Natural fibres have good weight-to-strength ratio which has made it a material of interest for scientists and engineers. However, the major drawback for outdoor application of natural fibres is its hydrophilic nature. In this study, attempt was made to render bamboo fibre hydrophobic through acetylation with acetic anhydride at room temperature. The functional water absorption properties were studied and the acetylation parameters, such as chemical dosage and acetylation time, were optimised. Taguchi Orthogonal Array was used for the experimental design. Based on the Taguchi design, a regression equation was generated which served as an objective function for Genetic Algorithm. Acetylation reduced the percentage water absorption of Bambusa Vulgaris fibre from 196.4% in un-acetylated fibre down to 45% in acetylated fibres within the feasible design space. The optimal parameter setting generated with genetic algorithm is 15% acetic acid concentration, 50minutes of time soaked in acetic acid, 5% acetic anhydride concentration and 30 minutes time soaked in acetic anhydride. Under the optimum condition, the percentage water absorption was 44%. A confirmation experiment validated the effectiveness of the Genetic Algorithm result.
Variability in production output, low quality, wastes, and downtimes are serious production problems which manufacturers of alkyd resin product are facing and it invariably affect manufacturers' economic performance and the nation economic growth which are often caused by differences in process temperatures and length of the resin. There is a strong incentive in controlling the end of the batch product property values so as to minimize the variability in product quality. This study seeks to investigate the relationship among variables capable of affecting the production process output of rubber seed oil based alkyd resin. A random survey of relevant literature was conducted to gather relevant information required that are capable of causing a dysfunction in the manufacturing process of rubber seed oil based alkyd resin for use in anti-corrosion paint application. The sensitivity and versatile applicability of opinion discrimination analysis as an off-line tool for dealing with these types of problems was apt. Our result showed that there is a strong relationship between temperature, catalyst, absence of catalyst, length of resin, acidic content, water resistance which can be manipulated to appreciably reduce product degradation and control process variability. Moreover, we showed that opinion discrimination analysis modelling tool can be used to determine the need to understand production process approach for alkyd resin. The study has ably demonstrated that opinion discrimination analytical modelling tool is very effective in fault diagnosis.
Bottlenecks in the refineries lead to the disruption of refinery operations which result in production loss and time wastage. Nigerian refineries are four and they have not been able to work optimally as they have failed to produce up to their installed capacity. A lot of factors are contributing to this and are known as bottlenecks. This study was taken so as to identify those bottlenecks in the refineries with a view of making them known so that actions can be taken to tackle them and get Nigerian Refineries move from their pariah states to a welcome state. Kendall’s Coefficient of Concordance (K.C.C) and Principal Component Analysis (P.C.A) which are tools in factor analysis were employed. The K.C.C helped in ranking the identified variables according to their order of importance while the PCA helped to achieve parsimony through factor reduction. The results obtained revealed that the experts ranking of the thirty two scale items were in agreement at an alpha level of 0.01 and the computed coefficient of concordance was 0.51which is substantial. The thirty two scale items were able to be reduced into mere five clusters by PCA. A lone variable cluster which was labeled creatively ‘Government interference’ came up trump and account for most of the challenges being experienced in the Refineries. Other clusters labeled creatively were Eclectic issues, organizational management, Supply Chain Architecture and Personnel Management. The import of this is that government interference needs to be removed if refineries are to work optimally and the remaining four clusters should also be looked at in order to tackle these bottlenecks.
Liquidus temperature is regarded as the minimum temperature required for an alloy to completely transform into the liquid state. Uncontrolled temperature leads to excessive heat generated in the material which create wider heat affected zone, alters the microstructure of the material and also induce residual stresses in the material. Optimizing this process is one sure way of producing a quality weld. In this study, the application of expert systems such as response surface method to optimize the liquidus temperature was pursued. The central composite design matrix was employed to collect data from the sets of experiments. The specimen was made from mild steel plates and welded with the tungsten inert gas process. The result of the response surface method shows that current has a very strong influence on the liquidus temperature. The model for optimizing liquidus temperature has a P-value < 0.0001. The model developed had a very high noise to signal ratio (S/N). Finally, the numerical solution obtained shows that a current of 130Amp, a voltage of 20.94volts, and a speed of 0.48m/min produced a result with liquidus temperature of 1365.05oC.
The design for manufacturing of granulating machines to produce fertilizer granules in small scale using locally available materials is often challenging and this results in low fertilizer usage among Nigerian farmers when compared with the world’s average usage. A lot of factors are associated with chemical fertilizer granulating machine, and it is necessary to examine and understand the interplay among these factors. This study weighs up a number of variables that relates with the design and usage of chemical fertilizer granulating machine and offers increased insight and awareness about their insidiousness. The study employed a survey approach, using the Rensis Likert’s attitudinal scale, to generate respondents’ data matrix that was analyzed with Principal Component Analysis (PCA), and which was facilitated by statistiXL software. Kendall’s Coefficient of Concordance (KCC) was used to rank the thirty two (32) identified variables and PCA was thereafter deployed to ascertain the degree of interplay among the variables. Results obtained by KCC suggested that judges ranking were consistent as there was sufficient evidence to reject the null hypothesis Also, PCA was indicating parsimony in data reduction from 32 variables to mere five. The result established five principal factors creatively labeled Miscellany Components, Technical Considerations, Granulation Efficiency, Agricultural National policy and Biophysical Elements. The most influential variable by its factor loading of 0.894 is Agricultural National policy. A gamut of variables which seem to affect chemical fertilizer granulating machine has been examined. This has helped in discerning similarities in dissimilarities.
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