Over the last many decades, manufacturers have continuously focused on reducing the total cost of poor quality (amounting to 20% of sales according to the American Society of Quality) and unplanned downtime costs (amounting to nearly $50 billion annually according to Deloitte). Today, the Industrial Internet of Things (IIOT), with huge new volumes of connected sensor data, provides the potential to unleash powerful new insights to optimize manufacturing performance – if only this data could be harnessed for analytics. Previous solutions have applied only piecemeal, fragmented software and hardware approaches to this problem – until now.
HDP runs on HPE's Elastic Big Data Architecture in the data center and can help capture, store and analyze the continuous shop floor data feeds. PTC's Thingworx IIOT platform can be seamlessly integrated with Spark on HDP, helping Data Scientists leverage Machine and Deep Learning algorithms to train the next generation of predictive and quality models. These models can then be deployed and ran using HDF on the Shop Floor, allowing Real Time, Actionable Decision Making.
This solution helps manufacturers significantly increase product qualify while avoiding costly assembly line machine downtime. With this joint solution, Manufacturers will be able to significantly increase revenue and reduce costs while accelerating product time to market.
Join our theater presentation T7026 – Leveraging big data and advanced analytics to reduce overall TCO for manufacturing shop floors. Discover new capabilities to optimize the entire IIOT analytics lifecycle including data ingestion, enrichment, storage, machine learning and real-time decision-making. In addition, learn how new IIOT analytics applications can be created and deployed easily, on a hardware platform optimized for edge analytics workloads. The result? Next-generation analytical insights, manufacturing performance and competitive advantage.