Parametric Optimization of Turning Process Using Evolutionary Optimization Techniques—A Review (2000–2016)

Rana, Parthiv B.; Patel, Jigar; Lalwani, D.I.

doi:10.1007/978-981-13-1595-4_13

Cited by 11 publications

(6 citation statements)

References 52 publications

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“…Regression analysis was used. As regards solving the mathematical models of machining parameters optimisation, literature supplies a series of models [3][4][5][6][7][8][9][10][14][15][16][17].…”

Section: Discussionmentioning

confidence: 99%

“…Then, many works have approached the machining parameters optimisation. Within the mathematical models regarding machining parameters optimisation there are found the times and costs related to the tool change [3][4][5][6][7][8][9][10][11]. The tool replacement time [6] can be expressed as follows:…”

Section: Literature Reviewmentioning

confidence: 99%

“…For the correct solving of the problem, the objective function must be connected to a set of constraints. The tool life T is most often integrated into optimisation mathematical models through the equation [3][4][5][6][7][8][9][10][11]:…”

Section: Literature Reviewmentioning

confidence: 99%

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2021

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As known, all industrial companies from all over the world are aiming at the main objective, as to maximize their profit. In order to reach this objective, companies use certain strategies, principles and techniques. An important strategy regards the optimisation of the available resources, including material, financial, human and informational resources. Companies must also pay an important attention to their technological processes that include certain machining processes for obtaining the products to be delivered to the market place. The present paper is focused on the optimisation of the cutting tool changing regime, which represents an important part of the lead time, in order to make the machining process more efficient. The core of the paper regards the optimisation of multi-tool life and machining parameters so that the time of tool change is diminished. The paper also includes two case studies that refers to drilling process using multi-tool machining.

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Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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“…Therefore, GA is a well-established technique with multiple variants. GA are also the most common option in other fields were metaheuristic algorithms are used for optimisation, such as sustainable building design (Evins, 2013;Nguyen et al, 2014) or industrial processes (Rana et al, 2019). However, some authors have found that other, more recent meta-heuristic methods may offer a better performance.…”

Section: Figure 2: Frequency For Optimization Methodsmentioning

confidence: 99%

A review of modelling and optimisation methods applied to railways energy consumption

Fernández

Sanchís

Piqueras

et al. 2019

Journal of Cleaner Production

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“…The objective function refers to minimizing unit production costs. Rana et al [34] presented a review of research related to the optimization of machining using evolutionary optimization techniques (years 2000-2006). Sofuoglu et al [35] propose a method for solving heuristic optimization problems to determine optimum parameters while minimizing cost functions.…”

Section: Literature Reviewmentioning

confidence: 99%

Machining Parameters Optimization Based on Objective Function Linearization

2022

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Manufacturing process optimization is an ever-actual goal. Within this goal, machining parameters optimization is a very important task. Machining parameters strongly influence the manufacturing costs, process productivity and piece quality. Literature presents a series of optimization methods. The results supplied by these methods are comparable and it is difficult to establish which method is the best. For machining parameters optimization, this paper proposes a novel, simple and efficient method, without additional costs related to new software packages. This approach is based on linear mathematical programming. The optimization mathematical models are, however, nonlinear. Therefore, mathematical model linearization is required. The major and difficult problem is the linearization of the objective function. This represents the key element of the proposed optimization method. In this respect, the paper proposes an original mathematical procedure for calculating the part of the objective function that refers to the analytical integration of the tool life into the model. This calculus procedure was transposed into an original software tool. For demonstrating the validity of the method, a comparison is presented among the results obtained by certain optimization techniques. It results that the proposed method is simple and as good as those presented by the literature.

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Parametric Optimization of Turning Process Using Evolutionary Optimization Techniques—A Review (2000–2016)

Cited by 11 publications

References 52 publications

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A review of modelling and optimisation methods applied to railways energy consumption

Machining Parameters Optimization Based on Objective Function Linearization

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