The Internet of Things (IoT) market is estimated to reach 75 billion devices worldwide by 2025. With the big increase in connected devices, it’s becoming more critical than ever for manufacturers to leverage new technologies, such as edge computing, to gather, process and manage IoT data.
Edge computing is growing in adoption and popularity for IoT deployments to manage the data generated by assets on the ground. Edge technologies bring intelligence to raw machine data through AI and machine learning, resulting in improved operational insights.
Whether it is building CNC machines or assembling motherboards, real-time alerts to operators or machines through edge-enabled solutions result in substantial cost savings and new revenue streams.
The edge is the next big lever for digital transformation: The computational demands of emerging applications have increased significantly through the rise of complex data streams, such as streaming video and audio, acoustic or vibration data. Transporting the data sets between edge and cloud defeats the purpose of low-level latency applications—and the cost of transport and storage is prohibitive. Lastly, industrial enterprises would prefer to retain their data in-house.
Edge computing equips factory operations with:
Daihen faced a challenge to make its digital transformation a reality by modernizing factory operations. Leaders at the Japanese industrial electronics firm’s Osaka factory sought faster ways to analyze sensor data from devices measuring material conditions and reduce the need for manual monitoring.
Daihen deployed edge computing software in collaboration with Energia Communications to automate monitoring of its industrial transformers and harness the power of its industrial data to improve efficiency in factory operations. Daihen leveraged an RFID infrastructure to track productivity and installed condition-monitoring sensors.
Within six months of deployment, the Osaka plant achieved 70% coverage with the RFID-based tracking system. Daihen so far has saved about 1,800 hours per year in the manual logging process in addition to reducing levels of inaccurate planning within the manufacturing process. It projects savings of 5,000 hours/year in the Osaka plant.
A nationwide rollout is now set.
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