Modeling and Optimization of Modern Machining Processes

Rao, R. Venkata

doi:10.1007/978-0-85729-015-1_3

Cited by 21 publications

(10 citation statements)

References 233 publications

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“…For instance, pure tabu search uses only one solution, ignoring some promising areas of the search space, and as a result, they may not find the optimal solution. Genetic Algorithm gives near optimal solution for complex problems [11]. GA as well as IA requires several parameters [12].…”

Section: Literature Reviewmentioning

confidence: 99%

“…In addition, there is no provision for selecting the best members from each generation [14]. It is therefore necessary to use nontraditional optimization algorithm, which is robust and gives the correct solution for complex problems [11]. This paper discusses the possibility of reducing the total tool travel time in drilling operations on printed circuit board by implementing modifications in the recently developed Shuffled Frog Leaping algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

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Determination of optimal tool path in drilling operation using Modified Shuffled Frog Leaping Algorithm

Dalavi

Pawar²,

Singh

2020

IJEM

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Applications like boilerplates, food-industry processing separator, printed circuit boards, drum and trammel screens, etc. consists of a matrix of a large number of holes. The primary issue involved in hole-making operations is a tool travel time. It is often necessary to find the optimal sequence of operations so that the total processing cost of hole-making operations can be minimized. In this work, therefore an attempt is made to reduce the total tool travel of holemaking operations by applying a relatively new optimization algorithm known as modified shuffled frog leaping for determining the optimal sequence of operations. Modification is made in the existing shuffled frog-leaping algorithm by introducing three parameters with their positive values to widen the search capability of existing algorithms. A case study of the printed circuit board is considered in this work to demonstrate the proposed approach. Obtained results of optimization using modified shuffled frog leaping algorithm are compared with those obtained using particle swarm optimization, firefly algorithm and shortest path search algorithm.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Determination of optimal tool path in drilling operation using Modified Shuffled Frog Leaping Algorithm

Dalavi

Pawar²,

Singh

2020

IJEM

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“…Most commonly used advanced optimization techniques are the implementation for genetic algorithm in manufacturing optimization. Genetic algorithm (GA) gives near optimal solution for complex problems (Rao, 2011) and it requires more parameters (Elbeltagi et al, 2005). In ACO algorithm, convergence is slow due to pheromone evaporation and it tends to use more CPU time (Elbeltagi et al, 2005).…”

Section: Fig 1 Image Showing Various Tool Combinations Required To mentioning

confidence: 99%

“…Immune based evolutionary approach requires more parameters. Hence it is necessary to use non-traditional optimization algorithm, which gives correct solution for complex problems (Rao, 2011). From literature it is found that recently developed optimization algorithm known as PSO could be used due to its simplicity, easy implementation and high convergence rate (Coello et al, 2011).…”

Section: Fig 1 Image Showing Various Tool Combinations Required To mentioning

confidence: 99%

Optimization of hole-making operations for injection mould using particle swarm optimization algorithm

Dalavi¹,

Pawar²,

Singh³

2015

10.5267/j.ijiec

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Optimization of hole-making operations plays a crucial role in which tool travel and tool switch scheduling are the two major issues. Industrial applications such as moulds, dies, engine block etc. consist of large number of holes having different diameters, depths and surface finish. This results into to a large number of machining operations like drilling, reaming or tapping to achieve the final size of individual hole. Optimal sequence of operations and associated cutting speeds, which reduce the overall processing cost of these hole-making operations are essential to reach desirable products. In order to achieve this, an attempt is made by developing an effective methodology. An example of the injection mould is considered to demonstrate the proposed approach. The optimization of this example is carried out using recently developed particle swarm optimization (PSO) algorithm. The results obtained using PSO are compared with those obtained using tabu search method. It is observed that results obtained using PSO are slightly better than those obtained using tabu search method.

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“…In developed countries, the machining process expenditure contributes approximately 5% of the total GDP while, in the US alone, it contributes approximately $250 B per year [4]. The manufacturing industries strive to achieve either a minimum cost of production or a maximum production rate, or an optimum combination of both, along with better product quality in machining [5]. In a competitive global manufacturing environment, it is necessary for every manufacturing company to optimize the machining parameters with respect to the manufacturing system's performance indicators in order to increase the productivity, decrease cost and produce parts according to design specifications.…”

Section: Introduction and Related Researchmentioning

confidence: 99%

Towards a Generic Framework for the Performance Evaluation of Manufacturing Strategy: An Innovative Approach

Adane

Nicolescu

2018

JMMP

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To be competitive in a manufacturing environment by providing optimal performance in terms of cost-effectiveness and swiftness of system changes, there is a need for flexible production systems based on a well-defined strategy. Companies are steadily looking for methodology to evaluate, improve and update the performance of manufacturing systems for processing operations. Implementation of an adequate strategy for these systems' flexibility requires a deep understanding of the intricate interactions between the machining process parameters and the manufacturing system's operational parameters. This paper proposes a framework/generic model for one of the most common metal cutting operations-the boring process of an engine block machining system. A system dynamics modelling approach is presented for modelling the structure of machining system parameters of the boring process, key performance parameters and their intrinsic relationships. The model is based on a case study performed in a company manufacturing engine blocks for heavy vehicles. The approach could allow for performance evaluation of an engine block manufacturing system condition. The presented model enables a basis for other similar processes and industries producing discrete parts.

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Modeling and Optimization of Modern Machining Processes

Cited by 21 publications

References 233 publications

Determination of optimal tool path in drilling operation using Modified Shuffled Frog Leaping Algorithm

Determination of optimal tool path in drilling operation using Modified Shuffled Frog Leaping Algorithm

Optimization of hole-making operations for injection mould using particle swarm optimization algorithm

Towards a Generic Framework for the Performance Evaluation of Manufacturing Strategy: An Innovative Approach

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