Crises require rapid response, resilience, and preparedness, as observed in the COVID-19 pandemic. Crisis resilience and preparedness necessitates a rich manufacturing ecosystem of agile production assets which can be rapidly reconfigured, as well as an overarching innovation architecture that leverages policymakers and academics to accelerate crisis response. Now, more than ever, policymakers must develop actionable, evidence-based toolkits which can be reconfigured and deployed to combat the urgency and novelty of crisis scenarios. The challenges posed by the COVID-19 public health emergency reflect the breadth of disruption inherent to crisis events. For the COVID-19 crisis, it was necessary for manufacturing systems to rapidly pivot to fabricate critical life-saving products at scale without existing supply chains and manufacturing lines. In contrast to directly supporting a particular new manufacturing process, the RESPOND network will establish a transdisciplinary, diverse stakeholder ecosystem that sustains critical supernodes of communication and accelerated crisis response through product development, supply chain management and manufacturing capacity during crisis response. The future manufacturing focus of this network is providing the framework for understanding what shared resources, tools, and education and workforce development are needed to rapidly pivot manufacturing, for effective decision making by organizations, as well as stimulating new relevant research topics. The outputs of the network will thus be valuable beyond the scope of an individual crisis as an exemplar of product innovation in a truncated timeline, with limited information. The network is supported by the experience of the Massachusetts Manufacturing Emergency Response Team (MERT), a government-led initiative that facilitated the production of millions of medical products through dozens of pivoted manufacturing firms at the onset of the COVID-19 pandemic.
The RESPOND network will contribute principally to the fields of manufacturing science, agile business models, product development and innovation, emergency preparedness and resilience, risk management, economics, and data science. The network will disseminate its findings through partner engagements, convening activities, and publications which include actionable documentation, resources, and tools. This network will contribute directly to the aforementioned fields as well as form a foundational ecosystem upon which future research into related subjects can be performed. RESPOND will: (1) Perform a detailed analysis of the relationships between technological, organizational or environmental factors and the probability of firm-level success in pivoting production using fuzzy-set theoretical methods applied to data acquired through qualitative interviews and quantitative surveys of firms that were both successful and challenged in participating in MERT; (2) Refine statistical models utilized by the MERT and the Massachusetts Emergency Management Agency for demand-projection across product categories with the intent to publish them as templates for future statistical models; (3) Utilize rank-matching and machine learning approaches in making recommendations for manufacturing capacity database architectures which may enable organizing bodies to triage efforts towards high-impact firms; (4) Evaluate the influence of exogenous factors on firm-level success and provide policy recommendations for emergency management stakeholders and regulators; (5) Prepare an adaptable game-based simulation framework used both as a research tool for informing alternative approaches and as an instructional tool in preparing stakeholders for future crises; (6) Physically or digitally convene a network of stakeholders around these activities and, especially, the aforementioned game-based activity, for the purposes of fostering connections, transferring knowledge between different actors, and refining research; and (7) Disseminate the sum-total of knowledge generated or captured within the preceding tasks through modular curricula deployed via academic and professional credentialing programs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
