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Manufacturing Technology Insights | Thursday, October 21, 2021
Leaders in digital transformation should search for collaborative artificial intelligence (AI) tools-products and solutions that utilize and complement the domain knowledge of small and medium-sized businesses.
FREMONT, CA: Smart factory technologies that take advantage of the industrial internet of things (IIoT), autonomous vision systems, edge computing, and AI and Machine Learning can enhance the cost, throughput, quality, and safety while increasing income. Despite the advantages, according to a recent poll, only fice percent of U.S. manufacturers have fully converted at least one smart factory, with the remaining 30 percent reporting ongoing smart factory projects. Smart factory enablement requires AI, and implementing AI in industrial operations is difficult.
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Many systems are built for greenfield (new factory) projects. They do not address sophisticated data management, difficult legacy machinery integration, corporate security requirements, real-time analytics, or the ability to handle hundreds of models in a manufacturing setting. Finding qualified personnel to develop and implement AI is a major issue. Citizen data scientists-subject matter experts with domain knowledge in operations-are frequently enlisted by global industrial companies, which equip them with modern analytical tools.
For manufacturers to accelerate the employments of AI applications, the industry must address several challenges before AI-led digital transformation transitions a factory into a smart factory. Leaders in digital transformation should search for collaborative AI tools—products and solutions that utilize and complement the domain knowledge of small and medium-sized businesses. Predictive analytics solutions tailored to the manufacturing team must be intuitive, simple to learn and use, and allow easy interaction with existing infrastructure. Providing powerful analytical tools to shop floor engineers will enable them to make data-driven operational improvements and lay the groundwork for creating value from AI at scale. In smart manufacturing, a collaborative AI platform that automates data preparation delivers automated feature engineering and promotes interpretability with explainable AI is a must.
One can connect factory assets, processes, and people to realize the smart factory vision of production that is responsive, agile, and self-healing by employing a collaborative AI platform and AI automation.
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