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Manufacturing Technology Insights | Sunday, January 01, 2023
By using virtual and augmented reality during the production stage, manufacturers are able to make adjustments or experiment with new design ideas without having to create physical versions of the product.
Fremont, CA: Digitalization is transforming manufacturing. Powered by IIoT, AI, and cloud technologies, Industry 4.0 has reached a critical tipping point in manufacturing. Or manufacturers will fall behind their competitors if they don't embrace digital transformation now. According to a PWC study, manufacturers will spend up to $70 billion by 2020 on technology to meet Industry 4.0 demands. In addition, they will add systems that will improve manufacturing intelligence (MI).
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If you don't understand MI and why it matters, you can't keep up with Industry 4.0.
Understanding Manufacturing Intelligence
Manufacturing intelligence refers to the software solutions that integrate data from your manufacturing operations for deep analytics. IIoT and other technologies are used to analyze big data for these systems. There is a difference between MI and Business Intelligence (BI) - the needs and goals of manufacturing are quite different from those of a business front office.
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The production process is the most important thing in manufacturing. A production line audit ensures that every machine is working properly and producing products as per specifications. Regardless of how many machines generate data regarding their production, if those data are siloed, they are meaningless. Using data analytics, MI can track a factory's entire infrastructure, determine which machines aren't performing to spec, and improve efficiency overall. This information is available to workers in real-time, so issues can be addressed immediately.
Trends in MI
We are seeing some trends emerge as more manufacturers adopt Industry 4.0 technologies. A few of them are:
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. Incorporating IIoT into daily life. It is becoming more common for factory equipment and machinery to be embedded with sensors. Data collected by these sensors is transmitted to the cloud or software, where it can be analyzed for feedback on the production process.
. Virtual and augmented reality. By using virtual and augmented reality during the production stage, manufacturers are able to make adjustments or experiment with new design ideas without having to create physical versions of the product.
. Twins digitally created. It is possible to better monitor and collect data by combining virtual reality and physical components. Using a robotic arm as an example, the virtual arm conducts its task while gathering equipment information to improve predictive maintenance.
. Cloud computing is becoming a more powerful force. More intelligent factories are being created by manufacturers using the cloud. The cloud is also being used to advance robotic solutions, and some of this incorporates IIoT sensors. Smaller factories can reduce their investment costs by outsourcing some of the technology with robotics-as-a-service.
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