The US Department of Defense is partnering with industry and academia on an initiative to advance and demonstrate the development of a Digital Maintenance Advisor (DMA) in support of materiel readiness with the application of artificial intelligence and machine learning toward predictive and prescriptive maintenance.
Specific objectives include:
- Predictive insights for decision-making: Deliver a machine learning-based predictive analytics system that proactively identifies anomalous behaviors based on sensor feeds, adapt to asset changes over time, provide prescriptive recommendations to improve maintainer performance and safety.
- Greater process efficiency: Establish a strong connection to workflows of maintenance operators utilizing AI technology that learns from historical datasets and operations experts and captures user input to improve prescriptive results.
- Greater asset availability: Prescriptive maintenance that delivers intelligent root cause analysis of inefficiencies, enabling the proactive mitigation of equipment failures days in advance and connecting to supply chain needs for reduced downtime and maintenance delays.
- Reduced maintenance and sustainment costs: Data driven analytics determine when services and maintenance should be performed based on asset failure and anomaly detection rather than relying on fixed schedules.
If you feel your organization has the technical capabilities and would like to be considered for this project, please complete the form below and upload your organization’s technical capabilities statement.
Interested Submissions Due by 10/31/23.
We encourage participation of Disadvantaged Business Enterprises (DBEs), including Minority Business Enterprises (MBEs) and Women’s Business Enterprises (WBEs).
