Adaptive Gaussian Quantum based PSO and TSA optimization for parametric Optimizaiton of Toughned glass on Toughening machine

Abstract

Usually, toughened glasses are used for safer road transport and general purposes. This is because toughened glasses are difficult to break since these types of glasses are four to five times stronger than ordinary glasses. Meanwhile, the compressive strength of the glass needs to be enhanced and tensile strength needs to be minimized to enhance the toughening glass quality. In addition to this, both cutting and machining parameters need to be optimized and validate with the production rate and the company product thus optimizing the production cost. In this paper, the machining and cutting parameters as well as the production cost are optimized using a novel technique named Adaptive Gaussian Quantum behaved Particle Swarm Optimization algorithm and Tunicate Swarm algorithm (AGQPSOA-TS) approach. Here, two different algorithms namely Adaptive Gaussian Quantum behaved Particle Swarm Optimization algorithm and Tunicate Swarm algorithm are integrated and proposed a novel technique named AGQPSOA-TS algorithm. Finally, the experiments are carried out with the aim of enhancing the compressive strength and minimizing the tensile strength of the toughened glass. According to the Indian standards, the thickness and dimensions of the glass workpiece are taken as 5 mm and 200mmx200mm respectively. The comparative evaluations are conducted for compressive strength, tensile strength as well as production cost to depict the efficiency of the proposed system.