Tag: AWS for Industrial

Introduction With the rapid development of the Internet of Things (IoT), enterprises aim to efficiently integrate, configure, monitor, and manage numerous edge devices. These devices and server systems must be highly secure and reliable, as they often become targets for hackers. Regular reviews, security encryption updates, and robust authentication and authorization mechanisms are necessary to […]

In the rapidly evolving automotive industry, manufacturers and suppliers must proactively address the challenges of managing vast amounts of data and documentation to streamline operations. These challenges include paper documents, disparate document versions and folder structures, collaboration with other plants, and finding important information when needed, especially when it comes to mitigating the disruptive impact […]

The manufacturing sector is undergoing a transformative shift driven by smart manufacturing principles and Industry 4.0 technologies like the Internet of Things (IoT), artificial intelligence (AI), and advanced analytics. These cutting-edge trends present opportunities for boosted productivity, accelerated innovation, and competitive advantage. However, manufacturers face looming challenges like labor shortages, an aging workforce, and the […]

This blog is the second in a two-part series that distills some of the most important best practices to help organizations accelerate the implementation of an Industrial Data Fabric (IDF) solution on Amazon Web Services (AWS) and increase the value it brings enterprise-wide. The best practices are organized by stage, as shown in figure 1 […]

Industrial Data Fabric (IDF) solutions on Amazon Web Services (AWS) enable manufacturing and industrial companies to build the foundation for digital transformation to help optimize operations. IDF helps align different data types in the time domain with context as it combines many disparate data sources like time series data from machines, maintenance data from EAM […]

In the competitive field of industrial operations, minimizing downtime is crucial for financial success. The challenge lies in managing complex data spread across various systems within industrial environments. Quickly identifying and solving issues without advanced analytics can be difficult. Operators often spend time consulting manuals to diagnose problems and follow protocols. Automation can streamline this […]

Manufacturers are constantly seeking ways to streamline operations and maximize productivity. With the advent of generative AI, manufacturing companies now have powerful capabilities to boost efficiency across various aspects of their business. From accelerating product development and assembly to extending equipment lifetimes, minimizing downtime and improving operational equipment effectiveness, generative AI has potential to revolutionize […]

Are you ready to discover the latest innovations in the process industry? Attend ACHEMA – the leading process industry event – on June 10-14 in Frankfurt, Germany. The event brings manufacturers and service providers from over 50 countries together to explore, experience and discuss offerings for chemical, pharmaceutical, and biotech research and manufacturing as well […]

The traditional approach to programming industrial automation systems, such as programmable logic controllers (PLCs) and robots, has been devoid of modern software development best practices. Meanwhile, as the industrial landscape evolves towards greater factory automation, the management of automation software becomes crucial. Implementing DevOps methodology on cloud platforms like Amazon Web Services (AWS) can significantly […]

In the high-stakes arena of manufacturing, where product quality can make or break market reputation, using visual intelligence effectively remains the linchpin of excellence. Visual intelligence, in this context, refers to the application of artificial intelligence (AI) precision to enhance visual quality inspection (VQI), seamlessly integrating visual data with operational metrics like overall equipment effectiveness […]