这对生产管理意味着什么？例如，在数据驱动的工厂中，生产订单不是简单地投入生产，而是与装配现场材料的实际可用性自动核对。这消除了搜索和等待时间，而可以有效地利用这些时间。通过集成预测性维护，可以提前将计划外维护工作与生产计划同步。终，IIoT 架构为新工厂布局提供了基础，在这种布局中，各个机器园区之间只存在松散的联系，而不是固定的生产链。机器使用、移动运输车辆和机器人、物流和员工的控制和协调在这里至关重要——只能基于“现实世界信息”进行监管。
为此需要哪些技术和概念？几个例子：

移动机器和机器人

工业无线局域网和工业 5G 用于移动机器和机器人之间的通信。在这里，特别是 5G 将提供一个基础设施，该基础设施也满足实时要求/为实施甚至复杂的应用程序（例如大规模使用自动运输车辆）提供显着更大的带宽。

集成无通信能力的资产——物件成为智能对象：射频识别 (RFID) 和实时定位系统 (RTLS) 支持基于数据集成本身不具备通信能力的可移动资产，例如材料箱、中间产品和工具。RFID 可以在机器或转运点进行直接识别，并且 - 当使用智能标签时 - 也可以用作识别。RTLS 提供实时识别和定位，并且当使用显示应答器时，还可以启用新的人机通信方式。



 

预测性维护

传感器和现场设备提供现场机械和设备的数据，这些数据不是自动化直接需要的。智能设备（例如具有通信功能的 Sitop 电源）可以将数据直接输入工厂管理，例如收集功耗曲线。由于许多传感器已经连接到可编程逻辑控制器 (PLC)，因此 PLC 也可以通过合适的模块用作“数据收集器”。

该架构的核心是一个高性能和灵活的网络基础设施，满足 OT 的特殊要求（可用性为重中之重，具有分层的服务质量级别），并辅以用于操作、诊断和优化的管理平台。

以这种方式捕获的数据可用于不同的架构和应用程序。边缘设备在靠近流程的地方处理这些数据。具有数据湖的基于云的解决方案可实现全面评估，并作为工厂管理的基础。此外，数据可以分布在多个站点甚至公司边界之外。因此，供应商和客户还可以将交付或需求信息实时输入数据驱动工厂的系统中。



 

Industrial Wireless LAN and Industrial 5G are used for the communication between mobile machines and robots. Here, 5G in particular will offer an infrastructure that also meets real-time requirements/offers significantly greater bandwidth for the implementation of even complex applications (e.g. use of autonomous transport vehicles on a large scale).

Integration of assets without communication capability – things become smart objects: Radio frequency identification (RFID) and real-time locating systems (RTLS) enable data-based integration of movable assets that possess no communication capability themselves, e.g. material boxes, intermediate products, and tools. RFID enables the direct identification at machines or transfer points and – when smart labels are used – can also serve as permanent identification. RTLS offers identification and localization in real time and – when display transponders are used – can also enable new ways of human-machine communication.

Predictive maintenance

Sensors and field devices supply data from machinery and equipment on site that is not directly needed for automation. Intelligent devices – such as Sitop power supplies with communication capability – can feed the data directly into the factory management, e.g. to collect power consumption profiles. Since many sensors are already connected to a programmable logic controller (PLC), the PLC can also be used as a “data collector” via suitable modules.

At the core of this architecture is a high-performance and flexible network infrastructure that meets the special requirements of OT (availability as top priority with tiered quality-of-service levels), supplemented by a management platform for operation, diagnostics, and optimization.

Data captured in this way can be used in different architectures and applications. Edge devices handle this data close to the process. A cloud-based solution with Data Lake enables comprehensive evaluation and serves as a basis for factory management. Moreover, the data can be distributed across multiple sites and even beyond company boundaries. As a result, suppliers and customers can also feed delivery or demand information in real time into the system of the data-driven factory.