Overview of NSGA-II for Optimizing Machining Process Parameters

This chapter introduces teaching-learning-based optimization (TLBO) algorithm and its elitist and non-dominated sorting multiobjective versions. Two examples of unconstrained and constrained benchmark functions and an example of a multiobjective constrained problem are presented to demonstrate the procedural steps of the algorithm.

Teaching-Learning-Based Optimization Algorithm

Thorough literature review of various modern machining processes is presented in this paper. The main focus is kept on the optimization aspects of various parameters of the modern machining processes and hence only such research works are included in this work in which the use of advanced optimization techniques were involved. The review period considered is from the year 2006 to 2012. Various modern machining processes considered in this work are electric discharge machining, abrasive jet machining, ultrasonic machining, electrochemical machining, laser beam machining, micro-machining, nano-finishing and various hybrid and modified versions of these processes. The review work on such a large scale was not attempted earlier by considering many processes at a time, and hence, this review work may become the ready information at one place and it may be very useful to the subsequent researchers to decide their direction of research.

Optimization of modern machining processes using advanced optimization techniques: a review

Enhanced transport phenomena are essential for chemical reactions in continuous-flow microstructured equipment with transitional flow regimes. The geometry and cross-section of the smallest channel determines the flow regime, pressure loss, and energy dissipation in the microchannel. Mixing and heat transfer are greatly influenced by the flow regime. Controlled reaction conditions lead to enhanced safety, especially for harsh reaction conditions at elevated temperatures or high concentrations. Safety and operational limits of these regimes are presented for optimized process intensification, with examples of nitration and organometallic reactions.

Harsh Reaction Conditions in Continuous‐Flow Microreactors for Pharmaceutical Production

Electrical discharge machining (EDM) is a process for shaping hard metals and forming deep and complex shaped holes by arc erosion in all types of electro conductive materials. In the present work, the effectiveness of the EDM process with tungsten carbide and cobalt composites is evaluated in terms of the material removal rate and the surface finish quality of the workpiece produced. The objective of this research is to study the influence of operating parameters of EDM such as pulse current, pulse on time, electrode rotation and flushing pressure on material removal rate and surface roughness. The experimental results are used to develop the statistical models based on second order polynomial equations for the different process characteristics. The non-dominated sorting genetic algorithm (NSGA-II) has been used to optimize the processing conditions. A non-dominated solution set has been obtained and reported.

Optimization of electrical discharge machining characteristics of WC/Co composites using non-dominated sorting genetic algorithm (NSGA-II)

Tungsten carbide/cobalt (WC/Co) cemented carbide is one of the important composite materials that are used in the manufacture of cutting tools, dies, and other special tools. It has high ha...

Influence of process parameters on electric discharge machining of WC/30%Co composites:

Effect of Electrical Discharge Machining on strength and reliability of WC–30%Co composite

Tungsten carbide/Cobalt (WC/Co) cemented carbide is one of the important composite materials which is used for manufacturing cutting tools, dies and other special tools. WC/Co cemented carbide produced through powder metallurgy is subjected to Electro Discharge Machining. The process characteristics such as Material Removal Rate, Tool Wear Rate and Surface Roughness are studied by varying speed of electrode rotation, pulse current, pulse on time and dielectric flushing pressure. The experimental results are used to develop non-linear regression models for the process characteristics. A non-linear Goal programming based on Genetic Algorithm is used to optimise the processing conditions.

D. Kanagarajan

Papers

Optimization of electrical discharge machining characteristics of WC/Co composites using non-dominated sorting genetic algorithm (NSGA-II)

Influence of process parameters on electric discharge machining of WC/30%Co composites:

Effect of Electrical Discharge Machining on strength and reliability of WC–30%Co composite

Application of goal programming technique for Electro Discharge Machining (EDM) characteristics of cemented carbide (WC/Co)