F2), toe in and out (F3), width (F4) and length (F5) as experimental factors, hoping to satisfy the Ackerman principle.

Traditionally, when dealing with four-wheel steering problems, solutions may be based on past experience or on new information used to formulate R&D plans. In this study, the combination of statistical factors and optimization is used to find the optimal combination of factors and the relationship between factors.

In the past, most literature relied on kinematics to study the car rotation system due to a lack of experimental design and analysis concepts. However, this study aims to achieve the above goals in finding the solution, which can be used to predict reaction values.

In the fast paced PCB industry of today windows of opportunity are short. One needs to be able to find quickly the key variables to a new process or an existing process so that the capability requirement can be met. Guesswork and traditional experimental design approaches will not work. Control charts by themselves will not work. Very large experimental studies will not work. What will work are simple, well defined, statistically designed experiments. This paper is an example of how simple, statistically based experiments were used to reduce haloing on Teflon® circuit boards. The drilling and plating processes using different laminate materials were investigated using Box‐Wilson and Plackett‐Burman experimental designs. Different data analysis techniques such as confidence intervals, scree plots, analysis of variance tables and analysis of means charts were used to determine the true significant (key) variables and the insignificant (non key) variables. An effective experimental study must have a capable measurement system. A method of determining the measurement system capability and improving it for haloing using isoplots is presented. In the end, two economically feasible paths to reduce the haloing problem were found.

Chapter 2 describes how behavioral science research methods that management and marketing scholars apply in studying processes involving decisions and organizational outcomes relate to three principal research objectives: fulfilling generality of findings, achieving accuracy of process actions and outcomes, and capturing complexity of nuances and conditions. The chapter's unique contribution is in advocating and describing the possibilities of researchers replacing Thorngate's (1976) “postulate of commensurate complexity” — it is impossible for a theory of social behavior to be simultaneously general, accurate, and simple and as a result organizational theorists inevitably have to make tradeoffs in their theory development — with a new postulate of disproportionate achievement. This new postulate proposes the possibilities and advocates the building and testing of useful process models that achieve all three principal research objectives. Rather than assuming the stance that a researcher must make tradeoffs that permit achieving any two, but not all three, principal research objectives as, Weick (1979) clock analogy shows, this chapter advocates embracing a property space (a three-dimensional box rather than a clock) view of research objectives and research methods. Tradeoffs need not be made; having-your-cake-and-eating-it-too is possible. The chapter includes a brief review of principal criticisms that case study researchers often express of surveys of respondents using fixed-point surveys. Likewise, the chapter reviews principal criticisms of case study research studies that researchers who favor the use of fixed-point surveys express.

This paper aims to study the corrosion inhibition of mild steel in 2.5 M HCl solution by kiwi juice at different temperatures, inhibitor concentration and immersion times.

Box–Wilson experimental design is used for runs distribution and the corrosion rate values are evaluated by weight loss technique.

Corrosion rate increased with temperature according to Arrhenius equation, and the inhibitor adsorbed according to Langmuir adsorption isotherm. Second-order polynomial model is used for data fitting. The optimum conditions were estimated with maximum inhibitor efficiency of 96.1 per cent. Fourier transform infrared analysis showed that the peaks correspond to phenols, and quercitine is the main component. Microstructural, hardness and theoretical quantum studies are also performed.

This is one of the first steps in the direction of understanding the corrosion control problems from different views. Kinetics, surface morphology, optimization and mathematical views are taken in to account.

Studies the feasibility of using the metamodelling technique for the performance analysis of a just‐in‐time manufacturing system. The data for the analysis are generated by a Siman simulation model. Develops a regression metamodel following an R‐IV fractional factorial design. Results show that, of the 15 variables considered, only assembly time, kanban capacity, and the interaction effect between demand and kanban capacity are statistically significant. Performs cross‐validation. Finds the results of the metamodel developed to supplement the simulation model to be accurate.