2018 年工業物聯網 (IIoT) 現況
各種產業都將工業物聯網 (IIoT) 技術視為推動數位轉型的重要核心。PTC 的「產業創新現況」研究系列，詳加探討工業物聯網部署作業，舉凡商業價值、使用案例與部署偏好，皆已包含在內。歡迎探索研究結果，並深入了解物聯網的未來。
各產業的採用情況
哪些產業正在搶搭風潮，將運用工業物聯網 (IIoT) 的機會轉化為商機？
工業物聯網使用案例分佈 (依角色分類)
工業物聯網正透過哪些方式提供實質業務成果？
Design for Connectivity - 1%
Design products, software, systems and systems of systems for connectivity.
Digital Design Review - 1%
Integrate CAD, PLM, product data into AR or VR experiences to enable design reviews with dispersed teams for real-time collaboration.
Digital Twin - 1%
Digitally represent a manufactured product that is connected to the physical counterpart so as to analyze real world usage data and configurations for future sales, recalls, or product update opportunities.
Engineering System Visibility - 1%
Collect and monitor data from multiple, diverse design systems to deliver real time insights.
Manufacturing Use Case:
Manufacturing Operational Intelligence - 28%
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 - 7%
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 - 3%
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 - 1%
Monitor product quality in real-time with notifications or alerts for anomalies.
Manufacturing Use Case:
Digital Instructions - 2%
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.
Manufacturing Use Case:
Manufacturing Operations Safety - 0%
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.
Sales & Marketing Use Case:
Flexible Business Models - 0%
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.
Sales & Marketing Use Case:
Usage-Based Marketing & Upsell - 0%
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.
Sales & Marketing Use Case:
Connected Consumable Resupply - 0%
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.
Service Use Case:
Remote Monitoring - 9%
Track products remotely by location, performance, utilization, and condition to monitor, troubleshoot, and diagnose issues.
Service Use Case:
Asset Maintenance - 4%
Real-time monitoring of equipment and machinery for onsite preventative maintenance and repair of operational assets.
Service Use Case:
Remote Service - 4%
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 - 4%
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.
Service Use Case:
Service Systems Visibility - 1%
Create a service dashboard to deliver real time service insights by collecting data from multiple, diverse systems.
Operations Use Case:
Asset Monitoring - 7%
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 - 3%
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:
Connected Operations Systems Intelligence - 1%
Create a dashboard to collect data from multiple, diverse systems and deliver real time operational insights.
Operations Use Case:
Predictive Maintenance for Operations - 1%
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.
Operations Use Case:
Inventory/Warehouse Mgmt. & Tools Tracking - 1%
Monitor inventory so as to optimize logistics, maintain inventory levels, prevent quality issues, detect theft, etc.
Operations Use Case:
Operations Safety - 1%
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.
Customer Use Case:
Remote Operation - 1%
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.
Customer Use Case:
Product Customization - 0%
Customers remotely add or remove features, integrate with other applications, change operating parameters to enhance their experience or product performance.
Customer Use Case:
Usage and Performance Benchmarking - 0%
Customers monitor and analyze the usage and condition of products or benchmark with anonymized peers to uncover opportunities for improvement.
Customer Use Case:
Customer Self Service - 0%
Customers diagnose and resolve issues themselves via AR experiences or connected applications to maximize product availability and uptime and improve customer satisfaction.
資料來源
工業物聯網解決方案中運用了哪些資料來源？
運用 ThingWorx 工業物聯網 (IIoT) 平台實現業務轉型
想了解工業物聯網 (Industrial IoT) 如何協助貴公司推動數位轉型嗎？歡迎探索 ThingWorx IIoT 平台、閱讀 PTC 客戶案例研究，並深入了解我們的合作夥伴網路。