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The United States relies on chemical manufacturing to provide products ranging from everyday consumer goods (plastics, fabrics, adhesives, paints) to cutting edge technologies (medicines, electronic materials), industrial goods (dyes, pesticides) and military supplies (fuels, explosives). While many high-volume, petroleum-derived chemical feedstocks are produced domestically, much of the fine chemical manufacturing necessary for complex chemical products (e.g., pharmaceuticals, electronics, energetics) has been outsourced.
As a result, the U.S. is vulnerable to dynamic factors that are challenging to forecast, including issues as complex as political conflict, as unpredictable as natural disasters, and as simple as economies of scale. While the origin might vary, the impact is universal – such forces disrupt our supply of chemical feedstocks and products, affecting critical sectors of our nation including
defense, healthcare, transportation, communications, and the economy.
Extreme events cause significant damage and disruption to the manufacturing sector, associated supply chains, and adjacent communities. These disastrous shocks may include natural disasters (e.g., hurricanes, floods, earthquakes), pandemics, catastrophic economic collapses (e.g., price crash of oil and gas), and terrorist and cyberattacks. Traditionally, the design, operation, and optimization of manufacturing facilities have been largely driven by economic factors with little consideration of risk, resilience, interactions with surrounding communities, and integration with supply chains.
Generally speaking, resilience engineering is aimed at decreasing the negative impact of shocks on the system performance and enhancing the adaptive capacity of the system to respond quickly and favorably to expected and unexpected disruptions. The three main capacities of a resilient system are absorptive, adaptive, and restorative and the key characteristics of a resilient system are robustness, resourcefulness, rapidity, and redundancy.
Reconfigurability corresponds to the ability to alter the process flowsheet using the same pieces of equipment but in different arrangements and/or for multiple purposes. In the field of process integration, this concept has been largely limited to batch processes and, to a much lesser extent, to small-scale specialty-chemical or pharmaceutical processes. Large-scale processing facilities are notorious for their fixed configuration. An effective way of reconfiguring the process without moving the fixed and bulky equipment is to use different configurations of the connecting pipelines.
A particularly useful tool that has been used in process synthesis is the superstructure approach. It is a network representation that embeds all configurations of interest that can then be translated into an optimization formulation to be solved for the selection of the optimal configuration.
Repurposability refers to the capability of a process to be used for purposes or products that are different from the original ones. During disaster times, there is insufficient time to resort to conventional retrofitting or revamping activities. Nonetheless, if the process has a pre-disaster design which is re-purposeful, alteration from one mode of operation to the other becomes almost instantaneously possible.
For instance, consider a process that converts natural gas to methanol. During pandemics, it is anticipated that there will be increased demands for hand sanitizers because of the additional use and panic buying. An important ingredient in the production of hand sanitizers is ethanol. Methanol cannot be used in hand sanitizers because it leads to severe health problems. Can a methanol plant be repurposed to produce ethanol? The answer is yes but the repurposing requires pre-planning during the greenfield design or retrofitting phases. Process simulation and synthesis techniques may be used to ensure the ability to repurpose and to identify necessary changes in vessel design, operating conditions, and catalyst.
DARPA launched Resilient Chemical Manufacturing (RCM) in March 2022 that seeks to enable the rapid reallocation and optimization of existing domestic chemical manufacturing infrastructure to a new suite of products, allowing the U.S. to leverage existing onshore production equipment to respond to chemical supply chain disruptions.
While developing new manufacturing infrastructure and methods (e.g., automated, distributed, continuous) is one way to address these challenges, another approach of specific interest to DARPA is to build software planning capabilities that enable automated allocation and optimization of existing domestic chemical manufacturing infrastructure to a new set of products.
Conventional plant-based chemical manufacturing consists of diverse sets of
equipment (reactors, pumps, columns, separators, etc.) connected in a defined sequence to produce a single product. Allocation and reconfiguring of this equipment to produce a different product is a slow, manual operation, requiring detailed process knowledge and deep expertise on a given product. As a result, domestic manufacturing capacity for any new product is vastly underestimated, and diverse, secondary considerations related to critical manufacturing process attributes (e.g., scale, purity, and throughput; geographic location/distribution; and sitespecific regulatory considerations) are challenging to consider and impossible to fully optimize.
Developing the capacity to automatically identify, allocate, and optimize chemical manufacturing assets across multiple sites/vendors and understand the dependencies of particular assets on user requirements for new chemical products would revolutionize our ability to address chemical supply chain challenges across multiple sectors.
RCM will enable rapid reallocation of existing domestic chemical manufacturing to produce chemicals that are subject to supply chain disruptions, allowing the U.S. to leverage on-shore, U.S.-owned production equipment to meet demand for chemicals due to supply chain disruptions or other dynamic demand swings. RCM will build robust production planning algorithms for a variety of domestic and foreign chemical products critical to the U.S. industrial and consumer base, develop precise ontologies for manufacturing equipment, establish a dynamic database of U.S.-owned manufacturing assets, and demonstrate a software tool that can pair production needs with latent (yet-to-be configured) manufacturing capacity. Importantly, RCM will not develop new production infrastructure but instead, provide the capacity to model and forecast existing production equipment to meet a new production need.
PHASE I:
This topic solicits Direct to Phase II proposals ONLY. Proposers must demonstrate that the following has been achieved outside of the SBIR program: Initial software tool/prototype that is capable of automated allocation of domestic manufacturing assets for at least ten chemical products. The demonstrated capability must include: (1) a database of domestic chemical manufacturing assets, (2) an ontology to adequately describe and measure equivalency of chemical manufacturing equipment, (3) the ability to consider process features (e.g., volume,
chemical compatibility, temperature ranges) and user requirements (e.g., throughput, purity, regulatory standards), and (4) capacity to consider equipment and/or processes across multiple manufacturing sites.
RCM performers will build and validate software that enables automated allocation, management, and optimization of domestic chemical manufacturing assets. DARPA anticipates approaches that include (1) acquisition of domestic manufacturing asset information resulting in a dynamic asset database; (2) economic, security, and availability assessments of existing critical fine chemicals with approaches to computationally assess substitute chemicals; (3) fully operational, validated software with a user interface (UI) designed for non-experts that automatically allocates
domestic chemical manufacturing assets across the U.S. to a particular chemical in shortage; and (4) a suite of tools that enables optimization across both chemical feedstock and/or supply chain availability and domestic manufacturing potential.
