________________________________________________________________________________________________________________________
1 . Manufacturers turn to AI pattern recognition tools to avoid a data overload
The rise in AI focus will help manufacturers improve efficiency through data pattern recognition . By using historical data , AI swiftly analyzes real-time production data , identifying patterns and anomalies . The long-term value of AI and data pattern recognition will provide manufacturers with ongoing root cause analysis , streamlining work , and predicting potential product quality issues by comparing various data points .
As manufacturing systems become more complex , AI-driven data pattern recognition is crucial for sharpening quality control , predicting equipment issues , and optimizing production for fewer defects , higher OEE , and significant cost savings . With Industry 4.0 and the emergence of Industry 5.0 , there will be too much data being generated every second for the human mind to cope with - AI will become an indispensable tool for manufacturers . But workers aren ’ t going anywhere . Despite the rise of automation and AI , humans will also remain indispensable in manufacturing due to their superior decisionmaking , creativity , and adaptability , something AI can ’ t do yet .
2 . AI can further optimize worker performance
As roles evolve , workers will need new skills . Providing them with the necessary tools and training to work alongside , and be augmented by , AI will ensure a productive synergy between human ingenuity and machine efficiency . AI greatly enhances the value proposition of connected worker platforms by empowering the worker with capabilities and insights designed to further optimize their performance .
Take AI-powered search on the factory floor . An unproductive worker is an expensive worker . AI can empower workers to work smarter , not harder by providing them with intelligent search capability that not only grasps their inquiry ’ s intent , but also adapts to human nuances like typos or vague terms . This ensures quick and accurate responses to inquiries such as how to troubleshoot a broken mixing machine with a jammed mechanism . AI makes sure they are presented with the right information at the right time via their smart device .
Or consider the fact many manufacturing workforces are comprised of a diverse set of staff , many speaking potentially different native languages . Intelligent multilingual transcriptions allow manufacturers to ensure critical operational content is available in all the languages of a diverse workforce . AIpowered transcription can break down global language barriers and encourage worker inclusion . This is an intelligent capability that automatically translates the audio from videos into relevant subtitles in the preferred language of the user . Not only does this reduce the effort to create and maintain content - it improves the comprehension and retention of information leading to better safety , quality and productivity .
3 . Reducing waste and ensuring quality control
Minimizing industrial waste while still ensuring quality remains a persistent challenge . Industrial manufacturing waste accounts for at least 50 percent of the waste generated on a global scale . To tackle this issue , AI has emerged as a promising solution to strike a delicate balance between quality control and waste reduction by enhancing our ability to make crucial , intricate , high-volume decisions . With AI-powered systems , manufacturers can now optimize their operations and make more informed decisions , leading to reduced waste and improved efficiency . The IFS AI research found respondents think AI can have the biggest impact on sustainability through designing better flow in manufacturing processes to improve efficiency .
28