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This paper aims to focus on calculating the number of layers of composite laminates required to take the applied load made up of graphite/epoxy (AS4/3501-6) which can be used in many industrial applications. Optimization for minimization of weight by variation in the mechanical properties is possible by using different combinations of fiber angle, number of plies and their stacking sequence.

Lots of research studies have been put forth by aerospace industry experts to improve the performance of aircraft wings with weight constraints. The orthotropic nature of the laminated composites and their ability to characterize as per various performance requirements of aerospace industry make them the most suitable material. This leads to necessity of implementing most appropriate optimization technique for selecting appropriate parameter sets and material configurations.

In this work, exhaustive enumeration algorithm has been applied for weight minimization of fiber laminated composite beam subjected to two different loading conditions by computing overall possible stacking sequences and material properties using classical laminate theory. This combinatorial type optimization technique enumerates all possible solutions with an assurance of getting global optimum solution. Stacking sequences are filtered through Tsai-Wu failure criteria.

Finally, through the outcome of this optimization framework, eight different combinations of stacking sequences and 24-ply symmetric layup have been obtained. Furthermore, this 24-ply layup weighing 0.468 kg has been validated using finite element solver for given boundary conditions. Interlaminar stresses at top and bottom of the optimized ply layup were validated with Autodesk’s Helius composites solver.

This paper demonstrates the use of genetic algorithms (GAs) for size optimization of trusses. The concept of rebirthing is shown to be considerably effective for problems involving continuous design variables. Some benchmark examples are studied involving 4‐bar, 10‐bar, 64‐bar, 200‐bar and 940‐bar two‐dimensional trusses. Both continuous and discrete variables are considered.

The purpose of this paper is to examine the progress of social development in terms of social development index (SDI) of India in the pre- and post-reforms period.

This study used the methodology of Ray (1989, 2008) for the construction of composite index for social development, i.e. SDI. The study also used the ordinary least squares method of regression analysis for checking the impact of development expenditure, non-development expenditure and Per Capita Net National Product (PCNNP) on the SDI value.

The results show an increasing trend in social development. The findings of this study also suggest that there is a sharp increase in the index over the period between 2002/2003 and 2010/2011. But in the remaining period, sluggish improvement in social development has been observed. Though there has been growth in the social sector, but it is not much heartening and perhaps more efforts need to be done in the social sector in India. The results also exhibit that development expenditure, non-development expenditure and PCNNP are significantly affecting the SDI value.

The study suggests that the government should focus more on social sector programs and there is an urgent need to increase development and non-development expenditures to improve the overall social condition of the country.

The work is different in terms of number of development variables from the already existing literature in India. The author constructed the SDI by using the weighted sum of 12 transformed social variables which has not been studied previously.

Trusses constitute a fertile field to demonstrate the application of optimization techniques because of the possibility of several different configurations. Using such techniques allows the search for designs that minimize the use of material to safely comply with the imposed loads. Truss optimization can be classified into three categories: cross-section, shape, and topology. The purpose of this paper is to present a numerical and experimental study developed to minimize the weight of aluminum trusses, taking both the cross-sectional dimensions of the elements and the nodal coordinates as design variables.

Initially, several numerical computer simulations were performed with an optimization program developed by combining the displacement method and a simulated annealing optimization method. Subsequently, two aluminum trusses were selected and built in order to validate the numerical results obtained.

Experimental tests verified the excellent performance of the optimized model.

In addition, it was concluded that significant savings could be obtained from the application of the proposed formulation.

The purpose of this paper is to consider a nonlinear problem of minimizing the cost of providing reliable systems. The authors assume that the system consists of several components in series, and for each such component, the cost of the component increases exponentially with its reliability.

In order to solve this nonlinear optimization problem, the authors propose two approaches. The first approach is based on the concept of adjusting the reliability of a pair of components to minimize the cost of the system. The authors call this procedure as reliability adjustment routine (RAR). Proofs of optimality and convergence for the proposed model are also provided. The second approach solves the problem by using a Lagrangian multiplier. A procedure is developed to obtain the maximum step size to achieve the desired optimal solution in minimum iterations. Proposed approaches are efficient and give exact solutions.

Proposed methods enable a decision maker to allocate reliability to the components in series while minimizing the total cost of the system. The developed procedures are illustrated using a numerical example. Although an exponential relationship between the component cost and reliability is assumed, this can be extended to various other nonlinear distributions.

This cost optimization problem, subject to system component reliability values, assumes the near practical nonlinear pattern of cost vs reliability. Such problems are complex to solve. The authors provide a unique approach called RAR to solve such convoluted problems. The authors also provide an approach to solve such problems by using a Lagrangian multiplier method. Various proofs have been worked out to substantiate the work.

The purpose of this paper is to introduce the notion of a social fabric (SF) in which the expression of knowledge sources (KS) in cultural algorithms (CA) can be distributed through the population. The SF influence function is applied to the solution of selected complex engineering problems and it is shown that different parameter combinations for the SF influence function can affect the rate of solution. This enhanced approach is compared with previous approaches.

KS are allowed to influence individuals through a network. From a theoretical perspective, individuals in the real world are viewed as participating in a variety of different networks. Several layers of such networks can be supported within a population. The interplay of these various network computations is designated as the “social fabric.” Using this new influence function, when an individual is to be modified, one KS is selected to perform the modification at each generation. The selection process is done via weaving the SF, hence changing the number of individuals that follow a certain KS.

Simulation experiments show that the choice of influence function has a great impact on the problem‐solving phase. For some problems, a social network is not necessary to produce frequent convergence to an optimum. On the other hand, it is observed that the social network can help to focus search by allowing a KS to influence groups of individuals within a network rather than single unrelated individuals. The new approach shows a more focused convergence to optimal values in complex engineering problems with numerous constraints. Also, it is suggested that a SF configuration can be robust in the sense that a configuration that works well for one problem can also perform well in a more complex but unrelated problem. This suggests that a configuration can be evolved to solve suites of problems.

The introduced approach is interesting for the optimization of problems of a non‐linear complex nature.

This paper deals with structural shape optimization of vibrating prismatic shells and folded plates. The finite strip method is used to determine the natural frequencies and modal shapes based on Mindlin‐Reissner shell theory which allows for transverse shear deformation and rotatory inertia effects. An automated optimization procedure is adopted which integrates finite strip analysis, parametric cubic spline geometry definition, automatic mesh generation, sensitivity analysis and mathematical programming methods. The objective is to maximize the fundamental frequency by changing thickness and shape design variables defining the cross‐section of the structure, with a constraint that the total volume of the structure remains constant. A series of examples is presented to highlight various features of the optimization procedure as well as the accuracy and efficiency of finite strip method.

The Sustainable Lean Six Sigma (SLSS) adoption approach, advancements in Internet technologies and the use of Industry4.0 technologies has resulted in faster customer need fulfilment. The Industry4.0 technologies have resulted in a new paradigm where strategic and operational decisions are in favour of profitability and long-term viability. The purpose of this study is to identify Industry4.0-SLSS practices and sustainable supply chain performance metrics, as well as to develop a framework for decision-makers and managers to make supply chains more sustainable.

The 33 Industry4.0-SLSS practices and 24 performance metrics associated with the sustainable supply chain are shortlisted based on extensive literature review and expert opinion. The Pythagorean Fuzzy Analytical Hierarchy Process (PF-AHP) approach is used to evaluate the weights of Industry4.0-SLSS practices after collecting expert panel opinions. The Weighted Aggregated Sum Product Assessment (WASPAS) methodology used these weights to rank performance metrics.

According to the results of PF-AHP, “Product development competencies (PDC)” are first in the class of major criteria, followed by “Advanced technological competencies (ATC)” second, “Organisational management competencies (OMC)” third, “Personnel and sustainable competencies (PSC)” fourth and “Soft Computing competencies (SCC)” fifth. The performance metric “Frequency of NPD” was ranked first by the WASPAS method.

The proposed paradigm helps practitioners to comprehend Industry4.0 technology and SLSS practices well. The identified practices have the potential to boost the sustainability and supply chain's performance. Organizational effectiveness will benefit from practices that promote a sustainable supply chain and the use of developing technology. Managers can evaluate performance using performance metrics that have been prioritized.

The present study is one of the unique attempts to establish a framework for enhancing the performance of the sustainable supply chain. The idea of establishing Industry4.0-SLSS practices and performance measures is the authors' original contribution.

The purpose of this paper is to describe a computer‐aided design/manufacturing (CAD/CAM) system for fabricating facial prostheses.

The CAD/CAM system can be used for fabricating custom‐made facial prostheses with symmetrical or asymmetrical features. This system integrates non‐contact structured light scanning, reverse engineering and rapid prototyping manufacturing technology. Fringe projection based on the combination of the phase‐shift and grey‐code methods is used for data collection. A robust approach is proposed to calculate the mid‐plane of the human face without any knowledge of the centroid position or the principal axis in data processing.

Results show that the proposed method increases the fabrication accuracy and reduces the operating time. Patients were satisfied with the rehabilitation results as the custom‐made facial prostheses fitted them well.

This study improves the fabrication accuracy of facial prostheses. Three‐dimensional data of the facial surface of a patient needing a facial prosthesis were obtained with almost no harm to his body; after a series of robust processes, a precise and suitable aesthetic facial prosthesis was fabricated.

This system has bright prospects for clinical application because of its advantages over other methods in terms of speed, accuracy, safety, cost, etc.

The purpose of this paper is to present an approach for structural weight minimization under von Mises stress constraints and self-weight loading based on the topological derivative method. Although self-weight loading topology has been the subject of intense research, mainly compliance minimization has been addressed.

The resulting minimization problem is solved with the help of the topological derivative method, which allows the development of efficient and robust topology optimization algorithms. Then, the derived result is used together with a level-set domain representation method to devise a topology design algorithm.

Numerical examples are presented, showing the effectiveness of the proposed approach in solving a structural topology optimization problem under self-weight loading and stress constraint. When the self-weight loading is dominant, the presence of the regularizing term in the formulation is crucial for the design process.

The novelty of this research work lies in the use of a regularized formulation to deal with the presence of the self-weight loading combined with a penalization function to treat the von Mises stress constraint.