Emerging sensors, computers, network technologies, and connected platforms result potentially in an immeasurable collection of data within plant operations. This creates the possibility of solving problems innovatively. Because most of the data appear to be unstructured or semi-structured, organizations shall design and adopt new strategies. Further, workflow architectures with data analytics are needed including machine learning tools and artificial intelligence techniques before proto-type solutions can be developed. We shall discuss several prospects of using (big) data analytics integrated with cloud services to produce solutions for improving plant operations. The paper outlines the vision and a systematic framework highlighting the data analytics lifecycle in the area of plant operation, process safety, and environmental protection. Four rather diverse example case studies are demonstrated including (1) deep learning-based predictive maintenance monitoring modeling, (2) Natural Language Processing (NLP) for mining text, (3) barrier assessment for dynamic risk mapping (DRA), and (4) correlation development for sustainability indicators. It further discusses the challenges in both research and implementation of proposed solutions in the industry. It is concluded that a well-balanced integrated approach including machine supporting decisions integrated with expert knowledge and available information from various key resources is required to enable more informed policy, strategic, and operational risk decision-making leading to safer, reliable and more efficient operations.

新兴的传感器，计算机，网络技术和连接的平台可能导致工厂运营中无法计量的数据收集。这创造了创新解决问题的可能性。由于大多数数据似乎是非结构化或半结构化的，因此组织应设计并采用新的策略。此外，在可以开发原型解决方案之前，需要具有数据分析的工作流架构，包括机器学习工具和人工智能技术。我们将讨论使用（大）数据分析与云服务集成来产生改善工厂运营的解决方案的几种前景。本文概述了这一愿景和一个系统框架，重点介绍了工厂运营，过程安全和环境保护领域中的数据分析生命周期。展示了四个相当不同的示例案例研究，其中包括：（1）基于深度学习的预测性维护监视模型；（2）用于挖掘文本的自然语言处理（NLP）；（3）用于动态风险映射（DRA）的障碍评估；以及（4） ）针对可持续性指标的相关性开发。它进一步讨论了在业界研究和实施建议的解决方案时所面临的挑战。结论是，需要一种平衡良好的集成方法，包括将机器支持决策与专家知识和各种关键资源的可用信息相集成，以实现更明智的政策，战略和操作风险决策，从而实现更安全，可靠和更高效的操作。