Of the many use cases in manufacturing, visual inspection—a task that involves using human eye or machine vision to verify if a product is free of defects or if parts are correctly assembled—is well-suited for AI. According to a study by McKinsey & Company, AI-powered quality inspection can increase productivity by up to 50% and defect detection rates by up to 90% compared to manual inspection.
Given these benefits, have businesses started using AI in visual inspections? If so, what is the level of adoption, and what are the challenges? These questions and more drove Landing AI, an industrial AI company, and the Association for Advancing Automation to launch this survey on the state of AI-based machine vision.
The survey polled 110 companies from the manufacturing and machine vision industry with both multiple and single choice questions. Respondents who took the survey perform a variety of roles and include C-suite executives, automation engineers and plant managers. One main takeaway is that businesses have high confidence in the effectiveness of AI, and a growing number of companies are already using deep learning-based machine vision for automated visual inspection.
In this report, we will highlight four key findings, detail those discoveries, and provide analysis.