论文标题
部分可观测时空混沌系统的无模型预测
Monte Carlo Methods for Industry 4.0 Applications
论文作者
论文摘要
近年来，第四次工业革命和数字化转型（通常称为工业4.0）的发展呈指数级发展。连接的计算机，设备和智能机器相互通信，并与环境交互，只需最少的人力干预即可。行业4.0中的一个重要问题是评估KPI的过程质量。蒙特卡洛模拟可以发挥重要作用来改善估计。但是，仍然缺乏清晰的工作流程来进行蒙特卡洛模拟，以选择不同的蒙特卡洛方法。因此，本文提出了用于在行业4.0应用中进行蒙特卡洛方法比较的模拟流。根据模拟流，我们比较累积的蒙特卡洛和马尔可夫链蒙特卡洛方法。实验结果显示了在行业4.0中使用蒙特卡洛方法以及两种模拟方法的可能局限性的方法。
The fourth industrial revolution and the digital transformation, commonly known as Industry 4.0, is exponentially progressing in recent years. Connected computers, devices, and intelligent machines communicate with each other and interact with the environment to require only a minimum of human intervention. An important issue in Industry 4.0 is the evaluation of the quality of the process in terms of KPIs. Monte Carlo simulations can play an important role to improve the estimations. However, there is still a lack of clear workflow to conduct the Monte Carlo simulations for selecting different Monte Carlo methods. This paper, therefore, proposes a simulation flow for conducting Monte Carlo methods comparison in Industry 4.0 applications. Based on the simulation flow, we compare Cumulative Monte Carlo and Markov Chain Monte Carlo methods. The experimental results show the way to use the Monte Carlo methods in Industry 4.0 and possible limitations of the two simulation methods.
