Plant controller systems based on static models are not responsive enough to adapt to changes and prescribe actions to insure optimal outcomes. As a result, set points are adjusted every now and then by operators who hunt for good conditions.
AI and machine learning offer manufacturing a chance for new and stable growth. When paired with traditional automation, these technologies can improve efficiency and decrease costs.
This article discusses how legacy manufacturing enterprises can harness the latest technologies, to optimize factory operations without having to ramp up infrastructure investment.
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.
Artificial intelligence (AI) is gaining favor as a solution for quality problems, but many manufacturers struggle with the perceived cost and complexity of implementing new technology.
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.
Automation helps companies achieve greater flexibility and planning reliability, even in the case of multi-variant production. One factor that deters many companies from switching to automated processes, however, is time.
Leveraging artificial intelligence (AI), the manufacturing industry can protect workers better and ensure that all employees wear gear to stay compliant with Personal Protective Equipment (PPE) protocols to avoid costly penalties.
A recycling center customer was looking for a high-performance, industrial-grade Artificial Intelligence (AI) solution that could successfully function in harsh environments. The customer needed an automated solution to help identify certain materials on the recycling line.
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.
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.
As the benefits of main AI elements such as Machine Learning, Data Analysis, and Predictive Analysis are undeniable, what are the few biggest challenges that companies may face while introducing AI to their day-to-day operations?
What's next for the world of CNC operators? An increasing move to incorporate artificial intelligence, or AI, into operations. Over the next several years, CNC machining could see something of a revolution that includes machines that respond to Alexa-like voice commands.
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.
To truly maximize IIoT, manufacturers need a single solution that supports scalable-IIoT deployments and creates a collaborative environment that's data-driven and provides transparency across the entire production process.
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Hexapod micro-motion 6-axis platforms are based on a very flexible concept that can easily solve complex motion and alignment problems in fields including Optics, Photonics, Precision Automation, Automotive, and Medical Engineering.