Electrical Discharge Coating by Copper-Tungsten Composite Electrode Prepared by Powder Metallurgy Route

Electrical discharge machining (EDM), a thermo-mechanical machining process, is used in producing complicated intrinsic cavity in difficult-to- machine materials with excellent surface finish. One of the major disadvantage of EDM process is the tool wear, which can be used advantageously for coating purpose. Coating is a unique method of EDM process by the use of electrode prepared via powder metallurgy route. Copper and tungsten powders in weight percentage of 30 and 70 respectively are used for the preparation of the tool electrode by varying the PM process parameters like compaction pressure and sintering temperature. The substrate on which coating is made is chosen as AISI 1040 stainless steel with EDM oil as the dielectric fluid. During coating, influence of parameters like discharge current, duty cycle and pulse-on-time on material deposition rate, tool wear rate and radial under deposition are studied. To find out the best parametric combination Grey Relational Analysis method combined with Harmony Search algorithm has been employed.

Optimization of Process Parameters in Plasma Arc Cutting Applying Genetic Algorithm and Fuzzy Logic

Plasma Arc Cutting (PAC) process is a widely used machining process in several fabrication, construction and repair work applications. Considering gas pressure, arc current and torch height as the inputs and among all possible outputs, in the present work Material Removal Rate and Surface Roughness would be considered as factors that determines the quality, machining time and machining cost. In order to reduce the number of experiments Design of Experiments (DOE) would be carried out. In later stages applications of Genetic Algorithm (GA) and Fuzzy Logic would be used for Optimization of process parameters in Plasma Arc Cutting (PAC). The output obtained would be minimized and maximized for Surface Roughness and Material Removal Rate respectively using Genetic Algorithm (GA) and Fuzzy Logic.

Decision Making Under Deep Uncertainty With Fuzzy Algorithm in Framework of Multi-Model Approach

Task of soft computing for decision support in field of risk management is analyzed in this chapter. Multi-model approach is described. Interrelations between models, remote sensing data and forecasting are described. Method of water quality assessment using satellite observation is described. Method is based on analysis of spectral reflectance of aquifers. Correlations between reflectance and pollutions are quantified. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality is making based on fuzzy algorithm using limited set of uncertain parameters. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated. Conclusions concerned soft computing in risk management are proposed and discussed. It was demonstrated, that basing on spatially distributed measurement data, proposed approach allows to calculate risk parameters with resolution close to observations.

Novel Approaches to Prediction of a Future Number of Failures Based on Previous In-Service Inspections

In this chapter, we present novel approaches to predictions of the number of failures that will be observed in a future inspection of a sample of units, based only on the results of the previous in-service inspections of the same sample. The failure-time of such units is modeled with a distribution from a two-parameter Weibull distribution. The different cases of parametric uncertainty are considered. The pivotal quantity averaging approach proposed here for constructing point prediction and simple prediction limits emphasizes pivotal quantities relevant for eliminating unknown parameters from the problems and represents a special case of the method of invariant embedding of sample statistics into a performance index applicable whenever the statistical problem is invariant under a group of transformations, which acts transitively on the parameter space. For illustration, a numerical example is given.

Applying Multi-Objective Optimization Algorithms to Mechanical Engineering

In today's scenarios, the utilization of simulation and optimization in the field of designing is achieving wider recognition in the various zones of commerce as the computational competences of computers upsurge day by day. The result is that the uses for numerical optimization have increased tremendously. Design process in engineering is a distinct practice of solving the problems where a group of recurrently indistinct objectives has to be well-adjusted deprived of violating any given circumstances. Consequently, it seems quite ordinary to consider a design process as an optimization process. The design process could be articulated as to allocate values to the system parameters to confirm that the state variables and the characteristics are as suitable as possible through an inclusive range of operating and environmental variables. This is a complex multi-objective optimization problem (MOOP). This chapter discusses the use of MOO algorithms in mechanical engineering.

Analyzing Sustainable Food Supply Chain Management Challenges in India

The demand of food is increasing day by day, innovative agricultural practices and sustainable food supply chain management (SFSCM) has gained an emergent importance. Food industries across the globe mainly focus on the manufacturing of their own products to achieve sustainability. The importance of sustainable food supply chain management is to overcome the wastage in food manufacturing industries. In the present research, we identified eleven challenges in the SFSCM on the basis of literature review and expert opinion. The approach is an integration of fuzzy with DEMATEL which can be used for dividing the challenges into cause and effect group. Fuzzy DEMATEL method has continuously been used for the analysis of challenges and is the novel approach for decision making. Thus, this method can be implemented in many fields including automobiles, food industries, retail market etc. From the fuzzy DEMATEL results, it can be confirmed that the Safety and Security is one of the most influencing challenge and has the strongest association with other challenges.

Nature-Inspired Metaheuristic Approach for Multi-Objective Optimization During WEDM Process

In this research paper Wire-Electric Discharge Machining (WEDM) is applied to machine AISI-D3 material in order to measure the performance of multi-objective responses like high material removal rate and low roughness. This contradictory objective is accomplished by the control parameters like Pulse on Time (Ton), Pulse off Time (Toff), Wire Feed (W/Feed) and Wire Tension (W/Ten) employing brass wire. Here the orthogonal array is used to developed 625 parametric combinations. The optimization of the contradictory responses is carried out in a metaheuristic environment. Artificial Neural Network is employed to train and validate the experimental result. Primarily the individual responses are optimized by employing Firefly algorithm (FA). This is followed by a multi-objective optimization through Genetic algorithm (GA) approach. As the results obtained through GA infer a domain of solutions, therefore Grey Relation Analysis (GRA) is applied where the weights are considered through Fuzzy set theory to ascertain the best parametric combination amongst the set of feasible alternatives.

Summability Techniques and Their Applications in Soft Computing

Summability methods are a useful tool in dealing with the problems in the soft computing like in filtering of the signals and for stabilizing the systems. Signals can be in the form of various types of series (Infinite Series, Fourier series, etc.) and hence, summability theory is applicable in finding the error of approximation and degree of approximation of such signals. In this chapter, the authors gave an introductory discussion on summability theory and approximation of the signals. Further, they explained about the stability of the frequency response of the system. Also, they used the Fourier approximation in the soft computing models (multilayer perceptrons; radial basis function (RBF) or regularization networks, and fuzzy logic models) and found the output data of requirement.

Selection of Appropriate Turbulance Model in Fuel Bundle of Nuclear Energy

This chapter presents an overview of various types of turbulence model and their effect on thermal-hydraulic characteristics of nuclear fuel bundle, both past and present using Computational Fluid Dynamic (CFD) approach. It includes the mathematical definition related to fuel bundle in nuclear energy. The various types of geometrical arrangement like Pressurized Water Reactor (PWR), Boiling Water Reactor (BWR), etc., are stressed. The solution procedures that are applicable to the various reactor types are introduced here and presented in detail for different types of turbulence models. Study of these characteristics enables the student to appreciate the effect of the different types of turbulence models on turbulent mixing and related phenomena. Finally, recommendations of turbulence model for rod bundle are finalized. The inclusion of related references provides a starting point for the interested reader / researchers /industrialists.

Optimal Designs by Means of Genetic Algorithms

With the advancement in contemporary computational and modeling skills, engineering design completely depends upon on variety of computer modeling and simulation tools to hasten the design cycles and decrease the overall budget. The most difficult design problem will include various design parameters along with the tables. Finding out the design space and ultimate solutions to those problems are still biggest challenges for the area of complex systems. This chapter is all about suggesting the use of Genetic Algorithms to enhance maximum engineering design problems. The chapter recommended that Genetic Algorithms are highly useful to increase the High-Performance Areas for Engineering Design. This chapter is established to use Genetic Algorithms to large number of design areas and delivered a comprehensive conversation on the use, scope and its applications in mechanical engineering.