Meet the Expert Webcast Series – IoT

What is (I) IoT / Industry 4.0 (Business) Integration?

One of the effects of digitalisation has been that networked intelligent and autonomous systems have made their way into industry, issuing in the 4th industrial age, or industry 4.0. At its core is the so-called Internet of Things (IoT) and its close cousin the Industrial Internet of Things (IIoT). These enable both real and virtual machines and processes in industry to be networked, both within and between companies.

Why are data and process integration also important for IIoT and industry 4.0? How can SEEBURGER support you in your company’s journey to an industry 4.0 firm? Read on for a comprehensive introduction to business integration for industry 4.0 and (I) IoT and find out how you can guide your own digital transformation, with you in the driving seat.

1. IIoT / Industry 4.0, Disruption or Evolution?

The autonomy and intelligence of objects and devices has been steadily increasing. Coupled with having access to data wherever you are via the internet, it has become far easier for business partners to cooperate with each other. This has had an enormous effect on productivity and fundamentally changed the entire economy. Indeed, these developments could be considered as radical as the changes which issued in the previous three industrial ages.



What are IIoT and Industry 4.0? Computer technology has been present in all areas of industry for decades. It significantly supports us in our planning, decision and implementation processes. At the same time, the internet has become the most important communication channel and marketplace for products and services. However, it has only been through these developments encroaching into our tangible space, even down to our household and leisure objects, that the potential of industry 4.0 has been recognised. This has led to digital twin technology. Previously confined to product simulations to support the development of product variants, digital twins are now being used for virtual and real scenarios in production, logistics and after-sales.  They have been directly integrated into processes, or are involved in automated interactions and transactions over a platform. This enables a company to tailor their production even closer to customer requirements, fulfilling individual wishes right down to a single, fully-customised product, within a feasible budget and time frame. The logistics sector is moving towards service-orientated on-demand logistics, while services, after sales, marketing and distribution are beginning to create their own data-based commercial ecosystems which give root to new service models. For this, IoT serves both as a network and a medium. It enables more comprehensive networking in industry 4.0 and therefore new ways of optimising processes even beyond the company’s four walls. However, it also enables completely new ways of doing business to materialise, addressing aspects of centralisation, participation and cleverer ways of dealing with data.  

All of this assumes that the technical systems, applications, services and equipment in a company can seamlessly interact with each other. Integrating processes and data is still a challenge for many companies, as, as far as digitalisation is concerned, many could do with a boot camp in preparing Industry 4.0.

Where are companies today in regard to industry 4.0?

On its path to becoming an industry 4.0 organisation, a company needs to upgrade its information systems to be ready to cope with the inevitable changes in business processes. These days, the biggest hurdles to implementing IoT / industry 4.0 projects are considered to be an inability to collect and analyse data and insufficient data security.  

At the Gartner Application Strategies & Solutions Summit in Las Vegas in December 2019, participants were asked what technology was considered to be a game changer in their companies. IoT was only in fourth place, behind AI, data analytics and cloud issues. Nevertheless, companies were planning on increasing their investment in IT for IoT by 12% in 2020, expecting a return on investment in 3 years. According to a study by the DSAG in 2019, outdated IT systems and the corresponding need for legacy system integration was seen as the biggest challenge in digital transformation. At the same time, money was being invested in new technologies, meaning, for example that the percentage of companies who are actively using digital twin technology is expected to increase from 12% to over 50%.

If we pose the question whether (I)IoT and industry 4.0 are just trends or whether they represent a fundamental change, the answer is unequivocal.  With the opportunities that the Internet of Things offers in every area of economy and industry, the fourth industrial revolution represents a fundamental transformation of the value chain. These opportunities include cloud computing, platforms, data analytics and AI, but also integrating ʽthingsʼ into business processes, as in the Internet of Things. Around 50% of manufacturing firms of all sizes and in the widest range of industries have either already implemented IoT projects or have made concrete plans to do so, whereas the other half are intending to do so in the next few years. Current studies show that companies are increasingly recognising that their IoT projects can only be successfully and sustainably implemented if they give the issues of hybrid integration top priority (GARTNER, 2020).

2. Examples of IIoT and Industry 4.0 in Practice


Real world examples of IIOT and industry 4.0 in use can be found in a variety of areas. A major area of application for industry 4.0 is in the automation and optimisation of operations through intelligent, autonomous, technical systems. New forms of man and machine working together are being developed in industry (cyber-physical systems). This means that individual customer requests for highly customised products all the way down to a batch size of just one, to be manufactured.

A further driving force for the increased use of IIOT and industry 4.0 solutions is meeting individual customer expectations. Consumers no longer only expect a high-quality product. They want to also be able to take up associated services to optimisehow effectiveness and efficiency of the product’s functions. In order to meet this demand, companies are now needing to set up entire digital ecosystems. These are used in all areas of business, from Research and Development through to Marketing and Sales via production, logistics and after-sales services. Indeed, if you consider smart cities or the analysis and use of weather data, you can see that digital ecosystems reach far beyond the commercial world.

In collaborative product development data on user behaviour and product condition plays a significant role in developing new and improved products. So that production processes can run smoothly with no unplanned downtime, maintenance providers can pull data on running time and condition directly from the machine itself to plan regular servicing and recognise impending faults before they cause the machine to break down - either temporarily or for good. This is known as predictive maintenance. Modern track and trace techniques open up wonderful opportunities in logistics to use sensors to determine in real time where goods currently are, meaning that delivery times can be precisely calculated for both production planning and sales. Smart products open up brand new avenues in after sales. Washing machines, for example, could send data on the number of cycles spun and other usage statistics directly to the manufacturer, setting the stage for both maintenance and service offerings on the one hand, and pay-per-use models on the other hand. Marketing and sales have access to sales figures in real time, sent directly from the point of sale (POS), which gives them a consistently up-to-date basis for planning campaigns and promotions, as well as for measuring customer satisfaction.

The possibilities opened up through IIoT and industry 4.0 solutions are manifold. However, a significant challenge set by both IIoT and industry 4.0 is to get your IT infrastructure in a good enough shape to take advantage of them.

3. What is IIoT Integration and What Can it Do?

The industrial, manufacturing economy depends on reliable and efficient production resources and value chain processes. Should new services and intelligent (autonomous) systems be introduced into the production process, it’s important to keep these manageable and sensible for both employees and the organisation as a whole.


The increasing networking of the real and the virtual world in every part of a company requires the ability to integrate with hybrid system landscapes. This doesn’t just mean setting up and using traditional (programme) interfaces or even releasing and using as them as micro services, rather enabling individual objects and their digital twins to be part of an end-to-end or hybrid network. This includes various forms of end-to-end data exchange and data integration in the value network, as well as new concepts such as event-based data nodes (publisher-subscriber) or data hub environments (data lakes/data pipelines).

Companies are still being faced with the task of increasing their service-based offerings, while also digitalising these. In order to transform new business models into viable, robust B2B business relationships, companies need to massively increase their IT capability. This gives rise to opportunities as well as risk, as a company’s own services and supply chain need to be redefined as further resources such as an IPaaS are added. Relationships and co-operations with existing B2B suppliers and clients need to be rejigged, and connections made to new parties.

Inside perspectives

Organisations need to increase their ability to react, adapt and learn in order to secure their success in a dynamically changing value chain. A hybrid integration concept needs to ensure that a company’s systems have the level of transparency and interoperability they require to stay flexible and to be continuously improved.

The advent of industry 4.0 is transforming production, making it possible to produce individual, fully-customised products. Increasingly shorter production cycles are forcing manufacturers to adopt production systems which are flexible and easy to adapt. Alongside end-to-end control communication, there needs to be a different type of information flow between the shop and top floors: a continuous exchange of data between engineering and production. This allows pieces to be followed through production, while a continuous exchange of information on the technical health of the assembly line prevents breakdowns and automates maintenance and configuration to a certain extent.  There are even options like utilising lightweight robots in collaborative assembly with human operators for more flexible production automation.

Examples in use – within the organisation

Flexible production systems

Large-scale manufacturers have been using IT systems for years to plan and simulate their production facilities. Before the physical machines are delivered, a digital machine folder is created and filled with the supplier’s files. These are used for virtual commissioning and are then kept in the planning systems as a digital model of the machine during the start-up and usage phases. The SEEBURGER Business Integration Suite (BIS) takes on the integrative role of an engineering data hub to track and update the condition of the resources, and any alterations made to them. This ensures that the virtual image always mirrors the condition and configuration of the real machine. Using the administration shell within the BIS as a model, a machine and other operating resources can be flexibly integrated into the planning and control systems as Plug & Produce. This immensely reduces the workload associated with commissioning and customising, allowing systematic, efficient management of your transformation needs. The efficiency you gain in customising your production facilities is an excellent argument for using further intelligent, autonomous systems.

Human + Machine collaboration in manufacturing

Employing flexible, scalable automation solutions in manufacturing, such as human + machine collaboration, requires end-to-end data exchange and integration between the shop and top floors.  The SEEBURGER Business Integration Suite (BIS) ensures an event-driven, context-sensitive information flow between the process controller, machine operators and monitoring systems, these days often accessible to employees on a mobile device. This is all necessary to ensure that enough raw materials and components are available at any time, to secure flexibility and to enable order-driven production.  If a specific order requires adjustments to be made to the process or further functions to be added to the production facilities, the BIS lets you either make these directly or communicate them to the operators. The BIS operates as middleware and an integration service bus to ensure inter-operability and information flow between the systems on the shop floor.

Outside Perspective

An IIoT and industry 4.0 integration approach on an intra-company basis needs to consider the entire value chain and all the various B2B processes. At the centre is the desire for effective, efficient and secure collaboration between all areas in the organisation.  At the beginning is usually engineering and product data exchange, or an existing EDI partnership, which requires a cloud platform service, applications and objects to be integrated so that the process as a whole can be controlled and automated.  Logistics processes are also being optimised through integration, from end-to-end supply chain monitoring to production facilities and digital ecosystems being networked with one another.

The importance of integration in B2B is these days less about enabling efficiently automated processes and more about how effectively and efficiently data can be provided to help steer strategy and improvement along the entire value chain.  Customers are only prepared to pay for individualised, customisable product functions. This requires knowing your customers very well, continuously checking their expectations and implementing these quickly and efficiently. A good (business) integration platform will be able to furnish you with the necessary end-to-end information logistics for this.

The ever increasing expectations on the availability and customisation of products and resources requires a tight, frictionless flow of information between suppliers/providers and customers. Risks – and opportunities – need to be recognised at an early stage and the offering adapted so that customers receive what they want. You also need to be able to introduce and offer new services based on this data through the product itself. The processes behind this need to be well mapped, and encompass the situations in which the product is used as well as a flow of data on the condition of the product and the impact it is having. Building your own IoT platform is only the first stage in networking household and other objects.   In reality, integration must let you offer new services directly from and through the object itself – naturally with the permission of your business partners. Your company’s processes need to be set up to enable this.

Examples in use – beyond the company

Ensuring you have the parts you need with an anticipatory ordering system

Suppliers of equipment depend on particularly fast, flexible and frictionless logistics processes, be that component delivery or maintenance on production lines, to enable a fast throughput on their assembly lines.  Manufacturers using Vendor Managed Inventory (VMI) needs to use a predicative needs analysis. Using the BIS IoT / industry 4.0 solution, and Kanban-based production facilities can be extended to continually – or periodically – exchange information on components used and required. This is then compared with service and supply capacity so that any necessary delivery can be organised quickly.

AR-based assistance systems

In the digitalisation of the construction and agriculture sectors, modern machinery is taking an ever more prominent role within the value chain.  Alongside a multitude of configuration options and add-ons, digital services such as geographic information systems (GIS) and the ability to collect and interpret data from sensors has greatly increased the productivity and efficiency of the machinery.   By integrating further IoT services, such as location-based services and data analytics, assistance systems can be tailored to a specific customer and made available within a process through an app. SEEBURGER’s BIS enables the necessary infrastructure and integration for platforms of this type,   which also smaller machinery providers can use to drive their transformation to product and service providers.

Companies need to see integration as essential groundwork for preparing themselves for an industry 4.0 environment. Successful companies don’t just develop innovative solutions but also consider integration needs in their corporate strategy from early on.

4. Challenges in IIoT Integration

Architectural levels in IIoT integration

In Industry 4.0, products and resources carry a digital image of themselves (digital twins). This real and this digital world need to be brought together – integrated. This involves connecting data flow through standardised interfaces, as well as creating an administration level which can uniquely identify both the real objects and their digital twins and communicate with them both.


IT architecture is in a state of flux. In order to enable companies to participate in and indeed shape a networked, digital ecosystem, they need to improve integration at all levels so they can provide new, data-driven services.  There is the edge layer, comprising the physical objects, their assets and periphery. This is followed by the platform level, with its central IoT cloud applications and data hub environment. This provides access to the digital ecosystem and your own EAI stack, with its back-end and management systems, and applications.

In coordinated data and process integration, there needs to be the appropriate facilities available to specify and process data streams, allowing a link between the things themselves, business and IoT events, and operational process control. From the dual perspective of process and data integration, you need to consider the following aspects:  

Integration dimensions

Horizontal integration

If you wish to guarantee optimal products and services, you need to consider the value chain throughout the entire product lifecycle – from development to production to use to maintenance/after sales.  To this end, it is necessary to be able to compare actual performance with targets you have set at every stage and across disciplines. In practical terms, you will need to integrate various parties into the flow of information, including external parties like the manufacturer of an assembly line, so that they are able to proactively react to anticipated issues with the technology.

Vertical integration

Vertically integrated business models require data and processes to be integrated end-to-end over every function and communication level. Interoperability, interaction and the ability to map processes needs to be ensured at every level.  In practical terms, thus means that an automation line in the company needs to have an integrated flow of data from the sensors and ERP system built into the IoT/ industry 4.0 architecture. These elements can then be assigned individual tasks and monitored based on the order specifications, and the process and quality control frameworks.

Demands on integration


By using reference models and recognised standards in interfaces – such as APIs – you can ensure that your systems and your partners’ systems can work with each other. This inter-operability requires data to follow a common semantic model so that master data can be merged with data from processes and machines.  It’s only then that companies can take proper advantage of this data to support decision-making, to support workflows through new digital services and to increase quality and productivity in processes. Integration needs to be carried out in a structured, logical way to ensure the aspired information flow between different areas.   


Naturally, IT, file and device security need to be sustainably secured from the very beginning for the entire security lifecycle. In a complex digital ecosystem, there are always vulnerable components that can become a gateway for attacks, with new vulnerabilities being discovered every day. Taking a security-by-design approach requires companies to consider security issues in all areas and at all levels from product development. And integration moves need to ensure that data security and by extension data sovereignty is not compromised.  


By using reference models and recognised standards in interfaces – such as APIs – you can ensure that your systems and your partners’ systems can work with each other. This inter-operability requires data to follow a common semantic model so that master data can be merged with data from processes and machines.  It’s only then that companies can take proper advantage of this data to support decision-making, to support workflows through new digital services and to increase quality and productivity in processes. Integration needs to be carried out in a structured, logical way to ensure the aspired information flow between different areas.      


Newer technologies for processing and analysing data from distributed systems (big data, analytics and AI) are essential components of a system in this era of industry 4.0. They enable an ever growing mass of data from networked systems, applications and objects to be merged and analysed. Companies use the insights from this analysed data to kick start new automation and optimisation measures. This often begins by monitoring, gathering and analysing data from inventory systems and sensors in the manufacturing facilities, and leads to context-based evaluation of aggregated data, maybe progressing to company-wide integration approaches (such as using a manufacturing service bus (MSB)). The aim is to increase the degree of automation of processes and individual resources by enabling them to autonomously make decisions and alterations through intelligent systems. To this end, they also need to be supplied with a flow of relevant data. Consistency is key: decisions and processes are linked, and your integration approach needs to always bear this in mind.  


Working across industries will always lead to a plethora of technologies and data standards existing alongside each other, which make it impossible to create B2B business processes in an industry 4.0 or IOT environment without adopting integration solutions.  Whether the digitalisation approach has performance, the customer or the supply chain at its core, there will always be the need for data and information flow beyond departmental and company borders. This needs to be flexible, seamless, consistent and able to deal with an increasing amount of data, interfaces and services. In order to leverage the potential offered by industry 4.0 and the internet of things, there needs to be an integration approach, which at its foundation ensures the interoperability of business applications and digital twins. This approach needs to enable data-driven services both in-house and beyond the organisation. A hybrid integration platform gives you the basic framework you need to integrate products and resources (assets) and the digital services based on these into your business processes.

Equip yourself for the future and invest in hybrid integration capability for IOT.  SEEBURGER AG can support you in actively creating a targeted business integration strategy for industry 4.0.

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