CANADA'S LEADING INFORMATION SOURCE FOR THE METALWORKING INDUSTRY

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CANADA'S LEADING INFORMATION SOURCE FOR THE METALWORKING INDUSTRY

CANADA'S LEADING INFORMATION SOURCE FOR THE METALWORKING INDUSTRY

4 key considerations for implementing GenAI in manufacturing

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To get the most out of GenAI, organizations must tie traditional and generative AI capabilities and expectations to their business challenges and objectives. PHOTO by Pexels.

AI is constantly evolving, as is its power to transform manufacturing. Companies that fail to move on GenAI may find themselves with outdated business models, rising costs, inefficient production and the inability to compete in the evolving market. While the options can feel overwhelming, Dell Technologies in its recently published report Generative AI for Smart Manufacturing says there are steps you can take now to move the needle. The experts at Dell advise manufacturers to consider the following four areas to address:

Strategy: To get the most out of GenAI, organizations must tie traditional and generative AI capabilities and expectations to their business challenges and objectives. Setting a strategy should include a collaborative process that helps you identify the problems to solve, determine the data to collect and analyze, and create a roadmap for reaching your goals.

Infrastructure: Modern scalable infrastructure is a critical component for AI success, both at the data source (the factory) and with the high-level computing power and capabilities required to:

• Store, protect and backup the required datasets.

• Train and use the large language models that provide a foundation for GenAI.

• Monitor performance and make recommendations.

• Scale, manage and replicate across the organization

Solutions: Effective solutions are vital for integrating GenAI into your manufacturing operations — for example, systems capable of storing, processing and utilizing large volumes of data. This forms the backbone of GenAI’s functionality. Equally important is the seamless transfer of data and AI models between various storage platforms, from local servers to the cloud, to ensure scalability and accessibility. Compliance and security are also paramount. Enterprises must ensure that all data handling complies with legal standards and is secure, utilizing tools like encryption and secure transfer protocols. By focusing on these solutions — efficient data management, seamless data transfer, security and compliance — manufacturers can prepare to leverage GenAI to its fullest potential.

People: When implementing GenAI in a facility, it’s vital to have the right people trained and accessible. They can either come from within the manufacturing company or be brought in by hiring or partnering with specialists. Identifying the skills and talent needed — and ensuring you have access to them — is essential to achieving the required outcomes, such as cost reductions, faster go-to-market, etc.

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