Manufacturers have long relied on automation to increase efficiency, reduce costs and waste, and optimize production. Automation helps streamline virtually every aspect of the manufacturing process, from material handling to assembly to inspection. Automated systems help increase output, maintain consistent quality and enhance safety.
Generative AI takes that to the next level by enabling even smarter automation.
Gen AI can help manufacturers improve product design and prototyping so they can respond quickly to changing market demands. Faster design iterations accelerate time-to-market while driving innovation. Manufacturers can also test new processes and identify potential problems without disrupting production.
However, manufacturers must overcome several hurdles to capitalize on the benefits of gen AI. Although manufacturing processes generate vast amounts of data, it can be difficult to ensure data quality and ensure the free flow of data into gen AI systems. Integrating AI with legacy manufacturing systems can also be a significant challenge. Few manufacturers have AI expertise in house, which can delay or even derail AI initiatives.
Gen AI Use Cases in Manufacturing
Digital Twins
Digital twins are simulations of physical objects or systems created using machine learning, virtual reality and other advanced technologies. Manufacturers use digital twins to visualize, test and improve product designs and processes. Digital twins can be updated in real time, enabling faster, more reliable innovation with significantly fewer physical prototypes. Data generated by the product in use or the factory in operation can be fed back into models to provide actionable insights for improving efficiency and productivity.
Predictive Maintenance
AI-powered systems can aggregate and analyze real-time data collected from IoT devices and network-connected equipment to detect and analyze anomalies. Predictive models then provide advanced warning of impending equipment failure, enabling manufacturers to perform preventive maintenance that can cut costs and minimize downtime. Predictive maintenance solutions can also provide manufacturers with insight into the overall health of their connected assets so that maintenance can be performed when it’s most needed rather than on a fixed schedule.
Supply Chain Optimization
By analyzing historical and real-time data across the entire supply chain, gen AI systems can forecast demand and predict and simulate shortages and disruptions. These solutions can then automate procurement processes to help manufacturers ensure they have the right materials at the right time. AI-powered inventory systems can help optimize stock levels in real time to reduce carrying costs and improve cash flow. Gen AI can also help track orders and streamline logistics to ensure timely delivery.
Gen AI Challenges in Manufacturing
Integrating AI with legacy systems is one of the greatest challenges manufacturers face. Many manufacturers maintain legacy systems because they can’t justify the cost of upgrades, but AI solutions may not integrate with older technologies. Manufacturers should determine which systems will need to integrate with AI, which will need upgrades, and the most cost-efficient way of handling the upgrades.
Poor-quality data and algorithms can disrupt operations in an industry that demands reliability. Manufacturers should ensure that datasets are complete and accurate to reduce operational risks and ensure regulatory compliance. They should also take steps to address the cybersecurity concerns that come with increased connectivity.
Gen AI initiatives require specialized expertise in data science, analytics, automation and other disciplines. Few manufacturers have this talent in-house, and finding qualified candidates can be difficult. Manufacturers should identify the skills needed, work with HR and recruiting professionals and upskill existing employees where possible.
How Cerium Can Help
The Cerium team is here to help manufacturers close the skills gap and gain the expertise needed to drive gen AI initiatives. Our proven methodology starts with identifying use cases and developing a clear plan for integrating gen AI into existing systems and processes. Our multidiscipline approach includes data storage and analytics, security, and system upgrades. Let us help you leverage gen AI to reduce costs and waste, increase operational efficiency, and drive innovation.
