Intelligent tools selection for roughing and finishing in machining of Inconel 718

Escamilla-Salazar, Indira G.; Torres-Treviño, Luis M.; González-Ortíz, Bernardo; Praga-Alejo, Rolando J.; González, David

doi:10.1007/s00170-016-9005-6

Cited by 6 publications

(2 citation statements)

References 18 publications

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“…Many scientific research works dealt with the optimization process, for example in the machining of aircraft structural parts with complex structures [4], optimization of high-speed machining [5], optimizing the feed rate in milling to improve machining efficiency [6], and optimization of machining of rigid parts with complex configurations [7]. The common goal of these researchers is to optimize a machining performance [8][9][10][11]. Some other efforts at developing machining models for optimization of the machining process include artificial intelligence [12].…”

Section: General Contextmentioning

confidence: 99%

Optimization of the 2 ½ D Processing Method of Complex Parts, through a Predictive Algorithm for Controlling the Geometric Shape Deviations Resulting from Processing

et al. 2020

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This article intends to define a new methodology that allows the processing of complex surfaces in space through processing cycles, in parallel superposed planes—the variant known as generic processing in 2 ½ D—but with predictable control over the deviation from the geometric form of the surface to be processed. The novel methodology consists of identifying the optimal distances between the working planes and the corresponding successive positions so that the deviations from the resulting geometric form fall within the prescribed limits. It is also envisaged that the method will provide facilities in terms of the possibilities for evaluation of deviations from the given form of the surface, and keeping them under control by the stage of elaboration of the numerical control programs. The new optimization is designed to determine the maximum distances between successive processing planes and their position in space, depending on the spatial shape of the surface to be processed. Thus, the aim is to obtain a small number of processing planes with a favorable effect on productivity, but under conditions that respect the tolerances of the surface or the profile, a restriction that otherwise has a negative effect on the same process.

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Section: General Contextmentioning

confidence: 99%

Optimization of the 2 ½ D Processing Method of Complex Parts, through a Predictive Algorithm for Controlling the Geometric Shape Deviations Resulting from Processing

et al. 2020

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“…A variety of technical and management problems with different characteristics, constraints, and objectives exist in the products manufacturing, including flow shop scheduling [1][2][3], material selection [4][5][6], tool selection [7,8], process planning [9,10], and resource allocation [11,12]. Due to the complexity of the general NP-hard (non-deterministic polynomial-time hard), most of these problems have to be solved by specific iterative search algorithms.…”

Section: Introductionmentioning

confidence: 99%

An evolutionary algorithm recommendation method with a case study in flow shop scheduling

Zuo

Wang

Laili

et al. 2020

Int J Adv Manuf Technol

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Numerous optimization problems exist in the product and process design, engineering, and planning, as well as production management, and the evolutionary algorithms (EAs) have been proved to be effective optimization methods to solve these problems. However, how to choose the appropriate EA is one of the key issues due to the variety of EAs and lack of experience. Under this circumstance, firstly, a novel EA recommendation system framework is designed and proposed, and the implementation of the EA recommendation method is also described in this paper. Then, computational experiments are implemented to demonstrate the effectiveness and accuracy of the proposed method on the basis of 14 typical benchmark problems and 20 classical EAs. Finally, a case study regarding permutation flow shop scheduling is also carried out to test its effectiveness and accuracy. The proposed recommendation method provides a new way to select the appropriate EAs scientifically and reasonably to solve a given optimization problem.

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NC process information mining based optimization method of roughing tool sequence selection for pocket features

Xu,

Zhang,

Liang

et al. 2024

Advanced Engineering Informatics

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Intelligent tools selection for roughing and finishing in machining of Inconel 718

Cited by 6 publications

References 18 publications

Optimization of the 2 ½ D Processing Method of Complex Parts, through a Predictive Algorithm for Controlling the Geometric Shape Deviations Resulting from Processing

Optimization of the 2 ½ D Processing Method of Complex Parts, through a Predictive Algorithm for Controlling the Geometric Shape Deviations Resulting from Processing

An evolutionary algorithm recommendation method with a case study in flow shop scheduling

NC process information mining based optimization method of roughing tool sequence selection for pocket features

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