Minimization of path lengths for materials and workers in smart factories using particle swarm optimization algorithm

In smart factories, where humans collaborate with robots and machines, productivity can be optimized by minimizing the distance traveled by workpieces and workers. Previous studies on this subject have largely focused on the movement of the workpieces. Therefore, this study expands on this work by a...

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Veröffentlicht in:Journal of mechanical science and technology Jg. 37; H. 7; S. 3683 - 3690
Hauptverfasser: Cho, Jaeyoung, Nam, Myonghun, Kim, Yeonggyun, Park, Kang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Seoul Korean Society of Mechanical Engineers 01.07.2023
Springer Nature B.V
대한기계학회
Schlagworte:
Algorithms
Collaboration
Control
Costs
Departments
Dynamical Systems
Engineering
Factories
Industrial and Production Engineering
Industrial plants
Layouts
Mechanical Engineering
Optimization algorithms
Optimization techniques
Original Article
Particle swarm optimization
Plant layout
Robots
Science
Vibration
Workers
Workpieces
기계공학
Collaborative robot
Layout
Arrangement
Optimization
Smart factory
PSO algorithm
ISSN:1738-494X, 1976-3824
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Abstract In smart factories, where humans collaborate with robots and machines, productivity can be optimized by minimizing the distance traveled by workpieces and workers. Previous studies on this subject have largely focused on the movement of the workpieces. Therefore, this study expands on this work by accounting for the movement of the workers. In this study, the facility layout of smart factories is optimized by minimizing the distances traveled by the workpieces and workers, which is accomplished through the particle swarm optimization (PSO) algorithm. In this algorithm, each arrangement of the factory elements constitutes a unique particle, and initial particles are generated randomly using rules to be used as seeds for optimization. PSO is then executed to generate a layout that minimizes the distances traveled by the workpieces and workers. This method produces layouts that are more optimal than those in which only the distance traveled by the workpieces is considered.
AbstractList In smart factories, where humans collaborate with robots and machines, productivity can be optimized by minimizing the distance traveled by workpieces and workers. Previous studies on this subject have largely focused on the movement of the workpieces. Therefore, this study expands on this work by accounting for the movement of the workers. In this study, the facility layout of smart factories is optimized by minimizing the distances traveled by the workpieces and workers, which is accomplished through the particle swarm optimization (PSO) algorithm. In this algorithm, each arrangement of the factory elements constitutes a unique particle, and initial particles are generated randomly using rules to be used as seeds for optimization. PSO is then executed to generate a layout that minimizes the distances traveled by the workpieces and workers. This method produces layouts that are more optimal than those in which only the distance traveled by the workpieces is considered.
In smart factories, where humans collaborate with robots and machines, productivity can be optimized by minimizing the distance traveled by workpieces and workers. Previous studies on this subject have largely focused on the movement of the workpieces. Therefore, this study expands on this work by accounting for the movement of the workers. In this study, the facility layout of smart factories is optimized by minimizing the distances traveled by the workpieces and workers, which is accomplished through the particle swarm optimization (PSO) algorithm. In this algorithm, each arrangement of the factory elements constitutes a unique particle, and initial particles are generated randomly using rules to be used as seeds for optimization. PSO is then executed to generate a layout that minimizes the distances traveled by the workpieces and workers. This method produces layouts that are more optimal than those in which only the distance traveled by the workpieces is considered. KCI Citation Count: 0
Author Park, Kang
Kim, Yeonggyun
Nam, Myonghun
Cho, Jaeyoung
Author_xml – sequence: 1
  givenname: Jaeyoung
  surname: Cho
  fullname: Cho, Jaeyoung
  organization: Department of Mechanical Engineering, Myongji University
– sequence: 2
  givenname: Myonghun
  surname: Nam
  fullname: Nam, Myonghun
  organization: Department of Mechanical Engineering, Myongji University
– sequence: 3
  givenname: Yeonggyun
  surname: Kim
  fullname: Kim, Yeonggyun
  organization: Department of Mechanical Engineering, Myongji University
– sequence: 4
  givenname: Kang
  surname: Park
  fullname: Park, Kang
  email: kxp007@gmail.com
  organization: Department of Mechanical Engineering, Myongji University
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10.9713/kcer.2014.52.4.475
10.14346/JKOSOS.2015.30.3.32
10.1016/j.apm.2016.01.014
10.1016/S0924-0136(01)00908-6
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10.1061/(ASCE)0733-9364(2008)134:9(739)
10.1016/j.cie.2009.11.015
10.1080/00207543.2013.765078
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Keywords Collaborative robot
Layout
Arrangement
Optimization
Smart factory
PSO algorithm
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Snippet In smart factories, where humans collaborate with robots and machines, productivity can be optimized by minimizing the distance traveled by workpieces and...
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SubjectTerms Algorithms
Collaboration
Control
Costs
Departments
Dynamical Systems
Engineering
Factories
Industrial and Production Engineering
Industrial plants
Layouts
Mechanical Engineering
Optimization algorithms
Optimization techniques
Original Article
Particle swarm optimization
Plant layout
Robots
Science
Vibration
Workers
Workpieces
기계공학
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Title Minimization of path lengths for materials and workers in smart factories using particle swarm optimization algorithm
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Volume 37
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