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IIC - Factory Automation Platform as a Service (FA-PAAS) Testbed
In recent years, amid increasingly intense global competition in the manufacturing industry, there has been a growing demand for more rapid product development and market introduction, quality improvements and shorter lead times in order to quickly respond to the rapidly changing market environments and management environments through the introduction of new technologies and collaborations between companies. In this backdrop, there has been a growing expectation for overall optimization that uses data related to manufacturing in the increasingly global supply chain to connect the front lines of manufacturing with management, suppliers, and customers. This in turn has given rise to a need for secure connections between a variety of devices in FA environment and cutting-edge IT services (e.g., Big Data and the cloud) and for the accelerated development of applications in the field of next-generation factories connecting business-to-business (B2B) applications unleashing real economic value to effectively compete in the global marketplace.
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Wind turbines using digital technology
Issues involved in expanding commercialization of wind powerIn 2015, the worldwide capacity of renewable energy facilities exceeded that of coal-fired power.*1 With the aim of creating a low-carbon society, in July 2012, Japan put into effect the feed-in tariff scheme for renewable energy, stimulating the construction of solar and wind farms. In 2016, the full liberalization of the electrical retail business resulted in an increasing number of companies planning either to enter the power generation field or to expand their business. These market conditions engendered a need for the development, design, manufacturing, and sales of wind turbines optimized for Japan's environmental conditions. Utilities considering entering the field of wind power also sought assistance in the streamlining of maintenance and other such business operations.
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Predictive maintenance of medical devices based on years of experience and advan
Failure prediction by human operators requires advanced skills, and the limited number of experts cannot monitor all MRI systems around the world. "Corrective maintenance" for repairs after breakdowns has also become inevitable.
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