About this session

How do you make quality a competitive advantage in an era of relentless production demands? As manufacturing leaders look to boost precision and efficiency, machine vision is emerging as a game-changer, not just for inspection but for smarter, more adaptive operations. Yet, building visual intelligence into complex production environments comes with its own challenges: calibration issues, data interpretation hurdles, and scaling across diverse product lines.

This group discussion goes beyond theory. It is a peer-led exploration of what is really working on the factory floor. You will join breakout groups with fellow manufacturing leaders to exchange ideas and debate approaches, diving into how machine vision is being applied across industries, from detecting micro-defects to guiding precision assembly. Whether you are optimizing existing setups or planning new implementations, this is your chance to compare notes and learn from real-world experiences.

We highly encourage you to prepare any questions you may have on this topic beforehand and use this forum as a valuable opportunity to learn how others in similar positions at different companies approach this topic.

Key Discussion Themes:

1. Driving Zero-Defect Manufacturing

• How is machine vision transforming quality control?
• What does it take to shift from reactive inspection to proactive detection?
• What real-world use cases highlight the impact of visual intelligence on manufacturing accuracy?

2. Making Sense of Visual Data

• How can manufacturers turn machine vision insights into actionable, real-time decisions on the shop floor?
• What tools and data interpretation methods are proving most effective?
• How do you train teams to leverage visual data efficiently?

3. Vision Systems That Scale and Adapt

• What are the key considerations when designing machine vision systems that can adapt to changing SKUs, compliance standards, and product complexity?
• How do manufacturers ensure that machine vision remains accurate and reliable as processes evolve?
• What lessons can be learned from scaling visual intelligence across diverse manufacturing environments?