N221-D02 TITLE: DIRECT TO PHASE II – Flight Operations Planning Decision Aid Tool for Strike Operations Aboard Aircraft Carriers

OUSD (R&E) MODERNIZATION PRIORITY: Autonomy

TECHNOLOGY AREA(S): Information Systems

The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws.

OBJECTIVE: Develop a decision support tool using intelligent agents to assist Strike Operations (Strike Ops) in scheduling flight operations aboard aircraft carriers.

DESCRIPTION: Flight operations planning on aircraft carriers is central to the success and efficiency of the carrier air wing (CVW) in executing missions. Scheduling is dependent on mission objectives, as well as available resources and strike group readiness. The schedule of all air operations within a day is documented in the Air Plan by the Strike Operations department. The Air Plan consists of events for each CVW squadron, which are broken down into details, such as launch and recovery times, mission type, and aircrafts assigned. A Load Plan is then generated to document the ordnance required to fulfill each event. These plans are distributed throughout the CVW for execution. The process of creating these plans can be challenging and time consuming. Information systems are in place for documenting and managing Air Plans but require expert input from Strike Ops planners. Additionally, there is a wide range of information sources that determine events to include within the Air Plan and it is difficult to gather information on readiness. These plans are likely to change on the fly as well, due to unforeseen changes to missions and resources. There is a technology insertion opportunity to reduce workload, increase planning efficiency, and improve adaptability through the use of a decision support application.

Intelligent agent technology can provide decision aids to reduce the complexity of flight operations planning. Agents would need to be able to generate plans based on mission requirements and strike group readiness. The system would need to collect and perceive all pertinent information required to fill out an Air Plan and a Load Plan. This includes tasks determined from mission requirements, maintenance requirements, carrier qualifications, logistics flights, and training requirements. Tasks would need to be mapped to resources such as squadron capability, ordnance required, and aircraft availability to populate an Air Plan and a Load Plan. For example, the system would need to automatically assign a squadron to a specific mission based on availability, capability, and readiness. The solution should include the ability to provide observability in its decisions while allowing for adjustments and alternative plans. Intelligent agents were proven applicable within many areas in industry, including defense and naval aviation. However, there is currently no intelligent agent technology directed towards the flight operations planning aboard aircraft carriers. This particular application’s dilemma is due to the difficulty of gathering information required to create the Air Plan. Not only do the plans need to take into account the status of available CVW resources, but also the intent of the CVW as well.

The Navy is considering technology solutions to creating an intelligent decision support system. Methods that address the time-consuming nature of information capture, both manual input and sensory input, will be considered. Solutions that can be implemented to current shipboard flight operations planning processes with minimal impact is preferred.

Work produced in Phase II may become classified. Note: The prospective contractor(s) must be U.S. owned and operated with no foreign influence as defined by DoD 5220.22-M, National Industrial Security Program Operating Manual, unless acceptable mitigating procedures can and have been implemented and approved by the Defense Counterintelligence and Security Agency (DCSA) formerly Defense Security Service (DSS). The selected contractor must be able to acquire and maintain a secret level facility and Personnel Security Clearances. This will allow contractor personnel to perform on advanced phases of this project as set forth by DCSA and NAVAIR in order to gain access to classified information pertaining to the national defense of the United States and its allies; this will be an inherent requirement. The selected company will be required to safeguard classified material IAW DoD 5220.22-M during the advanced phases of this contract.

PHASE I: For a Direct to Phase II topic, the Government expects that the small business would have accomplished the following in a Phase I-type effort. Have developed a concept for a workable prototype or design to address, at a minimum, the basic requirements of the stated objective above. The below actions would be required in order to satisfy the requirements of Phase I:

Determined and demonstrated the feasibility of a decision support tool in providing decision aids for a scheduling application. Feasibility must be demonstrated through analysis, modeling or lab demonstration. Results and analysis from previous efforts should be referenced in feasibility documentation.

FEASIBILITY DOCUMENTATION: Offerors interested in participating in Direct to Phase II must include in their response to this topic Phase I feasibility documentation that substantiates the scientific and technical merit and Phase I feasibility described in Phase I above has been met (i.e., the small business must have performed Phase I-type research and development related to the topic, but from non-SBIR funding sources) and describe the potential commercialization applications. The documentation provided must validate that the proposer has completed development of technology as stated in Phase I above. Documentation should include all relevant information including, but not limited to: technical reports, test data, prototype designs/models, and performance goals/results. Work submitted within the feasibility documentation must have been substantially performed by the offeror and/or the principal investigator (PI). Read and follow all of the DON SBIR 22.1 Direct to Phase II Broad Agency Announcement (BAA) Instructions. Phase I proposals will NOT be accepted for this topic.

PHASE II: Develop a decision support software prototype to assist in flight operations planning aboard aircraft carriers. Optimize intelligent agent outputs based on subject matter expert feedback. Demonstrate the technology through simulations and compare its effectiveness to traditional methods of scheduling and planning. Provide documentation on software and hardware architecture.

Work in Phase II may become classified. Please see note in Description paragraph.

PHASE III DUAL USE APPLICATIONS: Create a full-scale decision support software tool capable of supporting the process of flight operations scheduling aboard aircraft carriers. The system should be capable of providing schedules that increase the performance of flight operations.

Industry applications include production and manufacturing planning, shipping logistics, and medical scheduling.

REFERENCES:

1. Khemakhem, F., Ellouzi, H., Ltifi, H., & Ayed, M. B. (2020, October 13). Agent-based intelligent decision support systems: A systematic review. IEEE Transactions on Cognitive and Developmental Systems. IEEE. https://doi.org/10.1109/TCDS.2020.3030571.
2. Naval Air Training Command. (2014, January 28). Flight training instruction: CV procedures (UMFO) T-45C. (pp. 2-1–2-2 Flight Procedures). Department of the Navy. https://www.cnatra.navy.mil/local/docs/pat-pubs/P-816.pdf.
3. Zhang, Y., Tu, Y., & Qiu, D. (2018, March). A multi-agent based intelligent scheduling algorithm. In 2018 Tenth International Conference on Advanced Computational Intelligence (ICACI) (pp. 874-877). IEEE. https://doi.org/10.1109/ICACI.2018.8377578.

KEYWORDS: Intelligent Agents; Decision Support; Scheduling; Aircraft Carriers; Air Plan; Strike Operations