What are the key use cases of SAP AI in manufacturing?

SAP AI provides transformative use cases in manufacturing, leveraging AI to optimize processes and improve efficiency. The correct answers are AI-driven predictive maintenance, automated quality control, and AI-powered production scheduling, as these are explicitly documented as key use cases in SAP’s manufacturing solutions.

SAP documentation highlights: “SAP AI in manufacturing supports predictive maintenance, quality control, and production scheduling to enhance operational efficiency and reduce costs.” AI-driven predictive maintenance, supported by SAP Digital Manufacturing Cloud, uses “machine learning to predict equipment failures and schedule maintenance proactively,” minimizing downtime. Automated quality control leverages AI to “analyze production data in real-time” and “detect defects automatically,” ensuring product quality, as seen in SAP S/4HANA Manufacturing. AI-powered production scheduling optimizes “resource allocation and production timelines” by analyzing demand and capacity, supported by solutions like SAP Integrated Business Planning.

The incorrect options—manual equipment failure analysis and handwritten production reports—are not AI-driven. Manual equipment failure analysis contradicts SAP’s automation focus, and handwritten production reports are outdated practices replaced by digital solutions. SAP’s manufacturing case studies, such as those involving SAP Digital Manufacturing Cloud, confirm the relevance of the selected use cases.