Whether you work in production, automation or IT: anyone connecting factories quickly comes across terms like MQTT, edge computing or Unified Namespace. Our glossary explains the most important terms from A to Z in just a few sentences, and each term links to a detailed article.
Ansible is an open-source tool that automates installations, configurations and updates across many systems. Instead of setting up each server by hand, so-called playbooks describe the desired target state. This keeps even complex system landscapes reproducible and consistent.
The automation pyramid arranges the systems of an industrial production into hierarchical levels, from field devices and controllers through SCADA and MES up to ERP. Traditionally, data only flows from one level to the next. Modern architectures such as the Unified Namespace are increasingly breaking up this rigid hierarchy.
An MQTT broker is the central distributor in an MQTT network. It receives messages from senders (publishers) and forwards them to all receivers (subscribers) that have subscribed to the respective topic. This means machines and applications do not need to know each other directly.
A cyber-physical system (CPS) combines mechanical or electronic components with software and network communication. Sensors capture data from the real world, software evaluates it and feeds control signals back via actuators. CPS are considered the technical foundation of Industry 4.0.
Clustering combines several computers or servers into a group that appears to the outside world as a single system. Workloads can be distributed across the group, and if one node fails, the others take over. This increases both performance and reliability.
A data architecture defines which data exists in an organization, where it is stored and how it flows between systems. It covers both logical models and their physical implementation. A well-designed data architecture is a prerequisite for using data in a scalable and secure way.
A data hub is a central software platform that collects data from different sources, harmonizes it and distributes it to any target system. Instead of many point-to-point connections, there is one central hub. This reduces integration effort and creates a shared data foundation.
Data infrastructure covers all technologies, processes and actors involved in capturing, storing, processing and providing data. This includes networks, databases, integration platforms and governance rules. It forms the foundation of every data-driven application.
A data layer is a dedicated layer between manufacturing assets and IT systems. It establishes the data connections, normalizes the data and makes it available to applications such as MES, analytics or cloud services. This decouples machines and software from each other.
DataOps (data operations) describes methods and tools for managing data flows between processes, technologies and teams reliably and automatically. The approach applies DevOps principles to the world of data. The goal is for the right data to arrive quickly and in high quality wherever it is needed.
A digital twin is a virtual representation of a real object, system or process that is continuously fed with current data. It can be used to monitor states, simulate scenarios and test optimizations before they are implemented in the real plant.
The edge is the outer boundary of a network where IT meets the real world, right next to machines, sensors and controllers. This is where data is created and enters the IIoT network. In manufacturing, the edge is usually the plant or the production line itself.
With edge computing, data is processed directly at the source instead of first being sent to a central data center or the cloud. This shortens response times, saves bandwidth and keeps sensitive data on site. This is crucial for time-critical production processes in particular.
An EnPI (Energy Performance Indicator) is a metric that measures the energy efficiency of a machine, a process or an entire factory. EnPIs are a core element of energy management systems according to ISO 50001. They make savings potential visible and progress measurable.
An ERP system (Enterprise Resource Planning) maps a company’s core business processes, such as finance, procurement, supply chain, production planning and service. It sits at the top of the automation pyramid. Consistent planning requires up-to-date data from production.
In an event-driven architecture, every relevant event, such as a machine stop or a finished part, triggers a message. A central system distributes this message to all interested applications, which can then react immediately. This makes systems more flexible and responsive than cyclic polling.
A factory data hub is a data hub tailored specifically to the requirements of production environments. It connects heterogeneous machines and protocols with IT systems, provides data in a uniform way and manages access and security centrally. This turns the factory into a scalable data source for all applications.
The Industrial IoT (Industrial Internet of Things) describes the networking of machines, sensors and production equipment with IT systems. The devices capture and share data that is used for monitoring, analysis and optimization. It is a core technology of Industry 4.0.
An Industrial IoT platform is software that centrally manages and connects physical and virtual elements in manufacturing and IT. It handles data acquisition, integration, management and security. Companies use it to lay the foundation for rolling out IIoT applications quickly and in a standardized way.
Infrastructure as Code (IaC) means provisioning IT infrastructure through machine-readable configuration files instead of manual setup. The configurations are version-controlled in a central repository. This allows environments to be built in an automated, repeatable and traceable way.
Kubernetes is an open-source platform for the automated deployment, scaling and management of containerized applications. It distributes containers across available servers and restarts them automatically in case of failures. Kubernetes has become the standard for running modern, scalable software.
A Manufacturing Execution System (MES) controls and monitors manufacturing at the production level. It tracks orders, performance and quality in real time and acts as the link between machines and ERP. To do its job, the MES needs reliable data straight from the shop floor.
MLOps (Machine Learning Operations) covers the tools and practices for reliably bringing machine learning models into production environments and operating them there. This includes training, versioning, deployment and monitoring of the models. It takes AI projects from prototype to stable continuous operation.
MQTT (Message Queuing Telemetry Transport) is a lightweight messaging protocol for machine-to-machine communication. It follows the publish/subscribe principle via a central broker and copes well with unstable connections. MQTT is considered the standard protocol in the Industrial IoT and for the Unified Namespace.
Near real-time data is available with minimal delay because network latency and processing time are kept to a minimum. Unlike hard real-time, it does not guarantee fixed response times, but it is fast enough for monitoring, dashboards and many control decisions.
On-premises refers to software and infrastructure that is operated locally on a company’s own servers on site instead of in the cloud. The company retains full control over data, security and availability. In industry, this is often a prerequisite for applications close to production.
OPC UA (Open Platform Communications Unified Architecture) is a vendor-independent standard for secure data exchange in industry. It transmits not only values but also their meaning via an information model. OPC UA connects sensors and controllers with higher-level systems all the way to the cloud.
A smart factory is a connected production environment in which machines, systems and people continuously exchange data. Self-organizing systems control and optimize processes largely autonomously. The result is higher quality, flexibility and productivity.
Smart production describes manufacturing systems that can capture and diagnose their current state on their own. Based on this data, they adjust processes, report maintenance needs or prevent scrap. It is a key building block on the way to the smart factory.
A Unified Namespace (UNS) is a central, uniformly structured data layer in which all systems of a production publish and retrieve their current data. Instead of many point-to-point interfaces, there is one shared source for IT and OT. The UNS is usually based on MQTT and often models the company according to ISA-95.
The success stories of our customers show how the strategic decision for a Factory Data Hub brings future-proof scalability.
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