基于自适应过程模型的自组织重构管理增强智能数字孪生
Enhancing an Intelligent Digital Twin with a Self-organized Reconfiguration Management based on Adaptive Process Models
摘要：
产品生存周期的缩短和生产的日益个性化导致工业自动化系统领域的重新配置需求增加，这将在未来由信息物理生产系统主导。然而，在不断变化的系统中，几乎无限状态空间的所有配置选择都没有被完全理解。因此，某些配置可能导致过程不稳定、质量降低或机器故障。因此，本文提出了一种方法，增强了智能数字孪生与自组织的重构管理的基础上，自适应过程模型，以更全面地找到优化配置。
英文摘要：
Shorter product life cycles and increasing individualization of production leads to an increased reconfiguration demand in the domain of industrial automation systems, which will be dominated by cyber-physical production systems in the future. In constantly changing systems, however, not all configuration alternatives of the almost infinite state space are fully understood. Thus, certain configurations can lead to process instability, a reduction in quality or machine failures. Therefore, this paper presents an approach that enhances an intelligent Digital Twin with a self-organized reconfiguration management based on adaptive process models in order to find optimized configurations more comprehensively.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
