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Unpacking all things Industry 4.0, automation, and digital manufacturing technologies.
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- That is the big question our innovations director, Yanesh Naidoo, attempts to answer as he dives into some of the possibilities for modern manufacturing. In this article, he shares not just hypothetical, science-fiction scenarios but real solutions and actual use cases that are starting to change the way that production facilities operate in the age of AI.
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- The arrival of Industry 4.0 has allowed organisations to collect – and analyse – more data than ever before. However, many people fail to understand the mindset shift required and how to start using data to make the best decisions for their organisation.
- Cobots, or collaborative robots, are a type of industrial robot designed to work in close proximity to humans in a shared workspace. But while cobots are designed to work with you, they don’t always work for you – and their effective use will depend entirely on the production environment concerned. In this article, we’ll first unpack their history and purpose, consider the pros and then dive into the cons for various use cases.
- Today, the automated guided vehicle, or AGV, is a common sight in warehouses and factories worldwide. It’s both a practical and flexible transport solution for applications from logistics to manufacturing. In this article, we take a closer look at the specific use case of AGVs in a production environment.
- As the global shift towards electric vehicle (EV) production accelerates, vehicle manufacturers are navigating the complexities of this emerging industry. Meanwhile, governments are responding by introducing regulations to ensure safety and quality in EV assembly.
- As we stand bewildered by the pace of the Fourth Industrial Revolution and the juggernaut of Artificial Intelligence, many workers find their job security increasingly threatened by new technologies.
- For years, Industry 4.0 has been a buzzword promising a digital revolution in manufacturing. However, many manufacturers have been slower to adopt than expected – missing real opportunities to improve efficiencies and productivity. This article aims to clear up some misconceptions and provide a practical roadmap for implementation.
