The number and diversity of Process Analytics applications is growing fast, impacting areas ranging from process operations to strategic planning or supply chain management. However, this field has not reached yet a maturity level characterized by a stable, organized and consolidated body of knowledge for handling the main classes of problems that need to be faced. Data-Driven Process Systems Engineering and Process Analytics only recently received wider recognition, becoming a regular presence in journals and conferences. As a tribute to the groundbreaking Process Analytics contributions of George Stephanopoulos, namely through his academic tree, to which we are proud to belong, this article aims to contribute to the systematization and consolidation of this field in the broad PSE scope, starting from a fundamental understanding of the key challenges facing it, and constructing from them a workflow that can flexibly be adapted to handle different problems, aimed at supporting value creation through good decision-making. In this path, we base our foresight and conceptual framework on the authors’ experience, as well as on contributions from other researchers that, across the world, have been collectively pushing forward Data-Driven Process Systems Engineering.

流程分析应用程序的数量和多样性正在快速增长，影响着从流程运营到战略规划或供应链管理的各个领域。然而，该领域尚未达到成熟水平，其特点是具有稳定、有组织和统一的知识体系，用于处理需要面对的主要问题类别。数据驱动的过程系统工程和过程分析直到最近才获得更广泛的认可，成为期刊和会议的常客。作为对 George Stephanopoulos 开创性的过程分析贡献的致敬，即通过他的学术树，我们很自豪地属于，本文旨在促进该领域在广泛的 PSE 范围内的系统化和巩固，从对其面临的关键挑战的基本了解开始，并从中构建一个可以灵活调整以处理不同问题的工作流程，旨在通过良好的决策支持价值创造。在这条道路上，我们的远见和概念框架基于作者的经验，以及来自世界各地的其他研究人员的贡献，这些研究人员一直在共同推动数据驱动的过程系统工程。