Could Energy-Harvesting Technology Power IoT Devices of the Future?
It's particularly challenging to be too reliant on battery-powered IoT devices in industries like manufacturing and logistics. Many factories now have 24/7 operations, meaning there are no feasible downtime periods for recharging.
Understanding the Role of Machine Vision in Industry 4.0
Today it is being applied to diverse areas such as monitoring processes for predictive maintenance, and robotic guidance that makes it possible for robots to safely work with and respond to human interactions.
Strategies for Optimizing Supply Chain with Automation
The pandemic brought supply chain to the forefront, leading companies to seek AI, analytics, and automation solutions for efficiency and meeting demand. Machine Learning predicts demand and AI/automation boosts quality and monitors events.
5 Ways You Can Improve Your Manufacturing Operations with a Data-First Strategy
By going digital and adopting a data-first strategy, manufacturing leaders can transform their operations and better prepare themselves for the future.
Ten tips for modernising your HMI/SCADA system
Ageing industrial infrastructure can make it difficult to meet daily challenges for industrial plants and manufacturing companies. Fortunately, there are cost-effective ways to solve these challenges.
Patti Engineering and Kettering University Collaborate on Industry 4.0-Enabled Collaborative Robotic Cell for Real-World Learning
Patti Engineering and Kettering University collaborate to create an Industry 4.0-enabled collaborative robotic cell for a new classroom lab to teach engineering and computer science students.
INVENTEC COLLABORATES WITH MICROSOFT TO DELIVER SMART FACTORY SOLUTIONS ON MICROSOFT AZURE PRIVATE 5G CORE
The solutions integrate Inventec's 5G private network solutions, NEXCOM's top notch AIoT (AI + IoT) Industry 4.0 cross-border integration systems and solutions, and Microsoft HoloLens to build smart factories.
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.
GF Raises the Bar for Sustainability, Efficiency with Expansion in Singapore
In today's world, a semiconductor fab's performance isn't only measured by wafer output and yields, but also by how efficiently and sustainably it uses natural resources, and how effectively it minimizes the impacts of manufacturing on its neighborhood.
Smart Manufacturing - A Layered Approach to Digital Transformation
One of the main goals of digital transformation is to transform the shop floor into smart manufacturing to help manufacturers to manage their core production operations digitally to maximize the production by minimizing machine downtime and quality losses.
Outlook for Engineering Technologies in the Next 5 Years
Manufacturing has become more ambitious about implementing new technologies than ever before, so incoming innovations will make considerable waves throughout the industry. Here are five of the most impactful engineering technology trends that will define the next five years.
Digital transformation: How manufacturing is riding the cloud to new heights
Today, companies are hooking into cloud technology and continually digitizing operations. As a result, they're able to better handle disruption and dramatically advance efficiency and initiatives across their organizations.
5 ERP Capabilities That Will be the Most Important to Manufacturing Executives of the Future
A robust and tailored-for-you ERP becomes the hub of your organization and can inform its future through data-driven insights, predictions, and actions.
How SASE Helps Overcome Security & Connectivity Challenges In Manufacturing
The manufacturing industry is undergoing a major transformation. Everything from production to supply chain to logistics is getting digitized and technologies like Robotic Process Automation (RPA), AI and the Internet of Things are ushering in a new era of smart factories.
SUPPLIER SELECTION FOR CRITICAL MOTION CONTROL APPLICATIONS
In this article, I attempt to arm manufacturers with the questions that they need to ask to ensure that the motion control solution option chosen is right first time and up to the job. These questions should ideally focus on not just capabilities but also values.
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Automation & IIoT - Featured Product
MOTION CONTROLLERS FOR MINIATURE DRIVES AND MICRODRIVES
FAULHABER has added another extremely compact Motion Controller without housing to its product range. The new Motion Controller is ideal for integration in equipment manufacturing and medical technology applications. With 36 V and 3 A (peak current 9 A), it covers the power range up to approx. 100 W and is suitable for DC-motors with encoder, brushless drives or linear motors.
