2018년도 IIoT 현황

Collect data from multiple, diverse systems and assets to create a dashboard that monitors a manufacturing process and delivers real time insights.

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.

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.

Monitor product quality in real-time with notifications or alerts for anomalies.

Monitor inventory so as to optimize logistics, maintain inventory levels, prevent quality issues, detect theft, etc.

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.

Monitor and track the operating conditions and environment on the factory floor, so as to identify human and asset safety concerns/hazards. Deliver real-time insights, warnings, and remedial instructions, potentially via AR experiences.

Integrate product usage and performance data to enable usage, performance, or outcome based pricing and subscription models that create disruptive business models, and increase value captured and market penetration opportunities.

Analyze usage and condition data across products and customers to trigger automated cross-sell and up-sell alerts and identify opportunities for new market segments, products, or services which align to customer needs.

Connect and analyze product usage and consumable data to create inventory-based consumable resupply models which enhance the customer's experience and create new revenue streams.

Track products remotely by location, performance, utilization, and condition to monitor, troubleshoot, and diagnose issues.

Real-time monitoring of equipment and machinery for onsite preventative maintenance and repair of operational assets.

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.

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.

Create a service dashboard to deliver real time service insights by collecting data from multiple, diverse systems.

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.

Collect data from multiple, diverse systems and assets to create a dashboard that monitors an operational process and delivers real-time insights.

Create a dashboard to collect data from multiple, diverse systems and deliver real time operational insights.

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.

Monitor inventory so as to optimize logistics, maintain inventory levels, prevent quality issues, detect theft, etc.

Monitor and track the operating conditions and environment in/around an operations process, so as to identify human and asset safety concerns/hazards. Deliver real-time insights, warnings and remedial instructions, potentially via AR experiences.

Enable customers to remotely control and optimize their products and assets to reduce operational costs, mitigate safety risks, improve business processes, and increase employee and customer satisfaction.

Customers remotely add or remove features, integrate with other applications, change operating parameters to enhance their experience or product performance.

Customers monitor and analyze the usage and condition of products or benchmark with anonymized peers to uncover opportunities for improvement.

Customers diagnose and resolve issues themselves via AR experiences or connected applications to maximize product availability and uptime and improve customer satisfaction.