Rapid advances in artificial intelligence (AI) have the potential to significantly increase productivity, quality, and profitability in future manufacturing systems. (Caveat: The panel did not attempt to disentangle artificial intelligence from machine learning and used the two terms loosely interchangeably during the discussion.) Traditional mass production will give way to … [Read more...] about Opinion– Opportunities and Challenges to Integrate Artificial Intelligence Into Manufacturing Systems: Thoughts From a Panel Discussion
Smart manufacturing
Next-Generation Furniture Assembly by AI and Robots: Team SK2Y: A Winner of the Furniture Assembly Competition at AI–Robot Challenge 2021
The “Furniture Assembly AI–Robot Challenge 2021” is a competition that evaluates the performance of the robot for an assigned furniture assembly task by combining both artificial intelligence (AI) and robot technology. To generate commands such that a robot can execute the assembly instructions, it is essential to develop an AI-based algorithm that can recognize and interpret … [Read more...] about Next-Generation Furniture Assembly by AI and Robots: Team SK2Y: A Winner of the Furniture Assembly Competition at AI–Robot Challenge 2021
Reinforcement-Learning-Based Local Search Approach to Integrated Order Batching: Driving Growth for Logistics and Retail
As an important part of Industry 4.0, a smart warehouse can offer smart tips and operational constraints for users. Improving its work efficiency is a promising growth driver for logistics companies and retailers. Therefore, a reinforcement-learning-based adaptive iterated local search (RAILS) approach is proposed to improve order-picking efficiency for a smart warehouse. A … [Read more...] about Reinforcement-Learning-Based Local Search Approach to Integrated Order Batching: Driving Growth for Logistics and Retail
Toward Lifelong Learning for Industrial Defect Classification: A Proposed Framework
Automatic defect inspection is an important application for the development of smart factories in the era of Industry 4.0. It gathers data from production lines to train a model to automatically recognize certain types of defects. However, the defect types may vary in the production process, and it is difficult for the old model to adapt to new types of defects directly. … [Read more...] about Toward Lifelong Learning for Industrial Defect Classification: A Proposed Framework
