MLC Master Class Series Webinar
Defects and errors are costly to manufacturers in terms of time, materials, and ultimately money. Leaders charged with reducing defects on the factory line must strike a balance between adjusting to market demand, product updates, and new product rollouts while also anticipating and identifying potential sources of defects. Many are turning to different technologies to address those needs.
One such solution is computer vision technology. While vision systems are not new, their capabilities are now significantly boosted with the addition of AI that can accurately identify issues and take action. By adding intelligent “eyes” to their operations, the quality teams can quickly identify defects in production outputs as well as remotely monitor assets for potential disruptions.
View the MLC and IBM for this case study session to discover how to use self-learning visual inspection solutions that can provide manufacturers the ability to:
- Quickly respond to manufacturing issues and reduce rework, warranty claims, improve overall product quality and most importantly pursue a zero defects goal.
- Detect a defect at the point of origin and correct it plus provide immediate feedback about the defect to shop floor associates.
- Deploy built-in machine learning algorithms at the edge, data center, and anywhere in between.
- Penelope Brown, Content Director, Manufacturing Leadership Council
- Susan Zichitella, Worldwide Leader Industry 4.0, 5G and Supply Chain Engineering Services, IBM