Google updates on AI applications in the manufacturing industry
Google updates on AI applications in manufacturing industry
While the promise of artificial intelligence (AI) transforming the manufacturing industry is not new, long-ongoing experimentation hasn’t yet led to widespread business benefits. Gartner reports that only 21% of companies in the industry have active AI initiatives in production. However, new research from Google Cloud reveals that the COVID-19 pandemic may have boosted the use of AI and other digital enablers among manufacturers.
Google asked more than 1,000 senior manufacturing executives across seven countries—76% have turned to digital enablers and disruptive technologies due to the pandemic such as data and analytics, cloud, automation and Artificial Intelligence. And 66% of manufacturers who use AI in their day-to-day operations report that their reliance on AI is increasing.
The top three sub-sectors deploying the technology to assist in day-to-day operations are automotive/OEMs (76%), automotive suppliers (68%), and heavy machinery (67%).
Moving from Edge Cases to Mainstream Business Needs
Why are manufacturers now turning to AI in increasing numbers? Google’s research shows that companies who currently use the technology in daily operations are looking for assistance with business continuity (38%), helping make employees more efficient (38%), and to be helpful for employees overall (34%).
It’s clear that Artificial Intelligence and Machine Learning technologies can boost manufacturing employees’ efforts, whether by providing prescriptive analytics like real-time guidance and training, flagging safety hazards, or detecting potential defects on the assembly line.
In terms of specific Artificial Intelligence use cases, two main areas emerged: quality control and supply chain optimization. In the quality control category, 39% of surveyed manufacturers who use AI in their day-to-day operations use it for quality control and 35% for product and/or production line quality checks.
AI is mainly found in quality control and supply chain management
As for the supply chain optimization category, manufacturers said they make use of AI for supply chain management (36%), risk management (36%), and inventory management (34%).
In their day-to-day work, many manufacturers are rethinking about their supply chains and operating models to better accommodate for the increased instability that has been brought about by the pandemic, all while fulfilling the needs of individualized products.
Which factors cause the use of AI to vary by geography?
According to Google’s research, the extent to which artificial intelligence is already being applied today varies quite strongly between geographies. While 80% and 79% of manufacturers in Italy and Germany respectively report using AI in day-to-day operations, that percentage plunges in the United States (64%), Japan (50%) and Korea (39%).
It’s tempting to state this disparity is due to an “AI talent gap.” However, just 23% of manufacturers surveyed believe they don’t have the talent to properly leverage the techonology. Cost, too, does not appear to be a roadblock (21% of those surveyed). Rather, the missing link appears to be having the right technology platform and tools to manage a production-grade AI pipeline.
Looking Ahead: The Golden Age of AI for Manufacturing
Golden Age of AI for manufacturing
The key to widespread adoption of Artificial Intelligence is its ease of deployment and use. As AI becomes more pervasive in solving real-world problems for manufacturers, the industry is moving away from “pilot purgatory” to the “golden age”.
The manufacturing industry is no stranger to innovation, from the days of mass production, to lean manufacturing, and more recently, enterprise resource planning. Artificial Intelligence promises to bring even more innovation to the forefront.
Source: Google Cloud
Read more: How is virtual and augmented reality transforming manufacturing?
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