It has become clear in recent decades that manufacturing supply chains are increas-ingly vulnerable to disruptions of varying geographical scales and intensities. These disruptions – whether intentional, accidental, or resulting from natural disasters –cause failures and capacity reductions to manufacturing infrastructure, with last-ing effects that can cascade throughout the manufacturing network. An overall lack of understanding of solutions to mitigate disturbances has rendered the challenge of reducing manufacturing supply chain vulnerability even more difficult. Addition-ally, the variability of disruptions and their impacts complicates policy maker and stakeholder efforts to plan for specific disruptive scenarios. It is necessary to compre-hend different kinds of disturbances and group them based on stakeholder-provided metrics to support planning processes and modeling efforts that promote adaptable, resilient manufacturing supply chains. This paper reviews existing methods for risk management in manufacturing supply chains and the economic and environmental impacts of disruptions.In addition, we develop a framework using agglomerative hi-erarchical clustering to classify disruptions using U.S. manufacturing network data between 2000 and 2021 and characteristic metrics defined in the literature. Our review identifies five groups of disruptions and discusses both general mitigation methods and strategies targeting each identified group. Further, we highlight gaps in the literature related to estimating and including environmental costs in disaster preparedness and mitigation planning. We also discuss the lack of easily available metrics to quantify environmental impacts of disruptions and how such metrics could be included into our methodology.
BT - Environmental Research: Infrastructure and Sustainability DA - 12/2022 DO - 10.1088/2634-4505/ac9c8c IS - 4 LA - eng N2 -It has become clear in recent decades that manufacturing supply chains are increas-ingly vulnerable to disruptions of varying geographical scales and intensities. These disruptions – whether intentional, accidental, or resulting from natural disasters –cause failures and capacity reductions to manufacturing infrastructure, with last-ing effects that can cascade throughout the manufacturing network. An overall lack of understanding of solutions to mitigate disturbances has rendered the challenge of reducing manufacturing supply chain vulnerability even more difficult. Addition-ally, the variability of disruptions and their impacts complicates policy maker and stakeholder efforts to plan for specific disruptive scenarios. It is necessary to compre-hend different kinds of disturbances and group them based on stakeholder-provided metrics to support planning processes and modeling efforts that promote adaptable, resilient manufacturing supply chains. This paper reviews existing methods for risk management in manufacturing supply chains and the economic and environmental impacts of disruptions.In addition, we develop a framework using agglomerative hi-erarchical clustering to classify disruptions using U.S. manufacturing network data between 2000 and 2021 and characteristic metrics defined in the literature. Our review identifies five groups of disruptions and discusses both general mitigation methods and strategies targeting each identified group. Further, we highlight gaps in the literature related to estimating and including environmental costs in disaster preparedness and mitigation planning. We also discuss the lack of easily available metrics to quantify environmental impacts of disruptions and how such metrics could be included into our methodology.
PY - 2022 EP - 042001 ST - Environ. Res.: Infrastruct. Sustain. T2 - Environmental Research: Infrastructure and Sustainability TI - Characterizing manufacturing sector disruptions with targeted mitigation strategiesAbstract UR - https://iopscience.iop.org/article/10.1088/2634-4505/ac9c8c VL - 2 ER -