PMW/ISEA teams are dealing with thousands of trouble tickets daily, by prioritizing the tickets as they are submitted based upon how long the ticket is estimated to resolve will enable the help desk and the ISEA groups to make quicker decisions and prioritize their resources. Delta Duration Model was built with an ensemble structure to predict the time it will take for a ticket to resolve as the ticket ages. The Delta Duration Model uses up to 4 different AI/ML algorithms working together to determine duration of ticket upon submission. As the ticket ages, additional models are used to more accurately predict a resolution date. A model maintenance pipeline was created out of a need to track various accuracy metrics on the deployed models for the Delta Duration Model. Each week when new tickets have been submitted and predicted upon the maintenance pipeline tracks accuracy for each set of models within the pipeline. This monitors changes in the model’s accuracy over time and allows transparency when model drift has occurred.

Machine Learning to Predict and Monitor Trouble Ticket Duration

PMW/ISEA teams are dealing with thousands of trouble tickets on a daily basis – currently the process is reliant on sailors or help desk self-assessing issue severity​. CASREP Prediction Model was develop to predict which Trouble Tickets are most likely to escalate into a CASREP or will take longer to resolve. This allows immediate identification of high-risk issues as soon as the trouble ticket is submitted. Enables team to prioritize response actions and resources, and potentially reduce system downtime. CASREP Prediction Model uses NAVWAR Help Desk ITSM data and five different AI/ML algorithms to work together to boost accuracy. 

The Trouble Ticket Duration model builds upon the framework of the CASREP Prediction Model but with the focus on predicting how long until a trouble ticket will be resolved. The Fleet will be potentially able to forecast downtime and adjust operational plans to compensate effectively. The PMW/ISEA teams are potentially able to use the forecast to prioritize tasking in resolving these trouble tickets.



Using Machine Learning to Predict CASREP Occurrence and Trouble Ticket Duration

Poster Session 1B

poster

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Naval Information Warfare Center Pacific is partnering with AFCEA San Diego chapter to host the workshop.

The NAML workshop is an opportunity for researchers from Navy research and development centers and our partner organizations to exchange technical ideas and to come together as a team.

The goals of NAML are:

To spread awareness of current machine learning research relevant to Naval applications

To connect machine learning researchers with experts in military requirements

To build and strengthen collaborations within the defense research community


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  <iframe src="https://s3.amazonaws.com/pf-user-files-01/u-59356/uploads/2022-03-22/hk13mxo/NAML_ReceptionWithtitle.mp4" width=826  height=526  frameborder="0" allowfullscreen="true"> </iframe>
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NAML 2022

Naval Information Warfare Center Pacific is partnering with AFCEA San Diego chapter to host the workshop. The NAML workshop is an opportunity for researchers from Navy research and development centers and our partner organizations to exchange technical ideas and to come together as a team.

The goals of NAML are:

To spread awareness of current machine learning research relevant to Naval applications

To connect machine learning researchers with experts in military requirements

To build and strengthen collaborations within the defense research community



This is the 4th of four poster sessions.

**Date & Time:**  Thursday March 25th,  12-1:30pm PDT

**Location:** Poster Session Room 2B

The live poster sessions will happen in our Gather.Town lounge at the designated time. Each session has their own room. Once you click the gathertown button below, you will need to navigate to the Poster Session Room for each session located on the right side of the lounge. Each speaker will be by their poster where you can communicate with them and view their poster by clicking X on your keyboard.

[![](https://assets.underline.io/uploads/markdown_image/1/image/737a34c989ecf3ae95182670d99c072c.png)](https://gather.town/app/5IAViMZXC9ZF4E4l/NAML)

Poster Session 2B

Naval Information Warfare Center Pacific is partnering with AFCEA San Diego chapter to host the workshop.

The NAML workshop is an opportunity for researchers from Navy research and development centers and our partner organizations to exchange technical ideas and to come together as a team.

The goals of NAML are:

* To spread awareness of current machine learning research relevant to Naval applications

* To connect machine learning researchers with experts in military requirements

* To build and strengthen collaborations within the defense research community

**Watch this video to hear about the AFCEA purpose.**

<iframe width=1280 height=706 frameborder="0" scrolling="no" src="https://screencast-o-matic.com/player/creleVVcvRh?v=6&ff=1&title=0&controls=1" allowfullscreen="true"></iframe>

Howard Ly

2

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Machine Learning to Predict and Monitor Trouble Ticket Duration

Using Machine Learning to Predict CASREP Occurrence and Trouble Ticket Duration

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