Continually improving factory operations is critical for manufacturers. Look at the facts: the total cost of poor quality is as much as 20% of sales (American Society of Quality), and unplanned downtime costs factories approximately $50 billion per year (Deloitte).

The most pressing questions are: which process variables influence quality and yield and which process variables predict equipment failure? Finding these answers will give forward-thinking manufacturers a competitive edge.

Speakers will discuss the data management challenges facing today's manufacturers, including proprietary systems and siled data sources, as well as the inability to make sensor-based data actionable.

Integrating business data from ERP, MES, maintenance systems and other sources with real-time operational data from sensors, PLCs, SCADA systems and historians is an important first step. But how do you start? What is the value of a data lake? How is AI/ML applied to enable real-time action?

Join this educational session, which includes a look at a roadmap for an open source industrial IoT data management platform.

Key learning points:
• Understand the key use cases commonly performed by manufacturing companies
• Understand the value of using multivariate manufacturing data sources, as opposed to a single sensor on a device
• Understand the advances in big data management and streaming analytics that are paving the way for next-generation factory performance

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