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Fixture layout design is concerned with immobilization of the workpiece (engine mount bracket) during machining such that the workpiece elastic deformation is reduced. The fixture holds the workpiece through the positioning of fixturing elements that causes the workpiece elastic deformation, in turn, leads to the form and dimensional errors and increased machining cost. The fixture layout has the major impact on the machining accuracy and is the function of the fixturing position. The position of the fixturing elements, key aspects, needed to be optimized to reduce the workpiece elastic deformation. The purpose of this study is to evaluate the optimized fixture layout for the machining of the engine mount bracket.

In this research work, using the finite element method (FEM), a model is developed in the MATLAB for the fixture-workpiece system so that the workpiece elastic deformation is determined. The artificial neural network (ANN) is used to develop an empirical model. The results of deformation obtained for different fixture layouts from FEM are used to train the ANN and finally the empirical model is developed. The model capable of predicting the deformation is embedded to the evolutionary optimization techniques, capable of finding local and global optima, to optimize the fixture layouts and to find the robust one.

For efficient optimization of the fixture layout parameters to obtain the least possible deformation, ant colony algorithm (ACA) and artificial bee colony algorithm (ABCA) are used and the results of deformation obtained from both the optimization techniques are compared for the best results.

A MATLAB-based FEM technique is able to provide solutions when the repeated modeling and simulations required i.e. modeling of fixture layouts (500 layouts) for every variation in the parameters requires individual modeling and simulation for the output requirement in any FEM-based software’s (ANSYS, ABACUS). This difficulty is reduced in this research. So that the MATLAB-based FEM modeling, simulation and optimization is carried out to determine the solutions for the optimized fixture layout to reach least deformation.

Many a time the practicability of the machining/mechanical operations are difficult to perform costly and time-consuming when more number of experimentations are required. To sort out the difficulties the computer-based automated solution techniques are highly required. Such kind of research over this study is presented for the readers.

A MATLAB-based FEM modeling and simulation technique is used to obtain the fixture layout optimization. ANN-based empirical model is developed for the fixture layout deformation that creates a hypothesis for the fixture layout system. ACA and ABCA are used for optimizing the fixture layout parameters and are compared for the best algorithm suited for the fixture layout system.

The purpose of this research paper is to find the optimum parameters, namely, the sliding speed, applied load and percentage of silicon carbide particles (SiCp), under which AlSi10Mg/SiCp composites experience minimum wear.

Wear rate (WR) of AlSi10Mg, AlSi10Mg/10SiC and AlSi10Mg/20SiC was measured using pin-on-disk equipment according to ASTM G99 standards. Response surface method was used to design the experiments, model and analyze the tribological behaviour. Tests were conducted as per Box–Beheken design of experiments. The wear mechanisms were observed using scanning electron microscope. Genetic algorithm was used to find the optimum parameters for minimum WR.

Wear mechanisms underwent changes with variation in applied load, sliding speed and per cent SiCp. An optimum wear condition was obtained when the process parameters, namely, the sliding speed, applied load and percentage of SiCp, were at 4 m/s, 10 N and 20 per cent, respectively. Combined GA-RSM approach was successfully used to predict the minimum WR condition of AlSi10Mg/SiCp composites with an accuracy of 94 per cent.

The tribological behaviour of AlSi10Mg/SiCp composites has been investigated in detail. A statistical WR model is proposed. This paper provides an optimum condition to design the tribo contact between steel and AlSi10Mg/SiCp composites.

The paper aims to describe the Taguchi design method-based abrasive wear modeling of in situ AlB2 flake reinforced Al-4Cu matrix alloy composites.

The abrasive wear behaviors of the composite samples were investigated using pin-on-disk method where the samples slid against different sizes of SiC abrasive grits under various testing conditions. The orthogonal array, signal-to-noise (S/N) ratio and analysis of variance were used to study the optimal testing parameters on composite samples.

The weight loss of composites decreased with increasing grit size and percentage reinforcement and increased with increasing sliding speed. The optimum test condition, at which the minimum weight loss is obtained, has been determined to be A3B3C1 levels of the control factors. Deviations between the actual and the predicted S/N ratios for abrasive weight losses are negligibly small with 99.5 per cent confidence level.

This paper fulfils an identification of Taguchi method-based abrasive wear behavior of AlB2/Al-4Cu metal matrix composites produced by squeeze casting under various testing conditions.

Aluminium and its alloys are the most preferred material in aerospace and automotive industries because of their high strength-to-weight ratio. However, these alloys are found to be low wear resistance. Hence, the incorporation of ceramic particles with the aluminium alloy may be enhanced the mechanical and tribological properties. The purpose of this study is to optimize the specific wear rate and friction coefficient of titanium dioxide (TiO₂) reinforced AA7075 matrix composites. The four wear control factors are considered, i.e. reinforcement (Wt.%), applied load (N), sliding velocity (m/s) and sliding distance (m).

The composites were fabricated through stir casting route with varying weight percentages (0, 5, 10 and 15 Wt.%) of TiO₂ particulates. The mechanical properties of the composites were studied. The specific wear rate and friction coefficient of the newly prepared composites was determined by using a pin-on-disc apparatus under dry sliding conditions. Experiments were planned as per Taguchi’s L16 orthogonal design. Signal-to-noise ratio analysis was used to find the optimal combination of parameters.

The mechanical properties such as yield strength, tensile strength and hardness of the composites significantly improved with the addition of TiO₂ particles. The analysis of variance result shows that the applied load and reinforcement Wt.% are the most influencing parameters on specific wear rate and friction coefficient during dry sliding conditions. The scanning electron microscope morphology of the worn surface shows that TiO₂ particles protect the matrix from more removal of material at all conditions.

This paper provides a solution for optimal parameters on specific wear rate and friction coefficient of aluminium matrix composites (AMCs) using Taguchi methodology. The obtained results are useful in improving the wear resistance of the AA7075-TiO₂ composites.

Since, wear is the one of the most commonly encountered industrial problems leading to frequent replacement of components there is a need to develop metal matrix composites (MMCs) for achieving better wear properties. The purpose of this paper is to fabricate aluminum MMCs to improve the dry sliding wear characteristics. An effective multi-response optimization approach called the principal component analysis (PCA) was used to identify the sets of optimal parameters in dry sliding wear process.

The present work investigates the dry sliding wear behavior of graphite reinforced aluminum composites produced by the molten metal mixing method by means of a pin-on-disc type wear set up. Dry sliding wear tests were carried on graphite reinforced MMCs and its matrix alloy sliding against a steel counter face. Different contact stress, reinforcement percentage, sliding distance and sliding velocity were selected as the control variables and the response selected was wear volume loss (WVL) and coefficient of friction (COF) to evaluate the dry sliding performance. An L25 orthogonal array was employed for the experimental design. Optimization of dry sliding performance of the graphite reinforced MMCs was performed using PCA.

Based on the PCA, the optimum level parameters for overall principal component (PC) of WVL and COF have been identified. Moreover, analysis of variance was performed to know the impact of individual factors on overall PC of WVL and COF. The results indicated that the reinforcement percentage was found to be most effective factor among the other control parameters on dry sliding wear followed by sliding distance, sliding velocity and contact stress. Finally the wear surface morphology of the composites has been investigated using scanning electron microscopy.

Various manufacturing techniques are available for processing of MMCs. Each technique has its own advantages and disadvantages. In particular, some techniques are significantly expensive compared to others. Generally the manufacturer prefers the low cost technique. Therefore stir casting technique which was used in this paper for manufacturing of Aluminum MMCs is the best alternative for processing of MMCs in the present commercial sectors. Since the most important criteria of a dry sliding wear behavior is to provide lower WVL and COF, this study has intended to prove the application of PCA technique for solving multi objective optimization problem in wear applications like piston rings, piston rods, cylinder heads and brake rotors, etc.

Application of multi-response optimization technique for evaluation of tribological characteristics for Aluminum MMCs made up of graphite particulates is a first-of-its-kind approach in literature. Hence PCA method can be successfully used for multi-response optimization of dry sliding wear process.

This research aims to describe the influence of weight per cent of graphite (Gr), applied load and sliding speed on the wear behavior of aluminum (Al) alloy A356 reinforced with silicon carbide (SiC) (10 Wt.%) and Gr (1 Wt.% and 5 Wt.%) particles. The objective is to analyze the effect of the aforementioned parameters on a specific wear rate.

These hybrid composites are obtained by means of the compo-casting process. Tribological analyses were conducted on block-on-disc tribometer at three different loads (10, 20 and 30 N) and three different sliding speeds (0.25, 0.5 and 1 m/s), at the sliding distance of 900 m, in dry sliding wear conditions. Optimization of the tribological behavior was conducted via the Taguchi method, and ANOVA was used for the analysis of the specific wear rate. Confirmation tests are used to foresee and check the experimental results. Examined samples were analyzed via a scanning electron microscope (SEM). Regression models for predicting specific wear rate were developed with Taguchi and ANN (artificial neural network) methods.

The biggest impact on value of specific wear rate has the load (43.006%), while the impact of Wt.% Gr (31.514%) was less. After comparison of the results, i.e. regression models, for predicting the specific wear rate, it was observed that ANN was more efficient than the Taguchi method. The specific wear rate of Al alloy A356 with SiC (10 Wt.%) and Gr (1 Wt.% and 5 Wt.%) decreases with a decrease in the load and weight per cent of Gr-reinforcing material, as well as with a decrease in sliding speed.

The results obtained in this paper using the Taguchi method and the ANN method are useful for improving and further investigating the wear behavior of the SiC- and Gr-reinforced Al alloy A356.

Dynamic economic and emission dispatch (DEED) aims to optimally set the active power generation with constraints in a power system, which should target minimum operation cost and at the same time minimize the pollution in terms of emission when the load dynamically changes hour to hour. The purpose of this study is to achieve optimal economic and emission dispatch of an electrical system with a renewable generation mix, consisting of 3-unit thermal, 2-unit wind and 2-unit solar generators for dynamic load variation in a day. An improved version of a simple, easy to understand and popular optimization algorithm particle swarm optimization (PSO) referred to as a constriction factor-based particle swarm optimization (CFBPSO) algorithm is deployed to get optimal solution as compared to PSO, modified PSO and red deer algorithm (RDA).

Different model with and without wind and solar power generating systems; with valve point effect is analyzed. The thermal generating system (TGs) are the major green house gaseous emission producers on earth. To take up this ecological issue in addition to economic operation cost, the wind and solar energy sources are integrated with the thermal system in a phased manner for electrical power generation and optimized for dynamic load variation. This DEED being a multi-objective optimization (MO) has contradictory objectives of fuel cost and emission. To get the finest combination of the two objectives and to get a non-dominated solution the fuzzy decision-making (FDM) method is used herein, the MO problem is solved by a single objective function, including min-max price penalty factor on emission in the total cost to treat as cost. Further, the weight factor accumulation (WFA) technique normalizes the pair of objectives into a single objective by giving each objective a weightage. The weightage is decided by the FDM approach in a systematic manner from a set of non-dominated solutions. Here, the CFBPSO algorithm is applied to lessen the total generation cost and emission of the thermal power meeting the load dynamically.

The efficacy of the contribution of stochastic wind and solar power generation with the TGs in the dropping of net fuel cost and emission in a day for dynamic load vis-à-vis the case with TGs is established.

Cost and emission are conflicting objectives and can be handled carefully by weight factors and penalty factors to find out the best solution.

The proposed methodology and its strategy are very useful for thermal power plants incorporating diverse sources of generations. As the execution time is very less, practical implementation can be possible.

As the cheaper generation schedule is obtained with respect to time, cost and emission are minimized, a huge revenue can be saved over the passage of time, and therefore it has a societal impact.

In this work, the WFA with the FDM method is used to facilitate CFBPSO to decipher this DEED multi-objective problem. The results reveal the competence of the projected proposal to satisfy the dynamic load demand and to diminish the combined cost in contrast to the PSO algorithm, modified PSO algorithm and a newly developed meta-heuristic algorithm RDA in a similar system.

Aluminium is the most preferred material in engineering structural components because of its excellent properties. Furthermore, the properties of aluminium may be enhanced through metal matrix composites and an in-depth investigation on the evolved properties is needed in view of metallurgical, mechanical and tribological aspects. The purpose of this study is to explore the effect of TiC addition on the tribological behavior of aluminium composites.

Aluminium metal matrix composites at different weight percentage of titanium carbide were produced through powder metallurgy. Produced composites were subjected to sliding wear test under dry condition through Taguchi’s L9 orthogonal design.

Optimal process condition to achieve the minimum wear rate was identified though the main effect plot. Sliding velocity was identified as the most dominating factor in the wear resistance.

The production of components with improved properties is promoted efficiently and economically by synthesizing the composite via powder metallurgy.

Though the investigations on the wear behavior of aluminium composites are analyzed, reinforcement types and the mode of fabrication have their significance in the metallurgical and mechanical properties. Thus, the produced component needs an in-detail study on the property evolution.

The fiber orientation is considered one of the important parameters that have an effect on the characteristics of composites. This paper aims to investigate the effect of fiber orientation on the abrasive wear of the glass-epoxy (G-E) composites with different silicon carbide (SiC) filler weights (Wt.%).

The wear rate of glass fiber reinforced with angle-ply 0º, ±45º and 90º is discussed. The G-E composites with different weights of SiC filler at angle ±45º are considered. Hand lay-up technique was adopted for specimen preparation. The influence of effective parameters such as filler Wt. %, normal load, abrasive size and abrading distance on the wear rate was presented and discussed.

Experimental tests including pin on disk, micro-hardness and scanning electron microscope were carried out to investigate the composite characteristics.

The experimental results showed that the resistance wear was superior in case of ±45º fiber orientations. A validation of the experimental results using Taguchi approach to verify the optimal wear rate parameters was presented.

Research on the demographic characteristics of top management team (TMT) on e-commerce adoption has really advanced. Although some of such studies factored location factors as e-commerce adoption drivers, rare attempts have been made to unravel if the differences in the demographic composition of TMT and the rate of adoption may be explained by the differences in the firm’s geographical location. Therefore, the purpose of this paper is to bridge this knowledge gap by proposing a framework that conceives and measures geographical location as a contextual variable between e-commerce adoption and TMT composition.

Data were generated from the opinions of owners/managers of 226 SMEs drawn purposefully from registered SMEs in five industries located in three geo-political zones of Nigeria. Two cities (a state capital and a commercial nerve centre) were studied and a four-step hierarchical regression (spanning factor-loading) was used to test the hypotheses.

Evidence from the study shows that the hypothesized relationships between demographic factors and e-commerce adoption (main/direct effects) were statistically significant (supporting H1-H4). The two moderators (physical infrastructures and industrial specialization) that explained location factors were equally statistically significant in moderating the relationship between the demographic composition of TMT and e-commerce adoption.

Sampling the opinions of SMEs in some industries of three geo-political zones of Nigeria limits the power of generalization. Therefore, extended data and measures are required to replicate the study in order to build external validity and reliability, and possibly theories. Further, some errors seem unavoidable in the course of converting the data through SPSS procedure just as all the measures used appear subjective and prone to common method bias. Other demographic and location factors not captured in the study may be handled by future studies.

The work will be of benefit to the academia and practitioners in terms of showing how location factors dictate the relationship between the demographic composition of top management and e-commerce adoption. The paper raises pointers that stimulate future research and advised policy-makers on even or near-even distribution of infrastructural facilities.