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communication, e.g., for interfacing an ERP system directly
with sensors, is challenging and requires significant changes.
Changes in production processes, e.g., to introduce a new
product variant, require similar changes. Even if a change is
local and affects only one production cell, it may cause side
effects. Production cycle times may change and might
therefore no longer match the cycle time of the process.
Furthermore, modern PLCs are networked and provide data
to other PLCs. Changes in their programs may cause data to
arrive late, which also disturbs the process. The grown and
proven system architectures of production processes are
therefore not able to fully support the requirements on a Figure 2 – Industrie 4.0 maturity index [1]
changeable production system that can adapt to today’s
quickly changing markets. The first step towards Industrie 4.0 is level 3 of the maturity
model, i.e., the ability to visualize (“seeing”) the production.
The fourth industrial revolution is the end-to-end Achieving this level requires the creation of a digital twin
digitalization of production. It is not about the substitution of that consolidates the available data, such as data sheets,
PLCs or the introduction of new devices, but about new digital nameplates, live data from sensors and machines, or
system architectures that enable peer-to-peer communication data from MES and ERP systems. The consolidation of data
to support, for example, predictive maintenance, AI-based from heterogeneous sources into digital twins is the major
anomaly analysis in production, and efficient production of challenge in this step. Base technologies, such as OPC-UA
small lot sizes. Industrie 4.0 is therefore not about the (the OPC Unified Architecture) support this by defining
integration of a single new technology. It is much rather the unified protocols for data exchange between machines. In
introduction of new architecture paradigms to enable a more addition to basic communication, this step also requires the
flexible, and a more changeable, production that will yield harmonization of data models, data types, and semantics,
future competitive advantages. which requires domain knowledge. The creation of OPC-UA
companion specifications is an ongoing activity for the
In the domain of IT systems, Service-oriented Architectures creation of data models that conserve existing domain
(SoA) decouple systems into independent components and knowledge. Next, level 4 of the Industrie 4.0 maturity model
yield both scalable and changeable software systems. In this is about increasing the level of transparency in production
paper, we describe the application of SoA to production and increasing the understanding of why it is required and
systems. We discuss requirements and Industrie 4.0 the effect that it creates. Digital twins are used to get this
challenges, and provide an overview of Industrie 4.0 understanding and to realize, for example, condition
technology and solutions that support the implementation of monitoring systems. Level 5 of the Industrie 4.0 maturity
SoA principles. We furthermore document our experiences model covers the prediction of future effects based on live
in digitalizing production environments with our open- data and past experience. Using a digital twin to realize
source Industrie 4.0 Service-oriented Architecture Eclipse predictive maintenance is one example of this level of
BaSyx. maturity. Level 6 of the Industrie 4.0 maturity model is the
highest level of maturity. It covers the autonomous
2. I4.0 CHALLENGES AND CONCEPTS adaptation of manufacturing processes, e.g., the optimization
of machine maintenance intervals based on predicted
Numerous Industrie 4.0 challenges are currently arising in maintenance times.
industry. The Acatech Industrie 4.0 maturity index [1]
organizes solutions to these challenges based on the maturity These levels of the maturity model describe the technical
of an organization and outlines the steps required to reach a maturity of a production environment. An assessment of the
higher degree. It is based on the degree of digitalization a capabilities of a (digital) production environment also
company has achieved. requires consideration of the types of integrated assets. A
digital twin may cover an individual machine or integrate
2.1 Industrie 4.0 challenges and maturity data from all machines and sensors of a production line, as
well as of MES and ERP systems. The more assets a digital
The first two steps of the Acatech Industrie 4.0 maturity twin represents, the more advanced challenges can be
index are computerization and connectivity. Both are addressed with this digital twin. Figure 3 illustrates this by
prerequisites for Industrie 4.0 transformation, but not yet part extending the maturity levels of [1] with the degree of
of Industrie 4.0. Computerization covers the automation of horizontal digitalization in the production process.
repetitive tasks. This is well developed in most
manufacturing companies. Connectivity is about the
substitution of proprietary field bus systems with
standardized networking technologies.

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