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Why trusted data is crucial to AI innovation in manufacturing .
By Vinod Ganesan
In the dynamic landscape of modern manufacturing , AI has emerged as a transformative force . It ’ s reshaping the industry , offering unprecedented efficiency and innovation . As we navigate the fourth and fifth industrial revolution , AI technologies are sparking a shift in how products are designed , produced , and optimized .
Data is at the heart of this change . Armed with data from sensors , historical maintenance logs , and other contextual data , manufacturers can use AI to predict how their equipment will behave and when the equipment or a component will fail . AI can even prescribe the appropriate maintenance action at the right time , helping manufacturers to identify potential failures , optimize maintenance schedules , and reduce downtime . It can also be used to forecast product demand using historical data , trends , and external factors like weather and market conditions , generating huge value for manufacturers .
But , whilst AI promises to drive smart intelligent factories , optimize production processes , enable predictive maintenance , and pattern analysis , personalization , and many other use cases , without a robust data management strategy , the road to effective AI is an uphill battle .
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