Adoption by Industry
Which industries are moving quickly to capitalize on the IIoT opportunity?
IIoT Use Case Distribution by Role
How is IIoT being applied to produce business results?
Manufacturing Use Case:
Manufacturing Operational Intelligence - 61%
Collect data from multiple, diverse systems and assets to create a dashboard that monitors a manufacturing process and delivers real time insights.
Manufacturing Use Case:
Predictive Maintenance for Manufacturing - 12%
Collect operational asset information (sensor readings, service history, environmental conditions) and use analytical models to predict when an asset will be ready for maintenance vs. a reactive (break fix) maintenance approach.
Manufacturing Use Case:
Asset Health Monitoring - 12%
Monitor and track factory asset health and performance, and deploy machine learning to assess non-standard activity based on known patterns (anomaly detection), so as to deliver insights via unified real-time visibility of KPIs.
Manufacturing Use Case:
Quality Monitoring and Verification - 4%
Monitor product quality in real-time with notifications or alerts for anomalies.
Manufacturing Use Case:
Digital Instructions - 4%
Deliver digital content (i.e., work instruction, manufacturing processes, work instructions, safety procedures) via 3D or augmented reality in order to improve training, quality validation, maintenance execution, and operations monitoring.
Service Use Case:
Remote Condition Monitoring - 39%
Track products remotely by location, performance, utilization, and condition to monitor, troubleshoot, and diagnose issues.
Service Use Case:
Asset Maintenance - 17%
Real-time monitoring of equipment and machinery for onsite preventative maintenance and repair of operational assets.
Service Use Case:
Remote Service - 17%
Expand real-time product and asset monitoring with embedded diagnostics to enable remote access, remote service of assets including bi-directional file transfer or remote software updates.
Service Use Case:
Predictive Maintenance / Service - 14%
Collect service product information (sensor readings, service history, environmental conditions) and use analytical models to predict when a machine will be ready for service vs. a reactive (break fix) service approach.
Operations Use Case:
Asset Monitoring - 47%
Monitor and track health and performance of operational assets (mobile or fixed), and deploy machine learning to assess non-standard activity based on known patters (anomaly detection), so as to deliver insights via unified real-time visibility of KPIs.
Operations Use Case:
Operational Intelligence - 25%
Collect data from multiple, diverse systems and assets to create a dashboard that monitors an operational process and delivers real-time insights.
Operations Use Case:
Predictive Maintenance for Operations - 14%
Collect operational asset information (sensor readings, service history, environmental conditions) and use analytical models to predict when an asset will be ready for maintenance vs. a reactive (break fix) maintenance approach.
Data Sourcing
What data sources are being utilized within IIoT solutions?
