Dynamics and Resilience for Design of Sustainable Processes, Industrial Networks and Supply Chains: Review and Perspective

Engineers are increasingly faced with the question of sustainable design of processes, industrial networks and supply chains. Conventional steady-state methodologies prevalent for sustainability assessment are inadequate to address the dynamic complexities of multiscale systems with which this community deals. This review systematically examines the evolution of sustainability assessment frameworks, highlighting the limitations of static approaches in capturing the nonlinearity, feed- back loops, and temporal variability inherent across the multiple scales. We explore the transition to dynamic, data-driven methodologies, emphasizing the integration of hybrid mechanistic-machine learning models that bridge first-principles knowledge with data. Further, we highlight the importance of transdisciplinary concepts from ecological sciences such as non-linear dynamics and resilience to the design of industrial networks and supply chains. The perspective uncovers how these dynamic phenomena influence system stability, adaptability, and long-term sustainability by incorporating concepts such as time delays, hysteresis, and time-variant characteristics. We further examine stability landscapes and adaptive cycles to demonstrate how resilience thinking redefines process design and control strategies in the face of global uncertainties. The emergence of advanced computational tools, such as spatial-temporal deep learning architectures and adaptive process control strategies, is reshaping the sustainability of manufacturing supply chains. These innovations enable robust performance under dynamic conditions while aligning with circular economy objectives. By synthesizing resilience principles with dynamic sustainability assessments, this review establishes a transformative paradigm for chemical process network design, offering both theoretical insights and practical strategies to advance sustainability in chemical engineering practice and the future trajectory of research.