Enhancing gigafactory efficiency and EV battery quality through a holistic approach
The automotive industry is experiencing changes to meet high global environmental standards. A major trend in automotive is the implementation of new drive concepts based on holistic manufacturing analysis powered by artificial intelligence. Generally, a holistic approach has been discussed for the production of batteries…
Quality 4.0 – advanced technologies to maximize product quality
“Quality 4.0” refers to smart and digital methods of controlling the quality of products during and after manufacturing, which are crucial components of Industry 4.0. Quality 4.0 demonstrates new technologies such as Machine Learning/Artificial Intelligence and connected devices for achieving manufacturing operational excellence and maximizing…
Recalls causing loss of market share and reputation – How to improve Quality and Avoid Recalls using AI technology?
A product recall is the process of replacing defective goods for consumers. Each year, manufacturers recall millions of products, from all types of consumer electronics to the automotive industry. How to improve Quality and Avoid Recalls using AI technology? More than just replacing of…
AI Analytics: Improve Your First Pass Yield by integrating all your data into a unified digital twin database
“First pass yield” (FPY), is defined as the % of units that pass the first time the test of a particular process divided by the total number of units tested during the period. In other words, it measures the quality and efficiency of a manufacturing…
AI root cause analysis to quickly identify product and process errors in manufacturing
Root cause analysis objective is to understand the root cause leading to gaps at manufacturing process and extract insights to reduce faulty units and inefficiency. AI-powered root cause analysis is a game changer in improving quality and problem-solving. It uses smart algorithms that show exactly…
