GenAI in Manufacturing

Module 1: Why Generative AI Matters in Manufacturing

• Big Picture: What “Gen AI” really means—think smarter assistants, not magic robots.
• Value Drivers: Faster problem-solving (e.g., AI-drafted maintenance reports), smarter insights (e.g., anomaly alerts you can trust).

Module 2: Conversational AI & Knowledge Retrieval

• LLMs Simplified: Imagine a digital advisor that speaks English—no coding, just prompts.
• Taming Hallucinations with RAG: Hook your instruction manuals, SOPs and ERP FAQs into the model so answers always reflect your real procedures.
• Business Demo: Live mock-up of an AI chat widget answering “How do I troubleshoot Pump X?” using your own documentation.

Module 3: Predictive Maintenance with Smart Forecasting

• From Data to Decisions: How historical sensor readings become crystal-ball insights—without you writing a single line of code.
• Foundation Models for Time Series: Think of these like “Excel on steroids”—they spot patterns that you might miss in spreadsheets.
• Integration Talk-Through: Plug into your existing IoT platform (MQTT or OPC UA) and ERP (SAP, Oracle)—we’ll map out the data flow, roles, and responsibilities.

Module 4: AI-Driven Quality Assurance

• Visual Inspection Reimagined: Using pre-trained image models to flag defects—no custom programming required.
• Synthetic Data Magic: When you lack enough “real” images of rare defects, Gen AI can generate them for you.

Module 5: Roadmap & Adoption Best Practices

• Integration Strategy: Step-by-step approach to pilot → scale → govern (data, security, change-management).
• Platform Options: Overview of turnkey SaaS vs. on-prem frameworks—what fits your company’s risk appetite and IT stack.
• Governance & ROI: Defining success metrics (uptime improvement, cost savings) and setting up simple KPIs to track impact.
• Next Steps: Building your proof-of-concept, sourcing internal champions, and a curated list of “zero-code” or low-code AI tools to evaluate.