Improving Product Quality with AI-based Video Analytics: HPE, NVIDIA and Relimetrics Automate Quality Control in European Manufacturing Facility

Manufacturers are using the power of AI and video analytics to enable better quality control and traceability of quality issues, bringing them one step closer to achieving zero defects and reducing the downstream impacts of poor product quality. Together, HPE, NVIDIA and Relimetrics enable customers to adapt to high production variability and velocity with faster, more accurate, automated inspection processes.

Machine Learning has Significant Potential for the Manufacturing Sector

In this contributed article, Gregory Miller, a writer with DO Supply, explores the ways in which machine learning is being applied in the modern industrial world, focusing on manufacturing. To date, manufacturers have been able to introduce AI into three aspects of their business: operational procedures, production, and post-production.

An Enterprise AI Platform Created to Make Industry 4.0 a Reality

A new complete, full stack solution was introduced to help manufacturing businesses transform their operations to reduce waste, material defects and the overall energy required to create their products. The platform accelerates manufacturing and supply chain digital transformation projects and makes Industry 4.0 a reality. Dell Ventures accelerated the production of this multi-tier, industrial-grade edge-to-cloud-to-edge solution by leading Noodle.ai’s $35 million Series B round last year, joined by previous investor TPG Growth.

Interview: Prasad Akella, Founder and CEO of Drishti

I recently caught up with Prasad Akella, Founder and CEO of Drishti to discuss how factory use of AI technology is gaining a lot of traction, and how his company uses the commercial application of action recognition and AI innovations to automatically digitize human actions inside the factory.

InsideBIGDATA Guide to Big Data for Manufacturing

Manufacturing concerns consistently have sought ways to reduce waste and variability in their production processes to dramatically improve product quality and yield (e.g. the amount of output per unit of input). Further, these companies need a granular approach toward recognizing and correcting manufacturing process flaws. Big data technology provides just such an approach and many hightier manufacturers possess a significant degree of interest and motivation in adopting the big data technology stack.