Predictive maintenance can identify and correct potential issues to prevent unexpected breakdowns leading to reduced costs, optimized maintenance schedules, and data-driven decision-making. By leveraging wireless connectivity (such as Wi-Fi 6/6E & Bluetooth 5) and embedded modules, predictive maintenance solutions can use artificial-intelligence to keep machinery running smoothly and remotely monitor performance.
Maximize your production line with targeted maintenance. By continuously monitoring your machinery's health, ensure operational failures are caught and resolved before they escalate.
Gain complete visibility and real-time data to make informed decisions with wireless IoT ecosystems, from wireless modules, embedded systems, IoT sensors and gateways.
Fortify your workplace safety and well-being with preventative risk detection. IoT devices alert you at first signs of hazards, reducing the probability of accidents by up to 40%.
Achieve peak performance with machinery that operates flawlessly. Wireless IoT devices help your equipment to run without hiccups, increasing throughput and quality.
Consumer electronics have advanced significantly in recent years, resulting in the integration of processing and connectivity features into industrial equipment. This has led to the creation of Industrial Internet of Things (IIoT) and increased intelligence in devices like pumps, motors, generators, and more. Reliable maintenance is crucial, as downtime can cost millions of dollars per hour.
Read our white paper to learn more how sensor tech and wireless connectivity directly contribute to saving costs, time, and resources in a variety of use cases.
A smart factory never sleeps, every machine is synchronized to 24/7 production. Today, through the power of predictive maintenance, unplanned downtime once a major obstacle to productivity, is now being prevented by IoT devices. These devices, equipped with Wi-Fi, Bluetooth, LoRaWAN, and wireless system-on-modules, don't just watch over the machinery; they gather and wirelessly transmit critical sensor data, allowing operators to monitor the factory's health in real-time.
Operators can now detect potential issues before they escalate, scheduling maintenance without interrupting production flow. The result? Reducing maintenance costs and unplanned failures by up to 50%.
Key Ezurio Advantages:
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The manufacturing industry is always on the lookout for ways to optimize operations and reduce costs. Unplanned equipment downtime is one of the largest headaches in the industry as it not only impacts productivity, but also incurs significant costs for emergency repairs and parts. Manufacturers are leveraging predictive analytics by AI and machine learning to accurately predict equipment failures and optimize maintenance schedules.
Read this paper to learn how the integration of advanced AI and machine learning in predictive maintenance helps enhance manufacturing operations.
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Artificial intelligence and machine learning are transforming predictive maintenance in manufacturing. Using advanced analytics, IoT sensors, and real-time data, facilities are enhancing operational efficiency and reducing downtime.
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Even machinery that was not designed with the IoT in mind has data waiting to be tapped. Legacy motors, assembly tools and more can be reborn as smart devices that tell you exactly when they need serviced. This is predictive maintenance.
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