Use cases for AI in manufacturing you can apply right now
If you’re not using AI in manufacturing yet, you’re missing out on the benefits of artificial intelligence in manufacturing—from predictive maintenance to quality control. In Rockwell Automation’s 2025 State of Smart Manufacturing Report, 95% of manufacturers have either invested, or plan to invest, in AI/ML and GenAI or Causal AI in the next five years.
Whether you are new to AI or already using it in your production environment, there are use cases for AI in manufacturing you can apply right now.
Van Meter Solution Architects Karl Schmidt and Toni Etten will guide you through the steps you can take to Watch from the start or use the guide below to find the most relevant sections for your current state of AI adoption.
Smart Solutions Sessions: All in on AI in Manufacturing
Learn practical AI use cases for manufacturing, including predictive maintenance, quality control, and production optimization. Presented by Van Meter Solution Architects Karl Schmidt and Toni Etten.
CHAPTER GUIDE
Why AI in Manufacturing Matters?
AI in manufacturing is no longer a future concept. It’s happening now. From small pilot projects to full-scale data science teams, manufacturers are investing in AI to boost productivity, improve quality and build resilience. This chapter explores how AI is helping companies adapt to market shifts, empower their workforce and lay the foundation for predictive, self-aware operations.
Where AI in Manufacturing Fits in the Technology Stack
From enterprise planning to the shop floor, AI is transforming every layer of the manufacturing tech stack. AI is helping manufacturers optimize supply chains, predict equipment failures, fine-tune production through adaptive control and more. See how forward-thinking companies are using AI to stay ahead.
AI in manufacturing impacts every layer of the technology stack—from enterprise planning to the shop floor.
What are the Challenges with AI in Manufacturing?
AI holds massive potential, but manufacturers often struggle with fragmented data and unclear starting points. From aligning AI with business goals to the time-consuming process of data wrangling, this chapter breaks down the biggest hurdles manufacturers face when using AI in manufacturing. Learn how to avoid common pitfalls and set your team up for success with a structured, ROI-driven approach.
AI on the Manufacturing Floor
AI in manufacturing enables smarter, faster decisions—especially in areas like predictive maintenance and AI for quality control—without overhauling your entire operation. From reducing product giveaway in bottling lines to predicting air compressor failures and maintaining sensor accuracy in high-speed production, this chapter shows how manufacturers are using AI to cut costs, prevent downtime and improve quality.
Why LogixAI Is Essential for AI in Manufacturing
LogixAI brings AI-driven control and monitoring directly into your manufacturing processes without replacing your engineers. It continuously learns from real-time data to detect anomalies, predict outcomes and even adjust variables automatically to keep operations within optimal ranges. This chapter explains how LogixAI helps manufacturers simplify complex monitoring tasks, improve sensor reliability and achieve tighter control with less manual oversight.
Predictive Maintenance AI: How Manufacturers Reduce Downtime
Predictive maintenance powered by AI helps manufacturers move from reactive firefighting to proactive problem-solving. This chapter introduces FactoryTalk Analytics Guardian AI, a tool that uses existing plant devices, like PowerFlex drives, as smart sensors to detect early signs of equipment failure. This chapter also explores how tools like Fiix CMMS, Asset Risk Predictor and AI systems like Microsoft Copilot and Chat GPT work together to digitize maintenance, detect risks early and recommend prescriptive maintenance actions.
Predictive maintenance AI tools like GuardianAI help manufacturers prevent downtime.
The Art of the Possible
Looking for a real-life example of a successful AI use case? This chapter showcases how one manufacturer used real-time data and digital twins to predict bottlenecks, optimize material flow and boost OEE from 50% to 80%. It’s a powerful example of how AI can transform processes, as well as the way teams understand and improve their operations.
Where do you Start Using AI in Manufacturing?
The key to starting with AI in manufacturing is identifying high-impact opportunities that align with your business goals. This chapter walks you through a practical, phased approach – beginning with operational value, time-to-value and scalability across sites. With the right data, tools and guidance, manufacturers can confidently take the first step toward AI adoption and long-term transformation.
Start small: Identify high-impact AI use cases and scale across sites for long-term transformation.
WORK WITH A PARTNER TO GET STARTED
Ready to start with AI in manufacturing? From artificial intelligence manufacturing strategies to predictive maintenance AI, our experts can help you take the next step. Let us know where you would like to improve, and we’ll work with you to identify the right AI solution.
- Production Optimization
- Predictive Maintenance
- Quality Control
- Energy & Material Efficiency
- Workforce Empowerment
