SBIR-STTR Award

Digital Sustainment using Analytics for Land-Based Facilities
Award last edited on: 9/18/2022

Sponsored Program
SBIR
Awarding Agency
DOD : Navy
Total Award Amount
$1,148,989
Award Phase
2
Solicitation Topic Code
N193-A01
Principal Investigator
Michael MacEwen

Company Information

Beacon Interactive Systems LLC

271 Waverley Oaks Road Suite 204
Waltham, MA 02451
   (617) 441-9229
   info@beaconinteractive.com
   www.beaconinteractive.com
Location: Multiple
Congr. District: 05
County: Middlesex

Phase I

Contract Number: N68335-20-F-0164
Start Date: 11/21/2019    Completed: 4/20/2020
Phase I year
2020
Phase I Amount
$149,337
For N193-A01, Beacon is proposing to develop innovative AI and ML technologies that can predict and prescribe items for resupply within Naval Air Operations. The approach will be to build upon previous successful SBIR transitioned shipboard digital assets. The innovation proposed is to use AI / ML to inform and provide actionable intelligence into the supply chain from the operational point-of-performance; drive logistics from the needs at the flight line not just from acquisition requirements. The intent is to leverage a disparate and innovative data set along with existing products in order to have a more robust AI / ML experience that adds operational visibility to supply chain decision making. The proposed innovative data set embedded in a highly flexible software framework, combining maintenance, equipment, and operating conditions enables more precision in the supply chain.

Benefit:
The technology and innovation proposed by Beacon will directly benefit the Navy and other commercial customers by increasing efficiencies throughout the supply chain. Specifically: 1. The need for individual parts, tools and other supply chain elements will be more accurately determined 2. Supply chain and maintainers will be more closely linked, increasing precision of needed materials 3. All parties will have a more holistic view into the drivers of the supply chain because of the more holistic operational data set generated This technology has applicability beyond just Naval Air Operations and the Navy for any industrial customer that has significant operational assets to maintain, such as private shipyards, manufacturing plants, and electric utilities. Beacon also sees a large market in the DoD and Federal government for other areas that have a large, complex and diverse supply chain.

Keywords:
Machine Learning, Machine Learning, Logistics, supply chain, Analytics, sustainment, Artificial Intelligence, digital, maintenance

Phase II

Contract Number: N68335-22-C-0241
Start Date: 5/3/2022    Completed: 5/15/2023
Phase II year
2022
Phase II Amount
$999,652
Beacon will create a cloud-based Digital Infrastructure Sustainment Platform for the Surface Combat Systems Center, with a goal of providing real-time visibility into system capabilities and readiness and event planning. Beacon will develop and configure the prototype platform for managing baselines for SCSC. It will be capable of integration with any modern system, of where there are several standard Navy Systems used to manage and sustain SCSC systems. All these systems require manual translation to both enter and extract information between systems. This manual entry slows the flow of information, increases the probability of errors, and requires time that could be better spent resolving strategic and customer challenges. Built into the platform are process workflows that ensure proper execution of business rules and work. Behind the scenes, the information of each workflow (time started and stopped, who did it, impacts on other processes, etc.) is captured for true visibility into work. The architecture is based upon containerization and micro services, enabling a modular approach to build and delivery. Beacon also employs a plug and play approach to architecture that allows for future expansion.

Benefit:
The Platform will enable SCSC to efficiently achieve operational excellence through advanced functionality by: Providing forward looking capability to immediately identify conflicts between customer event planning and equipment availability Significantly improve event capacity by using analytics to: Identify critical equipment nodes to focus maintenance efforts on the most valuable assets Increase the efficiency of logistics support Plan maintenance based on data and customer requirements Creating efficiencies and value while reducing cost by creating a collaborative bi-directional flow of information between disparate systems and of knowledge between distributed personnel Implementing a modular, services-oriented architecture that eases deployment and seamlessly supports ongoing system improvement

Keywords:
cloud, sustainment, Analytics, open API, Process Digitization, asset management, maintenance