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相关概念视频

Response Surface Methodology01:16

Response Surface Methodology

279
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
279
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

148
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
148
Laminar Flow: Problem Solving01:24

Laminar Flow: Problem Solving

261
Laminar flow occurs when a fluid moves smoothly in parallel layers with minimal mixing and turbulence. In fluid mechanics, ensuring laminar flow within a pipe is essential for precise control of flow characteristics, especially in engineering applications. The key factor in determining whether flow remains laminar is the Reynolds number, a dimensionless quantity that depends on the fluid's velocity, density, viscosity, and the pipe's diameter. A Reynolds number of 2100 or lower...
261
Design Example: Managing Concrete Workability01:14

Design Example: Managing Concrete Workability

123
This example deals with managing the workability of concrete for a raft foundation project under hot weather conditions. Workability is crucial for ensuring the concrete is easy to place, compact, and finish. In this scenario, a slump test — a common method to measure the workability of fresh concrete — initially indicated low workability. This was attributed to the rapid water loss from the concrete mix, exacerbated by the high temperatures causing the course aggregates to heat up.
123
Cognitive Learning01:21

Cognitive Learning

551
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
551
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

741
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
741

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相关实验视频

Updated: Sep 16, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

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智能数据驱动系统用于模具制造,使用强化学习和知识图个性化优化进行定制生产.

Chengcai He1, Jiaxing Deng1, Jingchun Wu1

  • 1Shenzhen Ruipengfei Mold Co., Ltd, Shenzhen City, 518000, China.

Scientific reports
|July 4, 2025
PubMed
概括

本研究介绍了一种使用知识工程的优化模具数字化系统,以实现个性化的制造. 该系统提高了生产效率和质量控制,实现了超过94.7%的预测准确度.

关键词:
知识工程知识工程知识工程知识图表知识图表模具智能数据驱动系统是一个智能数据驱动系统.个性化 个性化强化学习是一种强化学习.

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Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
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Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

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相关实验视频

Last Updated: Sep 16, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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科学领域:

  • 制造业 工程 制造工程
  • 人工智能的人工智能
  • 知识工程知识工程知识工程

背景情况:

  • 传统制造业依赖于标准化的工艺,限制了定制化.
  • 个性化生产需要灵活和智能化的制造解决方案.

研究的目的:

  • 为个性化制造开发一个优化的模具数字化系统.
  • 整合知识图和智能算法用于智能质量控制.
  • 为了提高模具制造中的定制能力.

主要方法:

  • 利用知识工程将领域专业知识转换为可计算模型.
  • 雇员强化学习和图形神经网络用于知识提取.
  • 使用知识图和图形卷积网络开发了一个智能质量控制框架.

主要成果:

  • 优化的系统实现了超过88.1%的合格率,具有强大的性能调整.
  • 与其他模型相比,拟议的方法显示了超过94.7%的预测准确度.
  • 该系统显著提高了模具制造的定制性,效率和质量.

结论:

  • 优化的模具数字化系统为制造业的数字化转型提供了新的方向.
  • 该方法使智能,灵活的生产能够满足个性化的产品需求.
  • 该系统增强了制造商提供定制解决方案的能力,以高效和高质量提供定制解决方案.