Quality Control and Reliability Engineering (QCRE) Division Data Challenge Competition

Eligibility Criteria

Individuals or teams of a maximum of four members.
At least one of the team members must be an active member of the Institute of Industrial & Systems Engineers (IISE) and Quality Control & Reliability Engineering (QCRE) division.
Each team can only participate once.
Each team should submit a Notice of Intent Form to enter the competition (check details in the Notice of Intent section).
Completing Steps 1-3 in the Submission section is required for any team to be eligible as a finalist.
Participating teams are required to publicly release their solutions, including source code and trained model weights, on open-source platforms under the MIT license.
Finalist teams acknowledge that the competition organizers will publish their technical papers, solutions, source code, and trained model weights on the official competition GitHub page.
Participants must not share the challenge data publicly. Instead, they should refer to the original data request link provided by the competition organizers for access and distribution guidelines.

Notice of Intent

Each team must submit a Notice of Intent Form by March 14, 2025, through https://forms.office.com/r/ics3Lx9y6V to express their interest in entering the competition. The data will start to be released to each team on a First Come First Serve. The form requires the following information: Team members, Institution, Main point of contact (name and email address), and Copyright release agreement.

Submission Guidelines

Step 1: Initial Submission

Participating teams or individuals must submit the following files to iiseqcredcc@gmail.com and copy all the Chairs of the Competition Steering Committee no later than April 14, 2025:

The source code for model development and training.
The source code for model prediction (“predictions.py”).
The trained model weights.

File Structure

The submitted files should follow the sturcture below:

Source Code

|- DataFile

|- train_data
|- test_data

|- trained_weights
|- train.py
|- predictions.py

The primary script for generating predictions must be named “predictions.py”. This script should be capable of directly loading the trained model weights, reading DICOM files from the test_data folder or any other designated held-out test dataset, and producing the corresponding predictions.

It is imperative that the prediction script “predictions.py” runs without requiring any modifications. Any necessary software dependencies should be explicitly stated in the submission. Additionally, a ReadMe file must be included, providing clear instructions on how to execute the code.

Step 2: Technical Report Submissions

All finalists will be required to submit a technical report (not exceeding five pages, excluding references) by May 15, 2025. The report should include the following sections:

Team Members: Names, affiliations, and roles.
Introduction: Overview of the problem and motivation.
Methodology: Description of the approach, models, and techniques used.
Data Analysis/Result Discussion: Insights derived from the data and model performance.
Conclusions: Summary of findings and implications.

Additionally, the submission email must include:

A list of team members, including their full affiliations and contact information (email and phone number).
Identification of one team member as the primary contact for the team.

Email your submission Data Competition steering committee.

Step 3: Finalist Presentation at the IISE Annual Meeting

Finalist teams must showcase their work at the 2025 IISE Annual Conference & Expo. At least one team member from each finalist team is required to register for the conference and present their technical details during the QCRE Data Challenge Competition showcase session.

Evaluation Process

The Competition Steering Committee will assess submissions based on the files specified in Step 1 of the Submission section. Only teams that have submitted all the required files in Step 1 will be considered for evaluation. The evaluation committee will include at least one representative from the data sponsor partner with domain expertise.

The model performance will be measured based on
Score = Mean Average Precision (mAP)@0.5

mAP@0.5 indicates mean average precision at IoU threshold of 50% for the object detection tasks.

Selection Process

A maximum of four teams with the highest Score will be selected as candidate finalists.
Finalists will be invited to proceed with Steps 2 and 3 outlined in the Submission section.
Among the finalist teams, those who successfully complete all three steps will be ranked based on their Score, and the top four teams will be awarded 1st to 4th place prizes accordingly.

Important Dates (Deadlines)

Notice of Intent: March 14, 2025, (Data release based on receiving Notice of Intent)
Data will be released upon receiving the Notice of Intent and no later than March 14, 2025.
Deadline for submission of the results: April 14, 2025
Notification to the finalist teams: April 21, 2025
IISE Annual Conference & Expo, May 31 – June 3, 2025

Recognition

A maximum of the top four teams will be selected as finalists and will receive both a certificate and a monetary award based on their ranking. All the eligible finalists will also be recognized in the QCRE town hall meeting. If a team is unable to meet any item in the Eligibility section, the team may be excluded from the finalist selection. In this case, fewer than four teams may be awarded.

The 1st prize comprises a certificate and a cash prize of $1,000.
The 2nd prize comprises a certificate and a cash prize of $500.
The 3rd prize comprises a certificate and a cash prize of $200.
The 4th prize comprises a certificate and a cash prize of $100.

Committee Chairs

Qing Li, Ph.D. in Statistics
Assistant Professor
Department of Industrial and Manufacturing Systems Engineering
Iowa State University

Haifeng Wang, Ph.D.
Assistant Professor
Department of Industrial and Systems Engineering
Mississippi State University

Syed Hasib Akhter Faruqui
Assistant Professor
Department of Engineering Technology
Sam Houston State University

Conflict of Interest Policy

Societies and divisions must follow standard conflict of interest guidelines. Those guidelines include, but are not limited to:

Officers and Board members of the Division should be ineligible for awards during the period of their service, without approval by the Senior VP for Technical Operations (SVP). Exceptions may only be made by the SVP when awards are time sensitive, and the impacted board member(s) or officer(s) must recuse themselves from the award process. For awards that are not time-sensitive, the nominee should wait until their Officer or Board service is complete to be nominated.
The awards committee (or judging committee) should not include members who have either a personal or professional relationship with the nominees. For example, a faculty member should not be judging a paper competition where a participant from the same university is a nominee for best paper award.
The awards committee (or judging committee) should actively change its membership on a rotating basis from year to year to ensure fairness, equity, and diversity. That is, some members of the judging committee should roll off the committee and new members should roll on.