Material selection for microelectronic heat sinks: An application of the Ashby approach

This paper focuses on optimal materials selection for microelectronic heat sinks to maximize the thermal, mechanical and electronic response based on electro-thermal heat transfer analysis using the Ashby approach. In this work, material indices have been developed for a number of properties of heat sinks supported by materials selection tables/graphs. It is found that aluminum based alloys/metals perform better than other available materials for microelectronic heat sinks.     

Multi-objective material selection for wind turbine blade and tower: Ashby’s approach

The world today is continuously striving towards carbon neutral clean energy technology. Hence, renewable energy sources like wind power system is increasingly receiving the attention of mankind. Energy production is now no more the sole criterion to be considered when installing new megawatt (MW) range of turbines. Rather some important design parameters like structural rigidity, cost effectiveness, life cycle impact, and, above all, reduced mass come into the scenario from new installation point of view. Accordingly, these issues are followed up in this article from wind turbine design perspective. The study, at the outset, aims to establish blade and tower material selection indices on the basis of inherent structural constraints and potential design objectives. Next, it highlights entire blade and tower material selection aspects for small and large scale horizontal axis wind turbines, both for onshore and offshore application. Finally, it distinguishes advanced blade and tower materials in agreement with multiple constraint, compound objective based design optimization procedure. Findings from the study can be deployed to harness massive scale wind energy from structurally more promising, economically more competitive and environmentally more clean and green turbines.     

Material selection for thin-film solar cells using multiple attribute decision making approach

This paper presents a material selection approach for selecting absorbent layer material for thin-film solar cells (TFSCs) using multiple attribute decision making (MADM) approach. In this paper, different possible materials for absorbent layer and their properties like band gap, absorption coefficient, diffusion length, thermodynamic compatibility and recombination velocity is taken into consideration and MADM approach is applied to select the best material for thin-film solar cells. It is observed that Copper Indium Gallium Diselinide (CIGS) is the best material for the absorbent layer in thin-film solar cells out of all possible candidates. It was observed that the proposed result is in accordance with the experimental findings thus justifying the validity of the proposed study.     

Material selection for femoral component of total knee replacement using comprehensive VIKOR

The increasing trend of total knee replacement (TKR) revision surgery, which is associated with aseptic loosening, makes it a challenging research subject. The concern of loosening can be partially improved by selecting the optimal materials for TKR components. Therefore, this paper considers selection of the best material among the set of alternatives for femoral component of TKR through the multi-criteria decision making approach. The comprehensive VIKOR method was used to select the optimum material, and a systematic technique for sensitivity analysis of weights was introduced to find more reliable results. The obtained ranking order suggested the use of new materials over the existing ones. Porous and dense NiTi shape memory alloys were ranked first and second respectively.     

Supplier selection using fuzzy association rules mining approach

Owing to ill-structured, dynamic environments and the presence of multiple decision-makers with conflicting viewpoints, comprehension, analysis and support of the supplier evaluation process becomes more and more difficult. Moreover, with the complexities of issues such as the role of leadership, the influence of group formation, and analysis of disagreements, it cannot be predictable that there will ever exist a solution to cope with all imprecise, multi-criteria/multi-actor situations. A fuzzy association rules-based approach may be suited for the judgement of human subjects. In this paper, we develop an approach based on Fuzzy Association Rule Mining to support the decision makers by enhancing the flexibility in making decisions for evaluating suppliers with both tangibles and intangibles attributes. Also, by checking the fuzzy classification rules, the goal of knowledge acquisition can be achieved in a framework in which assessments could be established without constraints, and consequently checked and compared in several details. The efficacy and intricacy of the proposed model for finding fuzzy association rules from the database for supplier assessment is demonstrated with the help of numerical examples.     

Robot selection using a fuzzy regression-based decision-making approach

Industrial robots, which enable manufacturing firms to produce high-quality products in a cost-effective manner, are important components of advanced manufacturing technologies. The performance of industrial robots is determined by multiple and conflicting criteria that have to be simultaneously considered in a robust selection study. In this study, a decision model based on fuzzy linear regression is presented for industrial robot selection. Fuzzy linear regression provides an alternative approach to statistical regression for modelling situations where the relationships are vague or the data set cannot satisfy the assumptions of statistical regression. The results obtained by employing fuzzy linear regression are compared with those of earlier studies applying different analytical methods to a previously reported robot selection problem.     

Materials selection for hot stamped automotive body parts: An application of the Ashby approach based on the strain hardening exponent and stacking fault energy of materials

Complex stamping operations are becoming widespread in the automotive industry to produce vehicle body parts with adequate mechanical strength and reduced wall thickness. The need for weight reduction drives the development of new metallic materials capable of achieving a good balance between formability and mechanical properties. Advanced high strength steels play a major role in this scenario. The aim of this work was to develop a materials selection strategy for hot stamped automotive body parts using the Ashby approach. The selection process was based on the formability of metallic alloys derived from two fundamentals materials properties, the strain hardening exponent and the stacking fault energy.     

Multidisciplinary approach to materials selection for bipropellant thrusters using ablative and radiative cooling

Reduction of costs is a main consideration in every space mission, and propulsion system is an important subsystem of those missions where orbital maneuvers are considered. Lighter propulsions with higher performance are necessary to reduce the mission costs. Bipropellant propulsions have been widely used in launch vehicles and upper-stages as well as deorbit modules because of better performances in comparison with other propulsion systems. Unfortunately heat transfer and thermal control limit bipropellant propulsion performance and maximum performance cannot be achieved. Well-known cooling methods such as regenerative and film cooling increase the cost using extra equipment and high temperature materials. In this paper, a new approach for cooling is presented based on combined ablative and radiative cooling. Governing equations are derived for two or three layers of thermal protection system (TPS) to optimize the TPS mass. The first layer is used as an ablative layer to control the temperature where the second and third layers are used as an insulator to control the heat fluxes. Proposed cooling method has been applied for two real bipropellant thrusters. According to the results, the presented algorithm can suitably predict the heat fluxes and satisfy the wall temperature constraint. Then, the algorithm has been used to minimize the wall temperatures as low as possible and replace high temperature materials (platinum alloy) with common materials (composite or steel). It is shown that selection of TPS materials affects the TPS mass and Isp simultaneously, but conversely. Best solution should be derived by trading off between structure temperature (cost), Isp (performance), and TPS thicknesses (geometry). Multidisciplinary approach to TPS and structure material selection of a bipropellant thruster is presented for a case study. It has been shown that mass and performance penalties of using TPS are acceptable, considering the advantages of using steel alloy instead of platinum alloy.     

Material selection using PROMETHEE combined with analytic network process under hybrid environment

Material selection involves a great number of attributes, including quantitative and qualitative ones, among which there exist dependences of various degrees, and so belongs to multi-attribute decision making problem (MADM) under hybrid environment in the presence of interdependences. The method of preference ranking organization method for enrichment evaluations (PROMETHEE) combined with analytic network process (ANP) is presented to select the best material for a given application, where ANP is used to identify weights, and PROMETHEE to rank alternatives. Taking the material selection for a journal bearing as example, the decision-making procedure is enunciated, first determining the attributes according to the failure analysis and the requirements of customers, then screening out the feasible solutions, and last fixing the optimal solution, Aluminum bronze, which is in conformity with practice test. Finally, the method of expediting the calculation process is presented developing graphical user interface-based (GUI-based) related software.     

A two-step optimization approach for technology selection

An efficient optimization approach for the technology selection problem is described. Technology selection is a crucial step in the aircraft design process, especially when the performance and econo-mic requirements are not fulfilled for any combination of the configuration design variables. In such a case, the designer must search efficiently within a set of technology options for the optimal combination that achieves the required improvements. When the set of available technologies is large, as is usually the case, a difficult combinatorial optimization problem ensues, resulting in significant time and computational expense. The objective of the new approach is to reduce the computational cost of technology selection by decomposing the process into two smaller sub-problems. The new approach attempts to exploit the structure of the technology compatibility matrix to improve the efficiency of the technology selection process. Results from an application problem are presented and valuable insights and observations are discussed.     

A Lagrangian approach for quantum-mechanical electrostatic analysis of deformable silicon nanostructures

Semiconductor mechanical components of nanoelectromechanical systems (NEMS) typically undergo deformations when subjected to electrostatic forces. Computational analysis of electrostatic NEMS requires an electrostatic analysis to compute the electrostatic forces acting on the nanomechanical structures and a mechanical analysis to compute the deformation of the nanomechanical structures. Typically, the mechanical analysis is performed by a Lagrangian approach using the undeformed position of the structures. However, the electrostatic analysis is performed by using the deformed position of the nanostructures. The electrostatic analysis on the deformed position of the nanostructures requires updating the geometry of the structures during each iteration. In this paper, based on a recently proposed hybrid BIE/Poisson/Schrödinger approach, we propose Lagrangian formulations for the BIE/Poisson/Schrödinger equations and solve the coupled Lagrangian BIE/Poisson/Schrödinger's equations self-consistently using the undeformed position of the semiconductors to compute the charge distributions on the deformed semiconductors. The proposed approach eliminates the requirement of updating the geometry and, consequently, significantly simplifies the procedure of coupled electromechanical analysis of NEMS.     

Maintenance policy selection in manufacturing firms using the fuzzy MCDM approach

In manufacturing firms, there is a critical need for proper maintenance of manufacturing facilities. The maintenance process enhances customer satisfaction and reliability of the products, and increases the profit of the manufacturer. Therefore, a proper maintenance policy selection is a critical issue for manufacturers, as an inefficient maintenance policy affects not only the direct cost of the firm but also the other aspects. In the present study, maintenance policy selection at the level of the firm rather than the equipment level is shown, and for selection various criteria have been identified. The presented work not only provides the best alternatives but also provides an alternative ranking, which facilitates decision-makers in choosing alternatives according to their constraints. These selection criteria are different in nature, as some give a crisp value, whereas others are defined in linguistic terms. To select the appropriate maintenance policy, a distance-based fuzzy multicriteria decision-making (MCDM) approach has been employed. The proposed method provides the means for integrating the economic figure of merit with the strategic performance variables. The MCDM approach is efficient in incorporating data, in the form of linguistic variables, triangular fuzzy numbers, and crisp numbers, into the evaluation process of maintenance policy alternatives. A comprehensive example illustrates the application of the distance-based fuzzy MCDM approach.     

Optimal process plan selection in networked based manufacturing using game-theoretic approach

This paper proposes a scheme for generating optimal process plans for multi jobs in a networked based manufacturing system. Networked manufacturing offers several advantages in the current competitive atmosphere such as reducing short manufacturing cycle time and maintaining the production flexibility, thereby achieving several feasible process plans. An N-person non-co-operative game with complete information is proposed and a mathematical model has been developed to generate the payoff functions. To be part of a game, we divided the game into two sub-games such as games to address sub-game (GASG) and games to solve sub-game (GSSG) which try to interact with each other and achieve the Nash equilibrium (NE). Consequently, a hybrid dynamic-DNA (HD-DNA) based evolutionary algorithm approach has been developed for more effective solutions of the game and also for finding the perfect NE points. The objective of this game is to generate the optimal process plans to minimise the makespan. Finally, three cases having different job complexities are presented to demonstrate the feasibility of the approach. The proposed algorithm is validated and results are analysed to benefit the manufacturer.     

Process parameter selection for optimising weld bead geometry in stainless steel cladding using Taguchi's approach

Abstract

In the present study, the Taguchi method, a tool to design optimisation for quality, is used to find the optimal welding process parameters for cladding of austenitic stainless steel. An orthogonal array, the signal to noise (S/N) ratio, and the analysis of variance (ANOVA) are employed to investigate the effect of process parameters on weld bead characteristics. The present study was conducted by depositing AISI 317L onto an IS : 2062 structural steel substrate by the flux cored arc welding (FCAW) process under the shield of 95%Ar and 5%CO₂ gas mixture. The weld bead parameters are optimised individually (single objective) as well as collectively (multiobjective) to get the desired quality characteristics. The results show that these techniques can be used effectively to control the process parameters in cladding with certain limitations.     

Material selection based on ordinal data

Ranking and choosing the best material is one of most important stages in material selection process. Using linear assignment method, the multi-criteria decision making (MCDM) approach is proposed in decision-making process to rank the materials for a given engineering component with respect to several criteria. The proposed material selection procedure is relatively simple, and can be a useful approach when material selection problem includes qualitative properties or user-interaction aspects. The suggested approach also can be use for quantitative properties. Three examples are included to demonstrate the suggested method. Result of proposed approach showed good agreement with other methods.     

Material selection for the tool holder working under hard milling conditions using different multi criteria decision making methods

Nowadays machining of materials in their hardened state, also called hard machining, is a challenge in production of tools and molds. It has some advantages such as lower process time and lower manufacturing cost when compared to conventional machining. In machining of hard workpiece materials, however, very high stresses act on the tool holder through the cutting tool. These stresses necessitate the tool holder to have some specific properties. Especially in hard milling, the tool holder should have high stiffness and should be able to dissipate the energy generated during interrupted cutting. Material cost of the tool holder is also important since lower costs provide a competitive advantage for manufacturers. The material selection for the tool holder should be conducted considering aforementioned requirements. To tackle the difficulty of the material selection with specific properties from a large number of alternatives, multi-criteria decision-making (MCDM) methods have been used. In this paper a decision model including extended PROMETHEE II (EXPROM2) (preference ranking organization method for enrichment evaluation), TOPSIS (technique for order performance by similarity to ideal solution) and VIKOR (VIšekriterijumsko KOmpromisno Rangiranje) methods were used for the selection of the best material for the tool holder used in hard milling. The criteria weighting was performed by compromised weighting method composed of AHP (analytic hierarchy process) and Entropy methods. The candidate materials were ranked by using these methods and the results obtained by each method were compared. It was confirmed that MCDM methods can be used for the solution of real time material selection problems. Tungsten carbide–cobalt and Fe–5Cr–Mo–V aircraft steel were found as the best materials for the tool holder production. The obtained results are found to be rather satisfactory and can be used in design stage of hard machining operations.     

Adaptive optimal stimulus selection in cognitive models using a model averaging approach

Behaviormetrika - Stimulus selection based on the maximum Fisher information (MFI) principle enables the efficient estimation of participant parameters of cognitive models with elaborated...     

Vendor selection in a modified re-buy situation using a strategy-aligned fuzzy approach

The supplier/vendor selection is a decision-making problem at the strategic management level that involves a semi-structured process. The majority of the existing approaches obtained their optimal solutions without considering their fits with the strategy of the firm. This study utilizes the supplier positioning matrix, modified from the product-process change matrix, to link the capability of suppliers with the requirements of the customers to identify the strategy-aligned criteria for vendor selection in a modified re-buy situation. A fuzzy factor rating system is then used to evaluate the potential vendors based on the type of components required by the customers. In addition, in the proposed model, the final decision-maker is given the authority to synthesize the scores of individual alternatives based on the risks of individual vendors to accommodate the differences among the vendors to the specific environment. An empirical case study is performed to demonstrate the efficacy of the proposed system and to identify the best potential vendor(s) for further negotiation and development. The results of the case study also provide interesting managerial implications.     

A novel mixing method for levitated particles using electrostatic fields

A continuous particle mixing system using electrostatic forces and vibrations was developed. The system consists of two symmetrically arranged devices. The same or different types of charged particles were continuously fed from each device in a dispersed state and mixed instantaneously in the space between devices. When charged particles with opposite polarities were fed from each device by changing the direction of the electric field, the particles were homogeneously mixed. The electric field and particle trajectories were numerically calculated to elucidate the particle-mixing mechanism. Furthermore, the mixing state of the particles was evaluated quantitatively using Shannon entropy.