The AI Imperative: Crafting Your Manufacturing Future
How does a business begin to build a compelling AI case? It starts with a problem worth solving. Here is how businesses can leap onto the AI train with a strategy that is as pragmatic as it is ambitious.
How ML helps manufacturers maintain safer workplaces
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This article covers the concept of machine-learning in manufacturing and highlights four use cases of ML improving workplace safety.
IoT in Manufacturing: Seizing the Opportunities Amid Challenges
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Now more than ever, manufacturers are integrating new technologies, such as IoT, cloud computing and analytics, and AI and machine learning into their production facilities and operations.
Building Trust in AI/ML: The Key to Unlocking its Potential in Manufacturing
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Manufacturers are adopting AI/ML to increase efficiencies and cut costs. Using AI/ML to monitor and analyze plant operations reveals production chokepoints, potential equipment failures, and areas where automation can streamline operations.
Three Eras of Machine Learning ~ a New Paradigm for Quality Inspection
Simple rule-based algorithms have been used in the visual inspection market for many years, but as their limits have become more apparent, the need for more sophisticated software has grown.
Predictive Quality Analytics in Manufacturing: How AI and Machine Learning are Transforming the Industry
With predictive analytics quality management, manufacturers may now identify and avoid quality issues before they arise by utilizing cutting-edge technology like AI and machine learning (ML), which has significantly improved productivity and profitability.
Strategies for Optimizing Supply Chain with Automation
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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.
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.
AI & Machine Vision based Automated Weld Defect Detection for Manufacturing Industry
Purpose-built solution AI and machine vision solution on Intel® edge processors are helping manufacturers successfully adapt the defect detection technology and expand it to address broader Industry 4.0 use-cases.
AIoT and Edge Analytics: a Powerful Combination
Swedish philosopher Nick Bostrom once said, "machine intelligence is the last invention that humanity will ever need to make". AI decision making, with real time communication and data analytics, has the ability to transform the way manufacturers understand machines.
How factories Can Build Capacity and Improve Manufacturing Processes with ML
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Without making wholesale production changes, factories can improve process efficiency with machine learning (ML). ML can increase production capacity by up to 20% while lowering material consumption rates by 4%.
5 Ways Machine Learning Is Improving Manufacturing
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Artificial intelligence (AI) is one of the fastest-growing technologies in the business world today. AI is a broad umbrella, covering many specific technologies, and machine learning is one of the most promising of these.
The Impact of AI and Machine Learning Technologies in Manufacturing
New data- and ML-based business models will become more commonplace, so early adopters will have a competitive advantage. Machine learning will happen both in the cloud and on the edge, i.e., directly on or next to production machines and sensors.
Enhancing Predictive Maintenance with Machine Learning
There are a number of ways to maintain industrial machinery. If you search around, you will most likely come across these terms: preventive maintenance and predictive maintenance.
The Next Era of Automation Is Intelligence
We are entering a new manufacturing era defined by AI, machine learning and vision, enabling us to teach machines to adapt and learn plans and move us toward a true "Lot Size 1" utopia. Automation's next era will be defined not around volume, but around intelligence.
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