SBIR-STTR Award

DLA Subsistence Supply Chain (SSC) experiences mold growth on wood pallets used for transportation of MRE. We propose a mold growth analysis and mitigation methodology based on supply chain, microbial monitoring and statistical techniques. The supply chain is modeled as a network of storage, production nodes and transportation links. A data collection procedure is developed to gather data related to mold growth factors at each point in the supply chain. Statistical and data mining techniques identify the root cause of mold development. An optimization model is developed to identify the subset of solutions which maximize cost-benefit in the mold mitigation process. A feasibility study is proposed in Phase I. It will show that the supply chain methodology can identify critical factors for mold development in a single route of the SSC. Conceptual design of the methodology will be completed in this phase. The feasibility study will be followed by Phase II, in which the methodology will be validated for multiple routes of the SSC. The proposed work sets the foundation for wide implementation of supply chain-based mold mitigation strategies. The potential market of this work includes a majority of supply chains given the prevalence of wood pallet usage.

Mold development on wooden pallets used for product transportation is a universal problem found not only in the DOD DLA subsistence supply chain but in multiple supply chains across various industries, e.g., food processing, textile manufacturing. While some species of mold are considered to be harmless to humans, others are known toxin producers. However, prolonged exposure to high concentrations of any type of mold can adversely affect the health of a person. To ensure product security and safety of DLA storage and transportation personnel, we propose mold eradication and prevention “service as a product”.  During Phase-II multiple DLA supply chains will be monitored and evaluated. The packaging, storage, and transportation environmental conditions will be studied using engineered continuous monitoring devices. The supply chain factors affecting mold development will be identified for every route. The opportunity of data driven solutions lies in translating this understanding of causative factors into actionable items such as improved pallet handling practices, worker training for early detection of potential mold issues, providing the methodology and means for safer remediation efforts using an enzyme-based mold inhibitor. The “service as a product” developed in this project can be customized to other supply chains within and outside DOD DLA.