This paper presents a smart supervisory framework for a single process controller, designed for Industry 4.0 shop floors. This digitization of a full supervisory suite for a single process controller enables self-awareness, self-diagnosis, self-prognosis, and self-healing (by definition, these "self" elements are missing from other supervisory frameworks diagnosing numerous controllers in parallel). The proposed framework is aligned with the concept of a Cyber Physical System (CPS), since its implementation generates a rich cyber physical entity of the controlled process. This CPS entity can either be considered as the process digital twin, or can provide a solid basis for generating it. Finally, the framework includes the main characteristics of Industry 4.0, such as advanced use of Artificial Intelligence (AI) and big data analysis. The framework is based on four modules: (1) Control and Awareness module—performing both continuous process control and adjustments, as well as machine learning (ML) and statistical process control (SPC) for identifying abnormalities that require further diagnosis; (2) Process -diagnosis module—performing continual (recurrent) analysis of the process state and trends; (3) Prognosis and Healing module—performing prognosis and automated intervention via parameter changes, re-configurations, and automated maintenance; (4) External Interaction Platform—an interactive module for interfacing with experts, presenting them with the process analysis information and obtaining feedback from them as part of a learning process. Using an implementation showcase to illustrate the methodological framework’s applicability, we demonstrate its real-world potential. The proposed framework could serve as a guide for implementing smart process control and maintenance systems in Industry 4.0 shop floors. It could also provide a firm basis for comparison with future suggested frameworks. Future research directions could include pursuing improvements to the proposed process control framework and validating the framework by case studies of its implementation.

本文提出了针对工业4.0车间设计的单个过程控制器的智能监控框架。用于单个过程控制器的完整监控套件的数字化可实现自我意识，自我诊断，自我诊断和自我修复（根据定义，这些“自我”要素在并行诊断众多控制器的其他监督框架中缺失） 。提议的框架与网络物理系统（CPS）的概念保持一致，因为其实施会生成受控过程的丰富网络物理实体。这个CPS实体可以被视为过程数字孪生，或者可以为生成它提供坚实的基础。最后，该框架包括工业4.0的主要特征，例如人工智能（AI）的先进使用和大数据分析。连续过程控制和调整，以及机器学习（ML）和统计过程控制（SPC），用于识别需要进一步诊断的异常；（2）过程诊断模块-连续执行（经常性）分析过程状态和趋势；（3）预后和恢复模块-通过参数更改，重新配置和自动维护执行预后和自动干预；（4）外部交互平台-一个交互模块，用于与专家进行交互，为他们提供过程分析信息，并从他们那里获得反馈，作为学习过程的一部分。通过使用一个实现展示来说明该方法框架的适用性，我们展示了其在现实世界中的潜力。提议的框架可以作为在工业4.0车间中实施智能过程控制和维护系统的指南。它还可以为与将来建议的框架进行比较提供坚实的基础。