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Improving production efficiency is the foundation for the manufacturing industry to gain a firm foothold. The manufacturing industry achieves smart operations by introducing AI applications, automatically identifying abnormalities, or making adjustment suggestions, and assisting companies in achieving more accurate adjustments to machines and upgrading equipment. During the process, the traditional manufacturers are transformed into the smart manufacturers.
Artificial intelligence has brought in a new generation of robotics technology: Robotics 2.0. The principal challenge is the transformation from original manual programming methods to true autonomous learning. Faced with this challenge for innovation in AI robotics, how can Taiwan's manufacturing industry best seize the opportunity?
With the global economic development, the demand of the consumer market has driven the vigorous growth of the textile industry. However, under the business model of production-based sales, excessive production has not only caused environmental pollution but has also caused unnecessary waste of resources. Over the past few years, this has led the United Nations and the European Union, to begin to advocate "sustainability" and "environmental protection" as the focus of global development for the next 10 years.
In the era of digitization of science and technology, only by mastering key technologies and continuously following technological changes can we consolidate our competitiveness. Nowadays, packaging machinery combines data connection, unmanned operation, green packaging materials, and safety considerations, and enriches relevant intelligent data technology, so that it can continue to progress in the market.
Taiwan's IBM announced that it has joined forces with a large domestic solution integrator (SI) to identify the pain points that are difficult to integrate between IT and OT in the manufacturing industry, and uses the IBM Smart Manufacturing 5C maturity model as the blueprint. Both parties will provide pre-introduction evaluation services, depending on needs. However, SI will provide OT and IT integration services, or IBM will provide more data-driven AI value-added services.
Smart machinery manufacturers must accelerate innovation, gain the policy resources of the production and innovation platform, develop the domestic industrial acceleration scale group, and the intelligent diagnosis maintenance system (IDMS), which has been successfully introduced into the innovative application of high-tech industries.
Artificial intelligence illuminates the evolution of IoT and promotes three key application areas.
With the advent of Industry 4.0, countries have also adjusted their industrial manufacturing strategies to enhance their smart manufacturing capabilities.
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