Resilient Supply Chain
For a 360° view of factory operations, connect and integrate data from machines, systems, process historians, and operational data stores. With hundreds of protocols, connecting and unifying data across these "things" can be daunting. But with cloud, integration, data, and analytics, you can easily connect, integrate, and unify your data to gain a bird's eye view across global operations.
For global value chains, QMS and SPC are not enough. Combine historical and real-time data from systems and suppliers, then create AI models to detect and prevent quality issues before they occur. With IoT, integration, data unification, and ML, automate root-cause analysis, detect & classify defects, react in real time to proactive alerts, and dynamically learn to improve quality and reliability.
Reducing process variability has always been critical for manufacturing; but, doing this in real time is challenging. Reduce variability of your most complex processes with anomaly detection, univariate and multivariate Statistical Process Control (SPC) and maximize the value of streaming data with real-time with AI-infused process control methodologies
Eliminate Unplanned Downtime
Scheduled maintenance for instrumented assets, digital twins, and the IIoT can be costly. By continuously analyzing equipment and IoT sensor data, you can gain real-time awareness. Streaming and edge analytics, dynamic learning, and ML algorithms can ferret out key relationships and anomalies and predict future states before problems occur. Use predictive maintenance to maximize productivity.
With recent supply chain disruptions, building resiliency tops many agendas. Real-time intelligence allows organizations to proactively respond to customer & supplier changes. By unifying data across the value chain and eliminating data silos, you can create a smart inventory, sense & respond to demand in real time, monitor supplier performance, and optimize transport and logistics.