SBIR-STTR Award

Medical supply chain issues are exacerbated during pandemics, natural disasters, war, etc., and must be addressed Cybernet will investigate current logistic processes, available logistics data, and required capabilities to drive the development of an artificial intelligence based medical logistics planning system leveraging both expert system and machine learning technologies. The goal is to develop a portal that will enable decisions to help anticipate medical supply chain issues, distribution shortfalls, and/or other unseen/unexpected logistics hurdles that may impede medical care. It will also support the prioritization of medical assets/inventory across the medical theater to anticipate supply shortfalls in time to coordinate medical logistics enterprise solutions. Specifically, we will create an Intelligent Medical Logistics Planning System (IMLPS) to address common inventory challenges faced by the medical community, including untimely outage of medicines and surgical equipment, overstock of supplies, identifying stock shortfalls, monitoring the supplying, and predicting supply chain issues and disruptions. We will directly leverage the web based portal that Cybernet and LMI are currently developing for USINDOPACOM, where we monitor and track logistics assets and issues from a wide variety of different sources, and combine the information into a comprehensive one-page PowerPoint slide of linked information for review and dissemination.

Benefit:
The benefit of the IMLPS is that it will create an agile, just-in-time medical logistics chain that can quickly respond to both planned and unplanned events, and also demand pulls. The intent is to properly align the various actors required to fulfill demand requests and eventually to predict potential medical logistics shortfalls to enable vastly improved medical logistics enterprise solutions for hospitals, ships, and medical groups in the Navy.

Keywords:
Digital Logistics, Digital Logistics, Medical Logistics, medical supplies, supply chain, Covid-19, Machine Learning, Artificial Intelligence

___(NOTE: Note: no official Abstract exists of this Phase II projects. Abstract is modified by idi from relevant Phase I data. The specific Phase II work statement and objectives may differ)___ Medical supply chain issues are exacerbated during pandemics, natural disasters, war, etc., and must be addressed Cybernet will investigate current logistic processes, available logistics data, and required capabilities to drive the development of an artificial intelligence based medical logistics planning system leveraging both expert system and machine learning technologies. The goal is to develop a portal that will enable decisions to help anticipate medical supply chain issues, distribution shortfalls, and/or other unseen/unexpected logistics hurdles that may impede medical care. It will also support the prioritization of medical assets/inventory across the medical theater to anticipate supply shortfalls in time to coordinate medical logistics enterprise solutions. Specifically, we will create an Intelligent Medical Logistics Planning System (IMLPS) to address common inventory challenges faced by the medical community, including untimely outage of medicines and surgical equipment, overstock of supplies, identifying stock shortfalls, monitoring the supplying, and predicting supply chain issues and disruptions. We will directly leverage the web based portal that Cybernet and LMI are currently developing for USINDOPACOM, where we monitor and track logistics assets and issues from a wide variety of different sources, and combine the information into a comprehensive one-page PowerPoint slide of linked information for review and dissemination.

Benefit:
The benefit of the IMLPS is that it will create an agile, just-in-time medical logistics chain that can quickly respond to both planned and unplanned events, and also demand pulls. The intent is to properly align the various actors required to fulfill demand requests and eventually to predict potential medical logistics shortfalls to enable vastly improved medical logistics enterprise solutions for hospitals, ships, and medical groups in the Navy.

Keywords:
Digital Logistics, Digital Logistics, Medical Logistics, medical supplies, supply chain, Covid-19, Machine Learning, Artificial Intelligence