Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Decision Making: P-value Method01:09

Decision Making: P-value Method

5.5K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.5K
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

4.1K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
4.1K
Machines: Problem Solving II01:30

Machines: Problem Solving II

336
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
336
Stereotype Content Model02:16

Stereotype Content Model

14.8K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.8K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Industry 5 and the Human in Human-Centric Manufacturing.

Sensors (Basel, Switzerland)·2023
Same author

Adaptive Manufacturing for Healthcare During the COVID-19 Emergency and Beyond.

Frontiers in medical technology·2022
Same author

A Eukaryotic-like Serine/Threonine Kinase Protects Staphylococci against Phages.

Cell host & microbe·2016
查看所有相关文章

相关实验视频

Updated: Jul 23, 2025

Author Spotlight: Advancing Labor Management Through Electromyometrial Imaging for Understanding Uterine Contractions
08:07

Author Spotlight: Advancing Labor Management Through Electromyometrial Imaging for Understanding Uterine Contractions

Published on: May 26, 2023

1.2K

在劳动密集型制造业中,利用工人位置数据为人为驱动的决策支持.

Ayse Aslan1, Hanane El-Raoui2, Jack Hanson3

  • 1The School of Computing, Engineering and The Built Environment, Edinburgh Napier University, Edinburgh EH10 5DT, UK.

Sensors (Basel, Switzerland)
|July 11, 2023
PubMed
概括
此摘要是机器生成的。

本研究引入了一种用于优化制造业工人能力的新方法. 通过分析真实的工作数据,它展示了小调整如何在不增加员工的情况下显著缩短生产时间.

关键词:
完成时间 完成时间离散事件模拟的离散事件模拟.灵活的容量分配能力分配.室内定位系统 室内定位系统工业生产率的提高 工业生产率的提高过程采矿过程采矿

更多相关视频

Surrogate Model Development for Digital Experiments in Welding
09:17

Surrogate Model Development for Digital Experiments in Welding

Published on: March 28, 2025

1.1K
Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
07:05

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

Published on: October 27, 2016

9.3K

相关实验视频

Last Updated: Jul 23, 2025

Author Spotlight: Advancing Labor Management Through Electromyometrial Imaging for Understanding Uterine Contractions
08:07

Author Spotlight: Advancing Labor Management Through Electromyometrial Imaging for Understanding Uterine Contractions

Published on: May 26, 2023

1.2K
Surrogate Model Development for Digital Experiments in Welding
09:17

Surrogate Model Development for Digital Experiments in Welding

Published on: March 28, 2025

1.1K
Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
07:05

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

Published on: October 27, 2016

9.3K

科学领域:

  • 工业工程 工业工程 工业工程
  • 运营研究 运营研究
  • 制造系统制造系统的制造

背景情况:

  • 劳动密集型制造系统在很大程度上依赖于人类工人,使他们的实际工作实践对提高生产率至关重要.
  • 基于理论模型实施变化可能是无效的;对实际工人行为的数据驱动洞察力至关重要.
  • 在这些系统中,容量分配需要一种反映实际运营动态的方法.

研究的目的:

  • 为劳动密集型制造业的产能分配提供以人为驱动的决策支持提出一种新的方法.
  • 利用工人位置数据和过程挖掘来创建数据驱动的过程模型.
  • 利用离散事件模拟来评估基于观察到的工作实践的容量分配调整.

主要方法:

  • 使用定位传感器收集工人位置数据.
  • 应用过程挖掘算法来生成制造任务的数据驱动过程模型.
  • 在数据驱动过程模型的基础上构建一个离散事件模拟模型.
  • 调查容量分配调整对系统性能的影响.

主要成果:

  • 在没有额外的工人的情况下,通过轻微的容量调整实现了7%的完成时间缩短.
  • 通过增加一名工人和优化瓶任务,完成时间减少了16%.
  • 该方法证明了数据驱动模拟在手动装配线上的容量分配方面的有效性.

结论:

  • 工人位置数据和过程挖掘为实际制造业务提供了宝贵的见解.
  • 以真实数据为基础的离散事件模拟对于优化容量分配是有效的.
  • 有针对性的产能调整,特别是在瓶任务中,可以显著提高制造效率并缩短完成时间.