Optimization of Tool Travel Path in A Multiple Holes Cutting Process By Genetic Algorithm

Outfitting is a critical stage in the shipbuilding process. Within the outfitting, the construction of pipe systems is a phase that has a significant effect on time and cost. While cutting the pipes required for the pipe systems in shipyards, the cutting process is usually performed randomly. This can result in large amounts of trim losses. In this paper, we present an approach to minimize these losses. With the proposed method it is aimed to base the pipe cutting process on a specific systematic. To solve this problem, Genetic Algorithms (GA), which gives successful results in solving many problems in the literature, have been used. Different types of genetic operators have been used to investigate the search space of the problem well. The results obtained have proven the effectiveness of the proposed approach.

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Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm

Applied Mathematics & Information Sciences ◽

10.12785/amis/070145 ◽

2013 ◽

Vol 7 (1) ◽

pp. 363-370 ◽

Cited By ~ 9

Author(s):

Y. Nukman ◽

M. Hassan ◽

M. Harizam

Keyword(s):

Neural Network ◽

Genetic Algorithm ◽

Artificial Neural Network ◽

Co2 Laser ◽

Prediction Error ◽

Laser Cutting ◽

Cutting Process ◽

Artificial Neural

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Identification of Tool Wear Condition Based on Generalized Fractal Dimensions and BP Neural Network Optimized with Genetic Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.318.71 ◽

2013 ◽

Vol 318 ◽

pp. 71-75 ◽

Cited By ~ 2

Author(s):

Kai Feng Zhang ◽

Hui Qun Yuan ◽

Peng Nie

Keyword(s):

Neural Network ◽

Genetic Algorithm ◽

Tool Wear ◽

Bp Neural Network ◽

Fractal Theory ◽

Fractal Dimensions ◽

Cutting Process ◽

Generalized Dimensions ◽

Ae Signals ◽

Wear Condition

Based on multi-fractal theory, the generalized fractal dimensions of acoustic emission (AE) signals during cutting process were calculated using improved box-counting method. The generalized dimension spectrums of AE signals for different tool wear condition were gained, and the relation between tool wear condition and generalized dimensions was analyzed. Together with cutting process parameters, the generalized fractal dimensions were taken as the input vectors of BP neural network after normalization. The initial weight and bias values of BP neural network which was used to classify the tool wear condition were optimized with Genetic Algorithm. The test results showed that the method can be used effectively for the identification of tool wear condition.

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Experimental investigation on precision machining of multiple holes by WEDM on Aluminium-6061 using genetic algorithm

Multiscale and Multidisciplinary Modeling Experiments and Design ◽

10.1007/s41939-019-00062-1 ◽

2019 ◽

Vol 3 (2) ◽

pp. 77-88 ◽

Cited By ~ 1

Author(s):

Jaya Kishore Sunkara ◽

Siva Kumar Kayam ◽

Gopala Krishna Monduru ◽

Kumar Babu Padaga

Keyword(s):

Genetic Algorithm ◽

Experimental Investigation ◽

Precision Machining ◽

Multiple Holes

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Genetic Algorithm Applied to Investigate Cutting Process Parameters Influence on Workpiece Price Formation

Materials and Manufacturing Processes ◽

10.1080/10426914.2010.512817 ◽

2011 ◽

Vol 26 (3) ◽

pp. 550-557 ◽

Cited By ~ 8

Author(s):

André Felipe Henriques Librantz ◽

Nivaldo Lemos Coppini ◽

Elesandro Antônio Baptista ◽

Sidnei Alves de Araújo ◽

Aparecida de Fátima Castello Rosa

Keyword(s):

Genetic Algorithm ◽

Process Parameters ◽

Cutting Process ◽

Price Formation

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Waste reduction in Rectangular Figure Cutting using a Genetic Algorithm

Ciencia y tecnología de buques ◽

10.25043/19098642.138 ◽

2016 ◽

Vol 10 (19) ◽

pp. 19

Author(s):

Juan C. Rodríguez Noriega ◽

Jairo R. Coronado-Hernández ◽

Sergio Leottau

Keyword(s):

Genetic Algorithm ◽

Selection Process ◽

Waste Reduction ◽

Cutting Process ◽

Real Case ◽

Object Based

This paper introduces a genetic algorithm (GA) to minimize the waste produced during the cutting process of rectangular figures on a sheet. The chromosomes for solution codification use an object-based representation. It has the following operator: Partially Mapped Crossover (PMX), mutation based in double interchange (2-opt), and the elitism strategy for the selection process. The proposed algorithm was applied in a real case situation problem, where the numbers of items were 55 pieces. The result of this implementation was a reduction of the waste as a result of the decrease in the number of sheets used in the cutting process and at the same time an effective employment of the used area.

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Scanning Electron Microscopy of Fish Scales as an Adjunctive Aid in Speciation

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100095236 ◽

1972 ◽

Vol 30 ◽

pp. 394-395

Author(s):

Edward D. DeLamater ◽

Walter R. Courtenay ◽

Cecil Whitaker

Keyword(s):

Electron Microscopy ◽

Scanning Electron Microscopy ◽

Lateral Line ◽

Species Differences ◽

Fish Scale ◽

Fish Scales ◽

Anterior Border ◽

The University ◽

Multiple Holes ◽

Scanning Electron

Comparative scanning electron microscopy studies of fish scales of different orders, families, genera and species within genera have demonstrated differences which warrant elaboration. These differences in detail appear to be sufficient to act as “fingerprints”, at least, for family differences. To date, the lateral line scales have been primarily studied. These demonstrate differences in the lateral line canals; the pattern of ridging with or without secondary protuberances along the edges; the pattern of spines or their absence on the anterior border of the scales; the presence or absence of single or multiple holes on the ventral and dorsal sides of the lateral line canal covers. The distances between the ridges in the pattern appear likewise to be important.A statement of fish scale structure and a comparison of family and species differences will be presented.The authors wish to thank Dr. Donald Marzalek and Mr. Wallace Charm of the Marine and Atmospheric Laboratory of the University of Miami and Dr. Sheldon Moll and Dr. Richard Turnage of AMR for their exhaustive help in these preliminary studies.

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