可控机器生产线及装配生产系统及信息模型数据集

本文提出了一种聚焦于智能制造环境下的可控机器生产线与装配系统的模型数据集，用以对柔性生产系统建模与性能分析。前者通过单机控制与多机控制两类数据集描述生产线参数，覆盖机器数量、效率、缓冲区容量、能耗模式等属性，所有参数通过严格定义的概率分布或离散集合随机采样生成。后者包含四类装配场景（三机同步/异步、多机同步/异步）及深度训练测试集，通过产品种类、机器数量、加工效率、缓冲区容量等参数组合，采用蒙特卡洛仿真生成相关实例。其中，同步切换场景固定产品种类或机器数，异步场景通过参数动态组合模拟产线复杂度。该数据集适用于可控机器生产线与装配生产系统的相关生产场景模拟与性能分析，为工业生产系统的效率优化与生产任务调度决策提供客观的结果分析。

This paper presents a model dataset focused on controllable machine production lines and assembly systems in the intelligent manufacturing context, designed for modeling and performance analysis of flexible production systems. The production line subset describes production line parameters via two categories: single-machine control and multi-machine control, covering attributes including the number of machines, operating efficiency, buffer capacity, energy consumption patterns, and more. All parameters are randomly sampled from strictly defined probability distributions or discrete sets. The assembly system subset includes four types of assembly scenarios (three-machine synchronous/asynchronous, multi-machine synchronous/asynchronous) and a deep training and testing dataset. Relevant simulation instances are generated through Monte Carlo simulation by combining parameters such as product categories, number of machines, processing efficiency, and buffer capacity. Specifically, synchronous scenarios fix either the product type or the number of machines, while asynchronous scenarios simulate the complexity of production lines through dynamic parameter combinations. This dataset is applicable to scenario simulation and performance analysis of controllable machine production lines and assembly production systems, providing objective result analysis for efficiency optimization and production task scheduling decisions of industrial production systems.

搜集汇总

背景与挑战

背景概述

该数据集聚焦智能制造环境，提供可控机器生产线与装配生产系统的模型数据，用于柔性生产系统建模与性能分析。它包含生产线参数（如机器数量、效率）和四类装配场景的实例，通过蒙特卡洛仿真生成，适用于生产场景模拟与效率优化决策。