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相关概念视频

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

48
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Optimization of Productivity and Worker Well-Being by Using a Multi-Objective Optimization Framework.

IISE transactions on occupational ergonomics and human factors·2021
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使用自然启发的算法和数字人类建模工具对装配布局的多目标优化.

Andreas Lind1,2, V Elango1,2, L Hanson2

  • 1Scania CV AB, Södertälje, Sweden.

IISE transactions on occupational ergonomics and human factors
|June 12, 2024
PubMed
概括

本研究介绍了工业5.0的自动化工厂布局规划方法,集成多目标优化和数字人体建模,以提高工人福利和系统效率.

关键词:
多个目标的多重目标.组装的组装组装的组装.工厂布局 工厂布局 工厂布局工业 5.0 工业 5.0 工业优化的优化优化优化.

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科学领域:

  • 制造业 工程 制造工程
  • 运营研究 运营研究
  • 人类因素工程 人类因素工程

背景情况:

  • 传统的工厂布局规划是缓慢的,容易出现人为错误.
  • 现有的方法往往严重依赖于主观工程师的专业知识.
  • 工业5.0需要更加综合和高效的规划方法.

研究的目的:

  • 开发制造工厂布局规划的先进方法.
  • 将多目标优化与以自然为灵感的算法和数字人类建模相结合.
  • 解决工业5.0背景下传统规划方法的局限性.

主要方法:

  • 利用多目标优化,重点关注员工福利和系统性能.
  • 整合了以自然为灵感的算法,以实现高效的搜索和优化.
  • 采用数字人体建模工具进行现实的模拟和分析.

主要成果:

  • 展示了一个透明的,跨学科的,自动化的布局规划过程.
  • 成功地将该方法应用于踏板汽车装配站布局案例.
  • 实现了目标和高效的布局规划,考虑到双重目标.

结论:

  • 拟议的方法代表了制造工厂布局设计的重大进步.
  • 它为工厂规划提供了强大的多目标决策支持.
  • 促进向更自动化和数据驱动的布局设计实践过渡.