Detecting Anomalies with AI

Classic aspect using AI in  smart manufacturing.  Had interacted with Fujitsu in the past.

Fujitsu develops AI to detect product abnormalities during manufacturing

By Ryan Daws | March 29, 2021 | TechForge Media,  Categories: Manufacturing,

Fujitsu has developed an AI which can highlight abnormalities in the appearance of products to help detect issues earlier.

Catching problems during production enables intervention before materials are wasted—incurring direct and environmental costs. It also saves on the reputational damage and costs associated with returns/recalls after a defective product is shipped to customers.

The solution uses an AI model trained on images of products with abnormalities. These defects are simulated so images of actual products with issues pulled from a production line aren’t necessary. ... " 

Requirements for Smart Manufacturing

Good overview out of Forrester, which links to further resources.

Smart Manufacturing Requires A Range Of Technologies To Succeed
CIO | Forrester Blogs   by Paul Miller

Principal Analyst Paul Miller introduces The Forrester Tech Tide™: Smart Manufacturing, Q2 2020, and highlights a webinar that will dive more deeply into the research and its findings.
As manufacturing becomes connected, digital and smart, manufacturers find themselves grappling with unfamiliar technologies. In the Forrester Tech Tide™: Smart Manufacturing, Q2 2020, we highlight 20 significant technologies. The report offers clients advice on whether they should experiment with, invest in, maintain, or divest from each of these.

I will be running a webinar on 20 May, during which I will discuss the rationale for the report’s recommendations and take questions from participants. Please do join us.

A set of reports later in 2020 will dive more deeply into a number of the technologies flagged for experimentation or investment. Clients can always see my current research plan at the bottom of this page, or discuss it with their account manager   ... "