While still in its early stages, generative AI can provide powerful optimization capabilities to manufacturers in the areas that matter most to them: productivity, product quality, efficiency, worker safety and regulatory compliance. Generative AI can work with other AI models to increase accuracy and performance, such as augmenting images to improve quality evaluation of a computer vision model. With generative AI, there are fewer “misreads” and overall better-quality assessments.

Let’s look at five specific ways IBM® delivers expert solutions that have helped real clients incorporate generative AI into future operations planning.

1. Training validation

Worker training is an important part of creating a safe, efficient manufacturing environment, but it’s a time drain on managers. Generative AI can watch videos and track worker training steps, including noting specific events and validating proper completion. Generative AI then can summarize the results, including time stamps for managers  to review the event—saving time for everyone. In highly regulated industries, having “proof” beyond a certificate will improve workforce readiness and operations. Early testing suggests generative AI could reduce training time by about 30% and boost training completion and certification by 25%.

2. Assisting workers accessing SOPs

Workers accessing standard operating procedures (SOPs) often have tons of questions, especially in complex plants, which can have more than 3,000 SOPs. Getting quick answers with visual and audible support from generative AI can improve operational efficiencies by around 15% and increase end-user problem solving by as much as 90%. Being able to query and confirm operational steps reduces time consumed by other workers, increases the confidence of junior staff and improves overall adherence to procedures.

3. Verifying line set-up

In some industries, set-up and startup can be very complex tasks, which can lead to significant economic consequences if not handled correctly. One example is setting up line clearance in biopharma manufacturing, where properly executed line clearance can mean the difference between a high-value batch of medicine sold or costly scrap. Generative AI can review videos to provide automated verification of manufacturing line set-ups, checking and clearing the correct production run setup. Coupled with video and computer vision, generative AI can proactively augment workers’ manual checks, substantially reducing rework and decreasing set-up errors by about 75%. 

4. Enhancing quality assurance processes

Many industries are already using AI and computer vision to check quality. Generative AI can improve the fidelity of images that are then reviewed for quality assurance. Identifying and summarizing defects with mitigation strategies helps improve overall first-pass quality and could drive an 80% increase in quality error detection over other methods. Enabling workers to quickly tweak a manufacturing setting to eliminate quality issues can greatly lower the subsequent number of quality issues, improve throughput and enhance market reputation.

5. Maintaining regulatory compliance

Regulatory fines are no joke and can cost manufacturers millions of dollars each year. And as more countries create regulatory bodies and issue regulations, global businesses face an ever-changing, complex environment. The ability to check current processes and policies against regulatory databases for needed updates will increase adherence, reduce fines and avoid potential public embarrassment of missed requirements. Generative AI can drive a 25% reduction in fines and a 60% improvement in compliance using real-time text and spoken-query access to regulatory bodies to assist end users. 

Now is the time to maximize your use of generative AI, and the experts at IBM Consulting® can help you quickly and confidently design and scale cutting edge AI solutions and automation across your business. ​

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