Classification & Remediation of Defects using AI

Many quality control programs are based on digital inspection methods but utilize manual evaluations to classify and remediate defects. While manual inspections are useful in catching defects and errors, they have limitations that can negatively impact the quality, efficiency, and cost-effectiveness of production. When set up properly automated inspection techniques, such as machine vision or artificial intelligence, can empower inspectors by providing more consistent, efficient, and objective quality control. MxD is releasing a proposal to enable manufacturers to make educated and informed decisions about AI based automated inspection systems and increase the adoption of Industry 4.0 practices.

About the Project

MxD is releasing a Request for Proposals to enable manufacturers to make educated and informed decisions about the classification and remediation of defects using AI based digital inspections systems and to increase the adoption of Industry 4.0 practices.

The project seeks to classify various defects across multiple industry sectors, catalog available AI based digital inspection systems, and implement an intuitive automated AI driven digital inspection system in a production environment. Additionally, the project seeks to describe AI based digital inspection implementation methodologies, determine the effectiveness of the system in a production environment, evaluate the Return on Investment from a business perspective, and report the long-term impact of the system performance.

Automating this type manufacturing application using AI technology addresses a wide range of use cases across the automotive, electronics, semiconductor, and industrial sectors. The purpose is to go beyond the typical, binary, go-no-go inspection systems in use today, for example: An AI driven disposition process decision tree to determine if a defective product must be scrapped, repaired, or can be conditionally accepted based on defect threshold parameter limits such as, too big, or too many.

RFP responses are due on or before
Friday, May 19, 2023, 5:00 p.m. CT.

Proposals must be submitted by teams; MxD membership is not required for submission but will be required prior to project award. To facilitate team formation, MxD will compile and disseminate contact information from parties interested in Team Formation during the first month of the proposal period. If you are interested in submitting your contact info to this distribution list, please email

Note: All project work must be performed in the United States.
This project is a TIA Enterprise Project that requires a minimum of 1:1 cost share.

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