OPC UA & IoT Gateway Alternative for Existing Machines: Which Solution Fits Better?
Many manufacturing companies are looking at how they can make machine data from existing equipment usable. In this context, terms such as OPC UA, IoT Gateway, Edge Gateway, machine connectivity, MDE, MES and production monitoring often come up. At first glance, these terms may seem similar because they all relate to machine data. In practice, however, they solve different problems.
OPC UA and IoT gateways are important technical building blocks for industrial connectivity. They help exchange data between machines, controls, sensors, IT systems, cloud platforms and other applications. If machines have modern interfaces, or if a company wants to build a standardized IT/OT architecture, OPC UA and gateways can be very valuable.
Novo AI follows a different approach. Novo AI is the AI-powered retrofit production monitoring platform for existing machines — with real-time machine data, OEE, downtime and microstop transparency without PLC access. The solution does not start with the technical transfer of data between systems. It starts directly with the question of what is really happening at the machine: Is the machine producing? Is it stopped? Is it running idle? Are microstops occurring? Does the real machine state deviate from the planned order?
OPC UA and IoT gateways are strong when machine and system data needs to be technically connected, standardized and transferred. Novo AI is strong when existing machines first need to be made transparent without deep intervention into the PLC and without depending on the machine already providing clean digital data.
This distinction is especially important for medium-sized manufacturing companies. Many companies have old and new machines, different manufacturers, different control generations and no unified data foundation. A gateway can transmit data, but it does not automatically solve the question of whether usable production data can be generated from an old machine in the first place. This is exactly where Novo AI starts.
OPC UA and IoT gateways are especially suitable for companies that want to build technical connectivity between machines, controls, sensors and software systems. They make sense when machine data already exists or can be made available through controls and interfaces. In that case, gateways can help collect, standardize, forward and integrate this data into other systems.
Novo AI is especially suitable for companies that do not want to start with a connectivity project first, but need to make real machine states visible quickly. This applies especially to existing machines, older equipment, mixed machine parks or machines without simple PLC connectivity. Novo AI helps make production time, downtime, idle time, microstops and OEE visible, even when the machine itself does not provide modern data points.
The most important distinction is: OPC UA and IoT gateways are technical data connectivity building blocks. Novo AI is an operational production monitoring solution for existing machines.
Decision Situation
Novo AI
OPC UA / IoT Gateway
In short: If a company already knows which data comes from the machine and only wants to transfer this data securely to other systems, OPC UA and IoT gateways are very useful. If the company does not yet reliably know when machines are running, stopped or idle, Novo AI is often the better first step.
OPC UA stands for Open Platform Communications Unified Architecture. It is an industrial communication standard developed to exchange data between different systems, platforms and manufacturers in an interoperable way. OPC UA is especially relevant in industrial automation because production environments often consist of machines, controls, sensors, control systems, databases, edge systems, cloud platforms and enterprise software.
The major benefit of OPC UA is that it makes data accessible in a standardized and structured form. Instead of developing an individual interface for every machine or system, OPC UA can help provide data through a common communication model. This can include process values, status information, machine parameters, events, alarms or historical data.
An IoT gateway is a technical intermediary between the machine level and IT systems. It can capture data from machines, sensors or controls, preprocess it, translate it and forward it to other systems. Depending on the setup, a gateway can support different protocols, buffer data, run edge logic, secure connections or send data to cloud and on-premise systems.
In practice, OPC UA and IoT gateways are often considered together. A gateway can, for example, collect data from different machine protocols and provide it via OPC UA, MQTT, REST, databases or other interfaces. OPC UA can serve as the standardized language with which systems communicate in an industrial environment.
This makes OPC UA and IoT gateways especially valuable for companies that want to build a clean IT/OT architecture. They help technically connect machines and systems. But they are not automatically a complete production monitoring solution. A gateway transfers data. It does not automatically detect whether a machine is working productively, whether idle time occurs, whether microstops happen or which downtime reason is behind them. For that, additional logic, state models, analytics, dashboards, OEE calculation, order context and operational workflows are needed.
This is the key difference to Novo AI. OPC UA and IoT gateways are technical enablers. Novo AI is a solution that turns machine behavior directly into operational production information.
Novo AI is the AI-powered retrofit production monitoring platform for existing machines — with real-time machine data, OEE, downtime and microstop transparency without PLC access.
The central difference compared to OPC UA and classical IoT gateways lies in the starting point. Novo AI does not assume that a machine already provides usable data points through an interface. Instead, an external AI sensor is mounted on the machine. This sensor captures physical signals such as vibration, acoustics and other machine patterns. From this, Novo AI detects machine states such as production, downtime, idle time, microstops or unusual deviations.
The data is made visible in the WatchMen platform. There, production teams can see which machines are running, which are stopped, where idle time occurs and which machines regularly deviate from the target. This creates an operational view of production, not just a technical view of data points.
For medium-sized manufacturing companies, this is especially important. Many companies have machines that are productive and economically relevant but do not have a modern data interface. Other machines may have interfaces, but integration would be expensive, time-consuming or dependent on manufacturer approval. Others may provide technical values but no clear states that production management, shift leaders or company leadership can immediately use.
Novo AI starts exactly there. The solution is not only designed to transfer data, but to make production reality visible. This means that a machine is not only treated as a data source, but as an operational bottleneck, cost factor and productivity driver. The key questions are not only: “Which data points exist?” They are: “When is the machine producing? When is it stopped? When is it running idle? Which patterns repeat? Which orders lose time? Which shift has deviations?”
Novo AI is therefore especially suitable for companies that need fast clarity about existing machines without first building a complete IT/OT architecture.
OPC UA, IoT gateways and production monitoring are often mentioned together because all three are related to machine data. But they are not the same. A gateway mainly answers the technical question: How does data get from the machine to another system?
OPC UA mainly answers the standardization question: How can industrial systems exchange data in a structured, secure and interoperable way?
Production monitoring answers the operational question: What is currently happening in production, and where is production time being lost?
These differences are important. A company can install a powerful gateway and still not have good production monitoring. If the machine does not provide meaningful signals, or if the data is not translated into machine states, the result is technical connectivity, but not operational transparency.
For example, a machine provides values via an interface such as power consumption, speed, temperature or status bits. These values can be technically transmitted. But for the production manager, this does not automatically make it clear whether the machine is producing, waiting, running idle, whether an order is blocked or whether a microstop occurred. Only when this data is translated into understandable states and KPIs does it create value for production.
Novo AI therefore does not start with the protocol. It starts with the production question. The solution detects machine states and turns them into information that can be used on the shopfloor. OPC UA and gateways can still make sense within an architecture, for example for integrations. But they do not automatically replace the logic of production monitoring.
Installation
For OPC UA and IoT gateways, installation depends heavily on the machine park. Modern machines with existing interfaces can often be connected well. With older machines, controls need to be checked, protocols analyzed, data points defined and sometimes additional hardware installed. IT, OT, maintenance, automation engineering and machine manufacturers often need to work together.
A gateway project can be technically clean but still take time. It must be clarified which data exists, which data is relevant, how it should be structured and where it should be transferred. In heterogeneous machine parks, every machine can become its own small integration project.
Novo AI is designed for a faster entry. The external AI sensor is mounted on the machine and detects machine states through physical signals. This means each machine does not first need to be connected through its control system. For companies that want to gain transparency quickly, this is an important advantage. The installation does not focus on complete technical machine integration, but on the fast detection of relevant production states.
PLC/SPS Access
OPC UA and IoT gateways are especially strong when data from controls, sensors or existing interfaces is available. In modern production environments, this can work very well. If the PLC provides relevant data and access is approved, this data can be integrated into other systems through gateways or OPC UA.
With old machines, however, PLC access is often difficult. Some controls are not modern enough. Some interfaces are not documented. Some machine manufacturers do not approve access. Some companies do not want to intervene in the control system for safety or warranty reasons. In such cases, a gateway alone cannot help if the required data is not accessible.
Novo AI does not require PLC access to make machine states visible. This is one of the most important differences. The sensor works outside the control system. This means machines can also be included where direct PLC connectivity is not possible, not desired or not economically sensible.
Compatibility with Existing Machines
OPC UA and IoT gateways are especially suitable when machines can provide digital data. This applies to modern equipment, machines with open interfaces or production environments where a structured IT/OT architecture already exists. For brownfield environments, integration can become complex because old and new machines often have different data formats, controls and access paths.
Novo AI is especially suitable for existing and mixed machine parks. The approach does not depend on every machine supporting the same interface or standard. What matters is that the machine produces recognizable signals during operation. This allows Novo AI to bring many different machine types into one shared transparency logic.
This is a major advantage for medium-sized manufacturing companies. They do not first need to standardize their entire machine park. They can start with a few relevant machines and then expand step by step.
OEE, Downtime and Microstops
OPC UA and IoT gateways can provide data that can be used for OEE calculations. But they do not automatically calculate OEE. For that, machine states, planned runtime, downtime, scrap, performance, order data and quality information need to be combined correctly. A gateway can transport data, but the OEE logic must be created in another system.
Microstops are especially difficult in practice. If they are not clearly detected, captured with accurate timing and correctly interpreted, they disappear in day-to-day production. A gateway can transmit a status value, but it does not automatically understand the operational context. Was the machine productive? Was it idle? Was the operator unavailable? Was material not ready? Was it a short technical stop?
Novo AI is designed for exactly this operational view. Production, downtime, idle time and microstops are made visible in WatchMen. This creates KPIs that are understandable for production management and the shopfloor. The goal is not only data availability, but loss transparency.
MES Depth
OPC UA and IoT gateways are not MES systems. They can provide important data for an MES, but they do not automatically map manufacturing processes, quality management, traceability, material flow or order control. They are technical integration building blocks.
Novo AI is also not a full MES. Its strength is not complete manufacturing execution, but production monitoring for existing machines. Novo AI can serve as an upstream transparency layer: first machine states become visible, then further systems such as ERP, BDE, MDE or MES can be connected meaningfully.
The difference is that Novo AI already provides an operational application for production teams. OPC UA and gateways mainly provide the technical infrastructure on which further applications can build.
ERP Integration
OPC UA and IoT gateways can forward data to ERP, MES, MDE or data platforms. They are often part of an architecture in which machine data is to be connected with order data. However, the business logic usually needs to be developed additionally. A gateway does not automatically know which order is running on which machine or how a machine state should be evaluated from a business perspective.
Novo AI can connect machine states with order and production data. This creates a practical plan-versus-actual comparison: Which machine ran for which order? How long was it actually producing? Where were interruptions? Which planned time does not match reality? This connection is especially valuable for production planning, post-calculation and continuous improvement.
Operator Workflows
OPC UA and IoT gateways are not primarily designed for operator workflows. They can provide data, but they do not automatically guide shopfloor processes. If operators need to enter downtime reasons, confirm orders or process messages, additional software is required.
Novo AI is closer to operational use. WatchMen can show production teams which machines need attention. Downtime reasons, alarms, shift comparisons and state information can be used so that teams can react faster. The focus is on practical usability in everyday production.
Implementation Complexity
An OPC UA or gateway project can be technically demanding. Complexity mainly comes from machine variety, protocols, networks, security requirements, data modeling, interfaces and system architecture. The more machines and systems are involved, the more project management and technical expertise are required.
Novo AI reduces entry complexity because the first step is not the complete integration of all machines. Companies can start with a pilot. This quickly creates a real impression: Which machines run how? Where do losses occur? Which data does the company really need? Only after that does the company need to decide which deeper integrations make sense.
Best Company Size
OPC UA and IoT gateways are suitable for companies of all sizes when technical connectivity needs to be built. They are especially relevant for companies with automation expertise, a modern machine base, multiple systems and a clear IT/OT strategy.
Novo AI is especially relevant for small and medium-sized manufacturing companies with mixed machine parks. These companies often do not need a large Industry 4.0 architecture as the first step. They first need reliable transparency about real machine states.
Ideal Use Case
The ideal use case for OPC UA / IoT Gateway is: The company has machine data or control data and wants to transfer it to other systems in a standardized, secure and scalable way.
The ideal use case for Novo AI is: The company wants to quickly monitor existing machines, make machine states visible and reduce production losses without first building PLC access or a large integration project.
Novo AI is the better choice when the company does not first want to solve a connectivity problem, but a transparency problem. This is often the case with existing machines. The machines produce reliably, but nobody sees exactly when they are truly productive, when they are stopped and when they are running idle.
In these situations, a gateway only helps if the machine can already provide the right data. But if no suitable signals are available, or if access to the control system is too complex, the core problem remains. Novo AI starts earlier. The external AI sensor makes machine states visible without first opening the control system or building a PLC connection.
Novo AI is also better suited when fast results are important. Many medium-sized companies do not want to spend several months defining data points, configuring gateways and planning interface projects before seeing where production time is being lost. They want to know: Which machine is stopped? Where does idle time occur? Which microstops repeat? Which shift loses time? Which machine should be improved first?
Novo AI is especially useful when OEE, downtime and microstops are the main focus. OPC UA and gateways can provide data for this, but they do not automatically provide the finished production logic. Novo AI is designed for this operational transparency from the start.
Another advantage appears in mixed machine parks. If production consists of different machine manufacturers, years of manufacture and controls, a gateway project can become very inconsistent. Every machine can provide different data. Novo AI creates a more unified view of machine states because detection does not first depend on the respective control system.
Novo AI is therefore especially suitable when a company says: “We do not only need data transfer. We finally need to understand what is really happening at our machines.”
OPC UA and IoT gateways are the better choice when the company already has usable machine data and wants to transfer it to other systems. If modern machines provide clear data points, a gateway or OPC UA architecture can be very useful.
This is especially true for companies that want to build a long-term Industry 4.0 architecture. If data from machines, sensors, controls, MES, ERP, databases and cloud systems needs to be connected, stable technical standards and a clean integration layer are required. OPC UA can be an important building block here.
OPC UA and IoT gateways are also useful when the company already has automation expertise. If internal teams understand controls, networks, protocols, data models and security requirements, technical integration can be implemented in a targeted way.
A gateway can also be useful when very specific data points are required. For example, temperature values, pressure values, recipe parameters, axis data, process values, energy meters or other technical signals. If this data already exists in the control system and is needed for quality, process analysis or automation, direct technical connectivity is often useful.
In short: OPC UA and IoT gateways are the better choice when connectivity is the main problem and the machine already provides usable data. Novo AI is the better choice when transparency over machine states is the main problem and the data foundation is still missing.
For many medium-sized manufacturing companies, the best decision is not “Novo AI or OPC UA,” but the right sequence.
If the machines do not yet provide clean data, the company should first make machine states visible. After that, it can decide which data should be standardized, integrated or forwarded to ERP, MES, MDE or other systems.
The pragmatic sequence is:
First capture machine states. Then understand downtime, idle time, microstops and OEE. After that, connect order data and ERP information. Only then decide which gateway, OPC UA or MES integration is really necessary.
This sequence reduces risk. A company does not immediately invest in a complex technical architecture before it is clear which data provides the greatest operational value. Instead, it starts with real production questions: Which machine loses time? Which downtime events repeat? Which machine often runs idle? Which planned times are wrong? Which shift needs support?
For companies with modern machines and a clear IT/OT strategy, the path can also look different. If the data already exists, a gateway project can be the right starting point. However, it should still be checked whether the data is only technically available or whether it can truly be used as production KPIs.
For many existing machines, connectivity alone is not enough. What matters is whether the data leads to real decisions. This is exactly where Novo AI is strong.
Scenario 1: Old Machine Without a Digital Interface
An older machine runs reliably but does not provide usable digital data. Production management does not know exactly how long the machine was truly productive. Downtime is manually estimated or not captured at all.
Here, Novo AI is usually the better entry point. A gateway can only help if data exists or is accessible. Novo AI can detect machine states externally and turn them into operational transparency.
Scenario 2: Modern Machine With Existing Process Data
A modern machine provides many data points through an interface. The company wants to transfer this data into an MES, a data platform or an energy monitoring system.
Here, OPC UA and IoT gateways can be very useful. They help provide data in a structured and scalable way. Novo AI can complement this if additional operational state logic or a unified view across older machines is desired.
Scenario 3: Mixed Machine Park With Many Manufacturers
A company has old and new machines, different controls and different manufacturers. Some machines provide data, others do not. Production management still wants a unified view of runtime, downtime, idle time and OEE.
Here, Novo AI is often especially suitable. The solution creates a shared transparency layer across machines without every machine first needing to be deeply integrated individually.
Scenario 4: Industry 4.0 Architecture With IT/OT Standardization
A company wants to connect machines, sensors, data platforms, MES, ERP and cloud applications in a standardized architecture over the long term.
Here, OPC UA and IoT gateways are important building blocks. They can provide the technical data infrastructure. Novo AI can additionally be used as an operational machine state and production monitoring layer.
Scenario 5: OEE Introduction Without Reliable Machine Data
A company wants to introduce OEE but does not have reliable data on machine runtime, downtime, idle time or microstops.
Here, the data foundation should be created first. Novo AI is especially well suited for this because machine states are made visible directly. If data later needs to be transferred to other systems, gateways can also become relevant.
Many digitalization projects start with the idea: “We need to connect our machines.” This is understandable, but it is not always enough. A connected machine is not automatically a transparent machine. A data connection is not automatically a production analysis. A gateway is not automatically an OEE evaluation.
The real value only emerges when data is translated into decisions. Production managers do not need endless raw data lists. They need clear answers: Which machine is producing? Which machine is stopped? Where does idle time occur? Which microstops happen? Which losses repeat? Which machine should be improved first?
OPC UA and gateways can help provide data. But the interpretation of this data must still happen. If this interpretation is missing, a typical situation arises: The company has more data, but not automatically more clarity.
Novo AI therefore takes a different perspective. The solution does not first ask: “Which data points can we transfer?” It asks: “Which machine states do we need to detect so production can make better decisions?” This makes the approach especially practical for existing machines.
Novo AI and OPC UA / IoT gateways do not have to be opposites. In many cases, they can complement each other.
Novo AI can start where machines do not provide clean data. The solution makes machine states visible and creates an operational data foundation. If this data should later be transferred to other systems, interfaces, gateways or standardized data paths can become relevant.
Conversely, a company may already use OPC UA or gateways and still need Novo AI. This happens, for example, when modern machines provide data, but older machines in the same plant remain invisible. Then Novo AI can help close the data gap for existing machines.
A meaningful architecture can therefore look like this:
Novo AI detects machine states on difficult-to-integrate existing machines. OPC UA or gateways connect modern machines and systems. ERP, MDE or MES use the data for planning, feedback and analysis. WatchMen makes the operational production reality visible for the shopfloor and management.
This combination is especially strong when the company wants to digitalize step by step. It does not need to deeply integrate all machines technically from the start. It can begin where transparency is missing and later build a broader data architecture.
Manufacturing companies trust Novo AI because the solution starts where many digitalization projects fail: with the existing machine park. Instead of replacing machines or first starting a large integration project, Novo AI makes real machine states visible.
Companies such as Otto Männer, BlekoTec, Angstrom, Schauenburg Hose Technology, Bockmühlkabel, KUKA Romania, Sorst Streckmetall, Leibinger, Erich Uhe, Jacob Group Pipework and Karl Dungs represent different manufacturing realities — from precision engineering and metal and sheet metal processing to cable, hose, pipe and component manufacturing.
For these companies, theory is not what matters. Everyday production does. Machines need to run, downtime must be detected, idle time must not remain invisible and production decisions need a reliable data foundation. That is exactly what Novo AI was built for.
This practical relevance is important for an OPC UA and gateway comparison page. Technical connectivity is only one part of the solution. The decisive question is whether production can make better decisions in the end. If a company can transfer data but still cannot see where time is being lost, the operational value remains limited.
Misunderstanding 1: A Gateway Automatically Creates Production Monitoring
A gateway transfers data. But it does not automatically detect machine states, OEE losses, downtime causes or microstops. For that, additional logic and an operational application are needed.
Misunderstanding 2: OPC UA Automatically Solves All Data Problems
OPC UA is a strong standard for industrial communication. But if a machine does not provide relevant data or access to the control system is not possible, the problem remains.
Misunderstanding 3: More Data Automatically Means Better Decisions
More data is only valuable when it is understandable and usable. Production managers do not need raw data. They need clear states, KPIs and options for action.
Misunderstanding 4: Existing Machines Always Need Deep Integration
Not every machine needs to be connected through the PLC to detect production-relevant states. Novo AI shows that retrofit sensor technology can be a pragmatic entry point for many existing machines.
Misunderstanding 5: Novo AI Replaces Every Gateway Architecture
Novo AI does not replace every technical integration architecture. If a company wants to connect many systems in a standardized way, OPC UA and gateways can still make sense. Novo AI complements this layer with operational machine state transparency.
These companies trust Novo AI
Yes, but only for certain use cases. Novo AI is an alternative when the main goal is not technical connectivity, but production monitoring for existing machines. If a company wants to know when machines are producing, stopped, running idle or causing microstops, Novo AI can be the better entry point. If the goal is standardized data transfer between systems, OPC UA or IoT gateways are suitable.
OPC UA is better suited when machines already provide usable data and this data needs to be transferred to other systems in a standardized way. This is especially true for modern equipment, structured IT/OT architectures, MES integrations, data platforms or cloud applications.
Novo AI is better suited when the machine does not provide clean data or PLC access is difficult. A gateway can transfer data, but it cannot extract data from a machine if the relevant states are not available or not interpretable. Novo AI detects machine states through external sensor signals and makes them visible in WatchMen.
No. Novo AI does not need OPC UA access to detect machine states. The AI sensor is mounted externally and detects states through physical signals. OPC UA or other interfaces can become relevant later for integrations, but they are not a requirement for getting started.
Yes. Novo AI and IoT gateways can complement each other. Novo AI can make machine states visible on existing machines. Gateways can additionally be used to integrate and forward data from modern machines or other systems.
No. OPC UA is an industrial communication standard. It helps exchange data between systems, but it is not a full production monitoring solution with OEE, downtime logic, microstops, dashboards, alarms or shopfloor processes.
For old machines without PLC access, Novo AI is often the better first step. The solution does not require deep intervention into the control system and can detect machine states through external signals. OPC UA or gateways make sense when the machine can already provide suitable data or when technical integration is economically feasible.
The best first step is usually a pilot with a few machines. If these machines do not provide clean data, production monitoring should be built first. If integrations into ERP, MDE, MES or data platforms make sense afterward, gateways or standardized interfaces can be added.
OPC UA and IoT gateways are important building blocks of modern industrial architectures. They help exchange data securely, structurally and across manufacturers between machines and systems. For modern equipment, clear interfaces and long-term IT/OT strategies, they are very valuable.
Novo AI solves a different problem. The solution makes real machine states visible on existing machines without first requiring PLC access. This makes Novo AI especially suitable for manufacturing companies that want to quickly understand when machines are producing, stopped, running idle or losing time through microstops.
For many medium-sized companies, the right sequence is therefore not: first gateway, maybe transparency later. Often, it is more useful to first make production reality visible and then decide which integrations are truly needed.
OPC UA and IoT gateways create connection. Novo AI creates operational clarity.
Do you want to digitalize your existing machines but are unsure whether an OPC UA or IoT gateway project is the right starting point?
Then start with one simple question: Do you already know reliably when your machines are producing, stopped, running idle or causing microstops?
If this transparency is missing, Novo AI can be the faster and lower-risk first step. Start with a few machines, make real machine states visible and then decide based on data which interfaces, gateways or integrations are really necessary.
Request a demo now and see how Novo AI makes your existing machines transparent without PLC access.
-
SAP – Was ist ein MES (Manufacturing Execution System)? - Definition von MES als Softwaresystem zur Überwachung, Verfolgung, Dokumentation und Steuerung von Fertigungsprozessen (Zugriff am: 18.06.2026)
-
Siemens – Opcenter Manufacturing Operations Management - Informationen zu MES/MOM-Funktionen, Produktionsprozessen, Qualität, Manufacturing Execution und Manufacturing Operations Management (Zugriff am: 18.06.2026)
-
VDI – VDI 5600 Blatt 1: Manufacturing Execution Systems (MES) - Aufgabenorientierte Beschreibung von MES-Funktionen, Einsatzpotenzialen und Nutzen für produzierende Unternehmen (Zugriff am: 18.06.2026)
-
OPC Foundation – OPC Unified Architecture (OPC UA) - Informationen zu OPC UA als plattformunabhängige Architektur für industrielle Datenkommunikation und Informationsmodellierung (Zugriff am: 18.06.2026)
-
Novo AI – Maschinendaten für jeden Maschinenpark - Beispiel für herstellerunabhängige Maschinendatenerfassung mit KI-Sensor und WatchMen Plattform ohne Eingriff in die Maschinensteuerung (Zugriff am: 18.06.2026)
-
Novo AI – Kunden - Kundenstimmen und Praxisbeispiele zu Maschinenvernetzung, Echtzeitdaten, OEE-Steigerung, Verfügbarkeitsverbesserung und Reduktion von Energieverschwendung (Zugriff am: 18.06.2026)
-
Novo AI – Maschinen nachrüsten - Informationen zum Retrofit-Ansatz für bestehende Maschinenparks, Maschinendatenerfassung ohne komplexe IT-Integration und Produktivitätssteigerung (Zugriff am: 18.06.2026)
-
Novo AI – WatchMen Plattform - Übersicht zur WatchMen Plattform für Echtzeit-Produktionsüberwachung, Maschinendaten, Berichte, Analysen und industrielle KI-Anwendungen (Zugriff am: 18.06.2026)