Why the Conventional Deep Learning Model is Broken
The conventional deep learning model is a supervised model. It takes months of time to develop and train the model before it is ready for the production line. Here, Karina Odinaev explains why the conventional deep learning model is broken and what the alternatives are.
Smarter Manufacturing: Improving Safety and Efficiency With The IoT
Wireless connectivity enables manufacturers to more easily rearrange their production facilities to meet specific needs, minimizing costly downtime between production runs for multiple clients.
Unleashing the Potential of Generative AI for Unprecedented Success in the Manufacturing Industry
By leveraging Generative AI, manufacturers can initiate a wide array of use cases in areas such as customer service, product and quality control, supply chain, logistics, predictive maintenance, marketing and sales, finance, compliance and legal, and research and development
Why 3D Metal Printing Is Key to the Future of Aerospace Engineering
The aerospace industry constantly pushes the boundaries of what's possible, and the demand for advanced manufacturing techniques has never been more critical. This pursuit of innovation has led to a significant shift toward 3D metal printing.
10 Areas Manufacturers Might See an Impact from AI
AI can be programmed to learn from the data ERP software gathers to make deeper and more accurate predictions regarding customers, buying habits, inventory levels, markets, material purchasing and more.
Strengthening Cybersecurity in Manufacturing: The Path to a Defensible Architecture
Manufacturing is at the forefront of technological advancements, leveraging operational technology (OT) to streamline processes and improve productivity. However, this digital transformation comes with its fair share of cybersecurity challenges.
Transforming Logistics and Warehousing
The logistics industry, like many others, is focusing more and more on meeting sustainability goals. This is why we can expect companies to prioritize eco-friendly solutions to address their carbon footprint.
How Investments in Supply Chain Technology, Analytics and Visibility Strategies Can Improve Manufacturing Organizations
It's crucial to prioritize data management before jumping into implementing analytics. Because different departments and processes produce different data types, a common data language is a good place to start to help structure the data and break down silos.
The Use of Gearboxes in Warehouse Automation
It's crucial to prioritize data management before jumping into implementing analytics. Because different departments and processes produce different data types, a common data language is a good place to start to help structure the data and break down silos.
Additive at Scale Uses Essentium Technology to Create an Asset Tracking Solution in 60 Days
Using the Essentium High Speed Extrusion (HSE™) 180 ST 3D Printing Platform and Essentium PCTG-Z, Additive at Scale partnered with Blues Wireless to design and manufacture 100 pilot units for an asset tracking solution for a multinational chemical company in just 60 days.
Three Key Takeaways for OT Leaders from the National Cybersecurity Strategy
The National Cybersecurity Strategy released earlier this year takes a deeper dive into the comprehensive efforts that the administration is making in order to bolster cybersecurity. And it emphasizes the need for public and private collaboration.
Why Data Contextualization is Critical During the Digital Transformation Era
Data is the critical driver of change, but even the highest quality data can't drive change in a vacuum. Simply gathering and accessing data is not enough-manufacturers must leverage it in context to make decisions that enhance value in times of digital transformation.
Precision Tools Hot Off the Press at Paul Horn
Tübingen-based precision tools manufacturer Paul Horn GmbH is testing the boundaries of additive manufacturing. Behind this venture is a push to gain the competitive edge and offer customers the best possible solutions.
Glass Manufacturer Modernizes Plants to Extract Value from OT Data from Edge to Cloud
They aimed to adopt a "hub and spoke" architecture to collect OT data, analyze it locally to make improvements, and share it with centralized enterprise and cloud systems for advanced analytics, machine learning, and AI across the business.
SCARA Robot Sorts Recyclables Using a Simple Conveyor Speed Feedback System
As Everest Labs was developing their system to be sold to recycling centers worldwide, they found that their robot needed speed feedback in order to track the recyclables on the conveyor, and therefore needed a simple way to install conveyor speed feedback on a gear motor.
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