Find out how leading companies from our network successfully connect their IT and OT systems – from machine control to ERP. We showcase real solutions and practical examples with which companies can break down silos, standardize data flows and automate processes intelligently – securely, interoperably and scalably.
Our platform brings together leading technology partners, solution providers and integrators to help companies achieve successful IT/OT integration. From machine connectivity and middleware solutions to the implementation of an end-to-end data architecture – you can rely on partners whose solutions have already proven themselves in practice.
Since 2017, ayedo has specialized in tailored container solutions and the operation of complex...
b.telligent is a technology-independent consultancy with a focus on optimizing digital and data-driven...
BLUE-ZONE GmbH is a manufacturer of individual software applications for product manufacturers, with...
Confluent is pioneering a fundamentally new category of data infrastructure focused on data in motion....
Founded in 2012, Cumulocity is a global leading industrial IoT platform, offering ready-to-use device...
The software company Cybus specializes in data integration for large scale manufacturing environments....
EMQ is the world's leading software provider of open-source IoT data infrastructure. We are dedicated to...
Endress+Hauser is a global leader in measurement and automation technology for process and laboratory...
ENLYZE Shop Floor BI helps increase productivity in continuous manufacturing and make data-driven...
ICONICS (now MEIDS) is a global automation software provider specializing in real-time data...
ifm electronic gmbh with headquarters in Essen develops, produces and distributes sensors, controls,...
Prosys OPC is a leading provider of OPC UA software solutions, offering innovative products and services...
Networking brownfield – the right way! In many factories, old S5 controllers meet modern machines with OPC UA – and this is exactly where the challenge begins: heterogeneous machine parks, some of which are decades old, need sophisticated connectivity before use cases such as condition monitoring, CO₂ measurement or smart dashboards can be considered.
The key lies in a one-time, clean data integration – and scalable deployment across the entire enterprise. This requires internal standards: from Docker deployments and low-code platforms to defined technology stacks in Angular or Java. Rely on best practices and tried-and-tested solutions that turn your brownfield into a digital ecosystem. Take a look at our community – your challenge may already have been solved there.
End-to-end IT/OT integration is far more than a technical nice-to-have – it is the prerequisite for scalable, digital production. However, in the reality of many plants, a highly heterogeneous machine park meets ambitious digitalization goals: Machines from the 1970s run alongside systems from 2023. Some communicate via OPC UA, others not at all. The result: data silos, media disruptions and sluggish processes.
Many companies in our network have solved this challenge with a standardized connectivity strategy. For example, more than 10,000 machines in 70 plants worldwide have been networked with a standardized messaging infrastructure. IT/OT integration products from our IoT use case partners, which read machine and sensor data via IPC directly from control systems such as Siemens, FANUC, Heidenhain, Allen-Bradley or WAGO, often form the basis of these solutions. The data is then published via a message broker (e.g. NATS or Kafka) and is accessible worldwide – to anyone with authorization.
The advantage: the machines only need to be connected once, the data is uniformly structured and can be used in a variety of ways. This reduces the workload on IT, reduces set-up times and avoids costly multiple connections. New use cases such as condition monitoring, OEE analyses, CO2 calculations or bottleneck analyses can be implemented quickly and efficiently – without additional hardware or duplicate interfaces.
To ensure scalability, IT/operations governance managers in our community define clear standards: For example, Angular and Java for developments, Docker for deployments, low-code platforms for fast implementations. The data should be collected once and then made widely available – locally or in the cloud.
Whether retrofitting, brownfield networking or standardized data provision: the journey does not begin with the big AI use case, but with the clean connection. Schaeffler shows how this basis is created.
Conclusion:
IT/OT integration is not a goal, but an enabler.
Brownfield can be networked – with realistic effort.
Standardized infrastructures create the basis for real scaling.
Data should be collected once and used many times.
Discover our partners’ solutions now or join the community – your challenge may have already been solved!
IT (information technology) includes systems that process information such as recipe data or product specifics and store and provide it – such as ERP (e.g. SAP), MES systems with data such as order and production data (production orders such as ID, start/end time, batches, material requirements or actual quantities / target/actual comparison) or CRM systems (e.g. Salesforce), databases, business intelligence, cloud platforms (e.g. Cumulocity, Microsoft Azure platform or AWS) or data lakes. These systems primarily support business processes such as order processing, accounting, human resources or customer management.
OT (Operational Technology), on the other hand, controls and monitors physical processes in production – such as production systems, machines, sensors or robots. Data such as machine status (running, malfunction, set-up, etc.), causes of failure / downtime reasons (bottleneck analyses) or cycle times, cycle times are recorded here. This is achieved via control systems (e.g. Siemens S7, Allen-Bradley), SCADA systems or edge devices that can record and influence data from the production floor in real time.
Why is the connection crucial?
In industry, IT and OT are increasingly merging to enable data-driven decisions along the entire value chain. Liebherr, for example, connects the MES via an integration platform and thus prevents data from “being lost” there – e.g. for traceability, intralogistics or sustainability issues (CO₂ balance per batch). Schaeffler uses the MES for classic production data, but enriches it with process data (e.g. energy, condition, vibrations) from the OT in order to derive new KPIs. Central use cases can only be realized if data from machines, systems and sensors is transferred to IT in a secure and structured manner – for example:
Predictive maintenance (maintenance before faults occur),
production optimization (e.g. through cycle time or OEE analyses),
Quality management (traceability and process control),
Sustainability (e.g. CO₂ analyses at machine level).
The challenge: IT and OT do not speak the same language – they use different protocols, technologies and security models. Only with well thought-out IT/OT integration can both worlds be meaningfully combined.
“The challenge doesn’t lie in the technology, but in the organization.” – Peter Sorowka, CEO of Cybus, in IoT Use Case Podcast Episode #157
In many industrial companies, IT used to be involved only at the end of procurement processes – now it plays a role from the outset, often with direct involvement in procurement And for good reason: while the technical integration of IT and OT systems is feasible today, the real challenge only begins afterwards.
Production systems such as machine control systems (OT) are technically connected to IT systems such as ERP, MES or cloud platforms in order to realize business IoT use cases such as OEE, CO2 footprint or peak shaving.
In practice, this is done by IoT gateways or edge computers that read data from Siemens S7, FANUC or Allen-Bradley controllers, for example, and pass it on via protocols such as OPC UA or MQTT.
➡️ Integration is a technical process that enables pure data flow. However: technology alone does not solve organizational hurdles.
Lukas Scholze from Liebherr gets to the heart of the matter in the same podcast episode:
“We realized that we couldn’t implement every use case individually. Instead, we have developed a platform strategy that enables us to implement use cases quickly and efficiently.”
Successful integration alone is not enough. Without organizational alignment, the following issues still remain:
data silos
friction losses
redudant efforts
lack of scalability
This is where IT/OT convergence comes in: it describes the strategic and organizational merging of both worlds. The aim is to not only technically connect IT and OT, but also to coordinate them organizationally – with:
joint governance
coordinated security concepts
clear responsibilities
uniform technology stacks
coordinated purchasing and development processes
➡️ Convergence is an organizational and cultural shift – away from silos toward shared goals and processes.
Many companies achieve integration – but only through convergence can digitalization become truly scalable, secure, and efficient.
Both are essential for successful Industry 4.0 initiatives:
| Term | Meaning | Focus |
|---|---|---|
| IT/OT Integration | Technical connection between systems | “How do data get from the machine to IT?“ |
| IT/OT Convergence | Shared processes, standards, and responsibility | “How do IT and OT work together to scale digitalization?” |
The prerequisites for successful IT/OT convergence are:
Standardized interfaces (e.g. OPC UA, MQTT),
Secure network architectures for production environments,
Shared data models and semantics (e.g., AAS, ISA-95),
Cultural understanding and interdisciplinary teams that bring together IT and OT expertise.
Challenges include:
Technical complexity when connecting legacy machines (brownfield environments)
Building trust between IT and OT departments that have traditionally operated separately
Security issues when opening up previously isolated production networks
Lack of standards in some industries or legacy systems
A successful IT/OT convergence therefore requires not only technology, but also change management and strategic architectural work.
IT/OT integration solutions connect your shopfloor systems with your IT systems – such as your MES or ERP. These connections can be seamlessly embedded into existing processes. Proven, real-world approaches enable bidirectional communication between OT and IT without manual steps – unlocking numerous advantages:
Consistent, standardized data flows (e.g., via OPC UA and MQTT) provide full visibility into machine and operational data – in real time. Production managers can detect faults early, control processes more flexibly, and sustainably improve equipment efficiency.
Machine and equipment data are automatically fed into MES, ERP, or cloud systems. This eliminates manual steps in quality assurance, maintenance, and logistics. Workflows become leaner, error rates decrease, and response times are shortened.
Open standards and modular architectures (e.g., container technologies like Docker, standardized APIs) significantly reduce integration costs. New technologies – such as edge analytics or AI models – can be flexibly added without putting existing systems at risk.
Data is validated, standardized, and pre-contextualized right at the point of capture (edge). This significantly increases data quality – a key foundation for accurate analysis, predictive maintenance, and data-driven optimization of your production processes.
Integration creates a shared data foundation and mutual process understanding between IT and OT. Silos are broken down – interdisciplinary teams develop solutions faster, more practically, and more sustainably. Innovation becomes not just possible, but part of your company culture.
By avoiding proprietary technologies, you remain flexible: new machines, sensors, or platforms can be integrated easily. This protects your investments – and ensures your competitiveness in a rapidly evolving technological landscape.
Gain valuable insights into real-world IIoT implementations, learn from the best practices of leading companies, and connect with the right contacts in the community – for well-informed decisions and future-proof strategies.
Use our platform to discover hands-on best practices and industrial use cases. See how other companies are successfully implementing concrete IIoT projects.
Talk to us – we listen, understand your challenges, and connect you with the right experts and contacts from our community.
Find out how leading companies are using modern data transmission technologies to drive their digital transformation. Each of these examples shows how the right transmission technology as an integral part of a holistic IIoT concept contributes to success.
Find out how Cedalo and Portainer standardize complex machine connectivity using container-based architectures and MQTT protocols. The solution enables seamless real-time data transmission from machines to the cloud – scalable, secure, and independent of system boundaries. This creates future-ready IT/OT infrastructures for industrial applications.
Find out how soffico and secunet jointly deliver a flexible, secure, and scalable solution for the pharmaceutical industry. The combination of edge computing and low-code orchestration ensures regulatory compliance while boosting efficiency – from secure data acquisition to auditable GMP documentation.
Find out how BestSecret leverages Confluent Cloud to scale its event-driven architecture, provide operational data via Kafka topics, and rapidly launch new business initiatives – from real-time campaigns to a curated platform. Result: A stable, scalable system that unites innovation and customer experience.
Find out how Uhlmann and soffico implement a seamless integration architecture using Orchestra to ensure reliable traceability across the pharmaceutical shopfloor. The solution is modular, validatable, and fully GMP-compliant. A low-code approach with centralized data management and built-in audit trail functionality forms the foundation.
Many IIoT projects fail not because of the idea, but because of the implementation: a lack of scalability, high operating costs and unclear requirements lead to expensive rework and a failed business case.
On our platform, you will find tried-and-tested technologies, best practices from real industry projects and the collective knowledge of our community. We show you how to avoid typical mistakes with the right technology stack – from data acquisition to AI evaluation – and how to set up your IIoT project economically and future-proof.
Discover how leading companies from our network successfully structure their projects – modular, interoperable and data-secure.
Data acquisition forms the solid foundation of your IoT application. Whether machine, operating or sensor data - accurate and reliable data acquisition enables precise analyses and data-based decisions. Modern solutions capture data directly at the machine, standardized and in real time.
Reliable data transmission is essential for every IoT process. Choose between wired (e.g. Ethernet) and wireless technologies (e.g. 5G, LoRaWAN) based on your requirements in order to optimally combine stability and flexibility.
The efficient preparation and pre-processing of your raw data ensures that it can be used immediately. Whether edge computing or local pre-processing - reduce the amount of data and significantly improve the performance of your IoT systems.
Data standardization creates the basis for efficient, cross-manufacturer communication and consistent use of data throughout the entire life cycle. Whether through protocols such as OPC UA over MQTT for secure transmission or standardized product data and digital twins - your IIoT projects remain flexible, scalable and economical.
The convergence of production technology (OT) and information technology (IT) enables you to achieve a transparent data flow without media disruptions. This allows you to eliminate data silos, speed up decision-making and optimize your operational processes in the long term.
IoT platforms form the central nervous system of your digital infrastructure. As PaaS or SaaS solutions - for example in the form of customer portals for manufacturers - they store, visualize and manage IoT data. As a result, you always have a comprehensive overview of your processes and can make well-founded, data-based decisions.
Protecting sensitive industrial and process data is a top priority. Modern security concepts ensure that your data is transmitted and stored in encrypted form and that your systems always comply with current regulatory requirements.
Efficient management of networked IoT devices is a key component of successful digitalization strategies. From commissioning and updates to decommissioning - structured device management reduces operating costs and significantly increases the security of your IoT infrastructure.
Visualized data enables faster and more precise decisions in your company. Modern dashboards and graphical presentations transform complex data streams into clear, real-time displays and create transparency at all levels of the company.
The systematic analysis of your IoT data uncovers hidden correlations and identifies optimization potential in your processes. From descriptive statistics to complex analysis procedures - gain valuable insights from your operational data for well-founded business decisions.
Data analysis is the basis for data-driven IIoT applications - from process optimization to AI-supported predictions. While traditional evaluations work with fixed rules, AI algorithms independently recognize patterns and anomalies - for predictive maintenance or quality forecasts, for example. Both approaches complement each other and optimize the potential of your IoT data.
Industry-specific IoT applications address concrete challenges with preconfigured functionalities. From production optimization to asset tracking — these specialized solutions offer rapid time-to-value and can be flexibly adapted to individual requirements.
Modern IT/OT architectures are built on proven protocols, platforms, and standards. They enable secure, scalable, and vendor-independent data flows – from the machine to the cloud. These are the key technologies that leading industrial companies rely on today:
Our specialists analyze your requirements and identify the perfect transmission solution for your individual challenges — fast, precise, and independent of any manufacturer.
Our community brings together industry experts who have already implemented successful IIoT projects – openly, practically and on an equal footing. Gain insights into how other companies have solved challenges, share your use cases and discover new ideas and concrete solutions for your business.
Every innovation starts with an idea. Discover proven use cases that support your digital transformation — from predictive maintenance to worker safety.
Real-time monitoring of machine and sensor data to reduce downtime.
Data-driven maintenance to detect failures early and cut costs.
Seamless tracking of assets and material flows in production and logistics.
Automated collection and management of production and operational data.
In our podcast, we bring together users and manufacturers to discuss concrete challenges in data transmission — from both a technical and business-case perspective. Tune in for practical insights and proven solution approaches.
ZEISS uses the middleware “Orchestra” by soffico to implement a scalable integration platform that standardizes data collection across diverse OT and IT systems. Thanks to an intelligent template structure and standardized “channels”, new machines can be connected easily – regardless of protocols or manufacturers. The result: High flexibility, unified data models, and a solid foundation for cross-functional smart factory use cases.
Find out how the Uhlmann Group and soffico are collaborating on scalable data connectivity in the Factory-X lighthouse project – enabling greater interoperability and sustainable production. Using technologies such as the Asset Administration Shell, OPC UA, and ECLASS, they are developing use cases for machinery and plant engineering that establish standards and unlock new digital business models – sovereign, modular, and open.
Find out how Storopack and ENLYZE are implementing data-driven OEE and performance management in day-to-day production. The solution digitizes processes, reduces waste, simplifies training, and enables data-based decision-making. A best practice for improving efficiency in plastics processing.
Whether you need initial insights, specific questions or concrete use cases – we can help you! Contact us for individual consultation and solutions.
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IoT is the common abbreviation for the Internet of Things. The definition to the meaning is wide, so we translate the terms from industry to practice here.
Whatever you call it, you’ll find it here without “buzzword bullshit bingo.”
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