Artificial Intelligence is transforming every industry, and manufacturing is no exception. 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 LandingAI and the Association for Advancing Automation to launch a survey on the state of AI-based machine vision.
The survey, published ahead of the International Vision Solutions Conference, 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 AI-based machine vision in visual inspection projects.
Below are four key findings from the survey.
Key finding 1: In a heavily automated sector, manual inspection is still playing an important role with 40% saying their inspection is either completely or mostly manual.
Key finding 2: The confidence level of businesses regarding AI effectiveness is high with 26% saying they are already using AI for visual inspection.
Key finding 3: When it comes to using AI, scarcity of data, complexity of integrating AI within existing infrastructure, and the inability to achieve lab results in production are the top three challenges.
Key finding 4: Most businesses prefer to have ownership of AI projects either by developing in-house or working with a vendor.
