Unlock the Potential of Open AI in Smart Manufacturing
OVERVIEW
1.1 PURPOSE
The key purpose of this article is to help the reader understand the current landscape of Generative AI and potential application of Open AI LLMs ( large language models ) including ChatGPT for industry priority scenarios in smart manufacturing . The article covers the application of Open AI models ( a Generative AI technology ) primarily focusing on aiding product design using code and content generation , process automation using smart assistants or copilots and industrial knowledge management for IOT scenarios .
1.2 EXECUTIVE SUMMARY
Smart manufacturing is the use of advanced technologies and data to optimize the production process , improve product quality , reduce costs , and enhance sustainability . One of the technologies that is transforming the manufacturing industry is Generative AI , which is a type of AI that can create new content and ideas , such as designs , images , videos , music , and text . These systems fall under the broad category of machine learning and are often known as large language models ( LLMs ), a class of foundation models . It can be used to solve various challenges in the manufacturing and industrial sectors , such as 1 :
• Product development and design : Generative AI can explore various design options within specified parameters , such as materials , constraints , safety factors , and cost . This can enable faster and more efficient innovation , as well as more customized and personalized products .
• Customer service automation : Generative AI can generate natural language responses to customer queries , complaints , or feedback . This can improve customer satisfaction , loyalty , and retention .
• Manufacturing ( production ) optimization : Generative AI can analyze production data and identify patterns , anomalies , bottlenecks , and opportunities for improvement . This can enhance operational efficiency , quality control , waste reduction , and resource utilization .
• Supply chain management : Generative AI can forecast demand and supply , optimize inventory levels , plan logistics and transportation routes , and mitigate risks . This can increase the agility , resilience , and profitability of the supply chain .
• Machine-generated events monitoring : Generative AI can interpret telemetry from equipment and machines to predict and prevent failures , recommend solutions , and
1 https :// cloud . google . com / blog / topics / manufacturing / five-generative-ai-use-cases-for-manufacturing and https :// venturebeat . com / ai / ai-is-making-smart-manufacturing-faster-greener-virtual-and-more-real /
Journal of Innovation 45