=Paper=
{{Paper
|id=Vol-2114/paper9
|storemode=property
|title=Enterprise Architecture Planning for Industry 4.0
|pdfUrl=https://ceur-ws.org/Vol-2114/paper9.pdf
|volume=Vol-2114
|authors=Emmanuel Nowakowski
}}
==Enterprise Architecture Planning for Industry 4.0==
https://ceur-ws.org/Vol-2114/paper9.pdf
Enterprise Architecture Planning for Industry 4.0
Emmanuel Nowakowski
Supervisor: Ruth Breu
Department of Computer Science
University of Innsbruck, 6020 Innsbruck, Austria
emmanuel.nowakowski@uibk.ac.at
Abstract. Industry 4.0 (I4.0) is a trend that substantially influences the manufac-
turing industry and is an increasing driver of change. However, companies are
struggling with conducting the often expensive and risky IT transformation pro-
jects that are needed to reach goals like full automation of the logistics, produc-
tion, and sales cycle. In our work, we give evidence for a lack of research on the
practice of planning IT transformations towards I4.0. Additionally, we observed
that guidance in this direction is strongly needed in practice. Our research aims
to fill a part of this research gap. Additionally, our research aims to guide practi-
tioners in their digital transformation by providing a planning process, a meta-
model for I4.0 and tool support for I4.0 transformation planning.
Keywords: Enterprise architecture management, Industry 4.0, Enterprise archi-
tecture planning, Industrial Internet of Things, Transformation, Modeling
1 Introduction
Industry 4.0 is a trend that aims to achieve full automation of the value chain and pro-
duction individualization [1, 2]. This is realized with the integration of cyber physical
(production) systems (CPS) with the traditional enterprise IT as well as the point of
sales.
CPS are physical entities that are equipped with technologies such as radio-fre-
quency identification (RFID), sensors, or embedded systems [2–4]. Furthermore, CPS
enable products, humans, and production machines to communicate within a larger sys-
tem [5]. This type of communication is not new, but it leads to new challenges due to
the pervasiveness in all types of supply chains and organizations [4]. In our already
published research on the planning of I4.0 transformations [4] we were able to extract
the core challenges of such digital transformations. The results confirm that the intro-
duction of I4.0 leads to a new level of IT complexity. As a consequence, companies are
forced to apply a holistic management approach of their production, IT, and business.
In order to materialize I4.0 in a company, usually expensive and risky transformation
projects are conducted [4]. These projects need to be thoroughly planned for being able
to successfully realize value [6, 7]. An example for such a project is the reduction of
architectural silos like unconnected production machines (mostly legacy systems) that
work on their own without sharing valuable data [8].
Our claim is that for the successful planning of digital transformation projects, en-
terprise architecture management (EAM) methods need to be applied. Enterprise archi-
tecture (EA) gives a strategic view of an entire company from business and IT perspec-
tive [4, 9]. This is mostly achieved with the help of models of the company’s current
architecture.
EAM is concerned with the reduction of IT costs and the optimization of IT support
for business execution. One of the core processes of this IT management discipline is
EA planning, as described in established EA frameworks like TOGAF [10]. EA plan-
ning is conducted by modeling to-be architectures (also referred to as scenarios) that
transform the as-is (current) architecture into a specified target architecture [11]. The
overall goal is to plan IT transformations aligned with the strategy of an organization
as a whole [12].
Such IT transformations are usually conducted in a sequence of phases and aim at
meeting the current and emerging requirements of the business [12–14]. The planning
phase is one of these phases. After this phase, the planned transformation steps are
documented, executed and evaluated [4].
When the planning of a digital transformation is not conducted correctly, it possibly
results in failing projects and therefore in high financial losses [4]. Currently, organi-
zations are planning their transformations with the help of MS Office tools and mostly
based on outdated information [4, 12].
Due to the observed challenges in practice and the missing solutions in theory as
well as practice, our main research interest is the application of EA planning on this
kind of transformation projects.
In this paper, we propose artifacts that will contribute to theory and practice by
providing state of the art solutions to specific problems that were derived in our already
published research, like the documentation of I4.0 in general, the documentation of I4.0
transformation projects and the planning of such projects.
In Section 2, our research problem is described in detail. Furthermore, in Section 3
our research methodology is discussed. Section 4 outlines our objectives. In Section 5
the related work, or state of the art, is presented. Section 6 describes in which stage our
research currently is and concludes this paper.
2 Research Problem
In [4] we extracted the core problems considering digital transformations with the help
of expert interviews. Among the identified challenges are the increasing complexity
due to the introduction of I4.0, the currently insufficiently managed and documented
IT landscapes, and the communication between the business IT and the operational
technology (OT) departments [4].
In addition, we were able to gather seven core findings. This outcome overlaps with
the results from our more general research on EA planning requirements [12]. Two of
these findings are described in more detail because they support our research problem.
74
First, we were able to extract that in some companies EAM is specifically introduced
for launching I4.0. According to the interviewees, this is due to the additional complex-
ities that are going hand in hand with the digital transformation and the need to manage
them accordingly. This supports our claim that there is a need for sophisticated man-
agement methods when it comes to an introduction of I4.0 and that EAM methods are
suitable for this kind of challenge.
Second, some of the interviewees mentioned the need for a process for modeling and
planning and for a metamodel that supports I4.0 transformations. Hence, practitioners
would like to have more guidance and a structured process for the planning and mod-
eling of such projects.
To help companies with this endeavor we will develop solutions to the problem of
planning IT transformations towards I4.0 concepts. These will be also important input
for the topic of EA planning in general. Finally, we will help to manage the higher IT
and EA complexity, which result from the transformation to I4.0.
Therefore, we aim to answer the following research questions (RQ):
RQ (main): How can EA planning support the transformation to I4.0?
─ RQ1: What are the requirements of EA planning?
─ RQ2: How are I4.0 concepts currently documented and how could the documen-
tation be optimized?
─ RQ3: What kind of information is needed to support the documentation of I4.0
transformation projects?
─ RQ4: How can tools support I4.0 transformation planning?
3 Methodology
The conducted research is based on Hevner’s design science research (DSR) method-
ology [15]. Here, the proposed three-cycle approach is used [16]. It comprises a rele-
vance, a rigor, and a design cycle. The DSR method aims to create IT artifacts that solve
organizational problems and to rigorously evaluate them [15]. Therefore, DSR fits well
to our goal of creating research artifacts iteratively with the feedback of our industry
partners. The DSR methodology in combination with our research output associated to
the research questions is depicted in Fig. 1.
One of Hevner’s proposed cycles is the relevance cycle that builds the connection
between the design science activities and the contextual environment of the research
project [16]. In this cycle, the opportunities and problems in a specific domain are iden-
tified. Additionally, the relevance cycle defines the acceptance for the evaluation of the
research criteria. We already published two papers that are part of this cycle. The pub-
lication about planning in the context of I4.0 transformations [4] is mostly part of the
relevance cycle due to the research goal of gathering existing problems and require-
ments. Additionally, the series of expert interviews from the paper about requirements
for EA planning [12] is also part of this cycle.
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The rigor cycle provides knowledge from past research to the research project to
ensure its innovation [16]. It also comprises additions to the knowledge base as results
from the DSR. The above-mentioned requirements paper [12] is also located in this
cycle because it contains an extensive scientific literature review on the topic of EA
planning.
Finally, the design cycle, the heart of the DSR methodology, iterates between the
construction of an artifact, its evaluation, and the feedback from the evaluation to refine
it further. Here, the inputs are the requirements from the relevance cycle and the design
and evaluation theories and methods from the rigor cycle [16]. Our remaining work will
be mainly located in this cycle and will be described in detail in the following section.
Fig. 1. DSR applied to our research (based on [16])
4 Outline of Objectives
As starting point of our remaining research, we will use the results from [4] that dis-
covered a strong need for a metamodel for I4.0 specific EA planning in the context of
IT transformation projects. This is mainly due to the higher complexity of the IT land-
scape that is introduced with I4.0 and the need for its management.
Additionally, we were able to observe the need for a standardized EA planning pro-
cess for I4.0 transformations [4]. This was also observed for the general task of EA
planning [12]. Here, most of the interviewees reported that they were struggling with
the planning of their companies’ EA. That is mainly due to the missing support of tools
and the unstructured process, which is used for EA planning. Hence, we learned that
there exist neither a standardized EA planning process nor sufficient tool support to
guide companies in their planning endeavors. Therefore, we will analyze the tool sup-
port for EA planning by extracting and comparing the relevant features of EA tools that
are listed in Gartner’s Magic Quadrant [17] in the context of our results from [12] and
[4].
As the first design artifact, we will propose a metamodel for IT transformation plan-
ning. The goal is to guide companies in what should be documented in an EA model
and how the specific metamodel elements should be associated to each other to be able
to conduct EA planning in I4.0 IT transformations.
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For this purpose, we plan to enhance the classical three layer approach of EA docu-
mentation (business layer, application layer, and technology layer) [10]. As discussed
in [4], the newly introduced assets differ from the classic assets. One of the main dif-
ferences is that it is not possible to distinguish between the application and the technol-
ogy layer anymore. Due to this, we will introduce a fourth layer named the operational
layer. In this layer, the core assets of the automation architecture will be located and
connected to the classical layers used for documenting the other parts of the EA.
For the decision on what assets need to be modeled in the operational layer, our
results from [4] will be revisited. Additionally, we will analyze the classical automation
pyramid and its adaptations for I4.0 (see Fig. 2) in order to have a holistic picture of the
possibly needed assets. We will also investigate dedicated I4.0 reference architectures
like the one from IBM [18], and, in addition, ArchiMate 3.0 [19], which contains a
physical layer for modeling e.g. machines, so as to evaluate currently available methods
for modeling these assets. Furthermore, the automation assets now need to be part of
the EA, which is new because in the past the operational technology (OT) was strictly
separated from the business IT [4]. This is another reason why the new operational
layer, in which the relevant OT assets are connected to the classical EA layers, needs
to be introduced. For the associations between the OT and business IT we will consult
I4.0 frameworks like the “Reference Architecture Model Industrie 4.0” (RAMI 4.0)
[20] that propose a standardized communication between these layers.
Fig. 2. Decomposition of the classical automation pyramid (based on Monostori [21]) and the
proposed 4-layer approach for EAM
The automation pyramid is the current standard model in which the classical layers
and components of industry automation are depicted and described [22]. This pyramid
usually consists of a device layer, a control layer, a layer for the manufacturing execu-
tion system (MES), and an enterprise resource planning (ERP) layer. At device level,
the production machines with their sensors and actuators are located. Furthermore, at
control level the controllers for these machines are positioned. The MES level consists
of the execution system that controls the execution of production in real-time. Finally,
the top level of the classical automation pyramid is the ERP level, which constitutes the
connection to the business. The communication between these layers is hierarchical.
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With the introduction of I4.0, these layers need to be broken up into the new CPS-based
automation [21] (see Fig. 2) in order to establish information links between the compo-
nents.
As the second DSR artifact, we propose a planning process that will be implemented
in the form of a TOGAF Architecture Development Method (ADM) extension. TOGAF
ADM is the core of TOGAF and describes a method for developing and managing the
lifecycle of an EA [10]. Furthermore, it is a rather generic framework that does not
include a description of a process for I4.0 integration and transformation planning [4].
The need for a TOGAF ADM extension is a result from our interviews that are dis-
cussed in [4]. This extension will help companies with conducting EA planning in a
structured manner, which will help them with implementing their planning initiatives.
The planning process will be closely connected to the above-mentioned metamodel,
which therefore is also part of the TOGAF ADM extension. Furthermore, the process
will be developed with the help of a case study, which will be created in collaboration
with our industry partners and experts in the field of I4.0 transformations. After that,
our proposed method will be applied to this case study and be evaluated again. The
outcome of this process will consist of several best practice approaches for conducting
EA planning in the context of I4.0 transformation projects. For example, it will incor-
porate modeling guidelines, useful metrics and comparison guidelines for different
plans of the to-be architecture, and step-by-step guides for typical planning problems
in specific domains. This is especially useful because currently companies are planning
based on outdated data, in an unstructured way, and have problems with the comparison
of the different planning scenarios, which could lead to problems in bigger planning
initiatives like I4.0 transformation projects are [4, 12].
Both of the above-mentioned IT artifacts will be implemented within a tool for au-
tomated EA documentation that is a result of our previous research [23]. This will con-
stitute our third DSR artifact. In addition, it will be used for the evaluation of the met-
amodel and the EA planning process.
The evaluation and validation of our research artifacts will be performed with the
help of our industry partners and experts in the field of I4.0 introduction and transfor-
mation. The latter include consultants that are involved in such type of projects, auto-
mation experts, and enterprise architects from this field. Relevant industries for evalu-
ation are in general all industries that are concerned with industrial production (like
discrete and process manufacturing) and telecommunication.
For evaluation, the mentioned stakeholder groups will test the tool with its new plan-
ning feature (our third DSR artifact). As a next step, we will gather feedback on the
usefulness and practicability of our approach in expert interviews and, if possible, in
focus group discussions.
The gathered feedback will be iteratively implemented in the research artifacts, as
proposed by our chosen DSR methodology.
78
5 State of the Art
From the structured literature review in [12] we learned that there are two main clusters
of researchers that published on the topic of EA planning.
One of these research groups is Aier et al. from the University of St. Gallen who
focused on the process of transformation planning in the course of which they devel-
oped a process model for EA planning in [24]. Additionally, they created an integrated
information model that describes EA transformation planning as well as a system that
accounts for the interplay of EA planning, release, requirements, and synchronization
management [12, 25].
The second cluster of researchers is Buckl et al. who worked on an information
model for application landscape evolution in [26]. Moreover, they focused on how to
model enterprise architecture transformations [12, 13].
The publications of the two groups are mostly of conceptual nature except for a pro-
totype that is described in [27]. Furthermore, the research of these two research groups
is concerned with EA planning in general and not with the implementation of EA plan-
ning methods in the field of I4.0 transformations.
Therefore, we conducted another literature research focusing on the application of
EA planning for digital transformations [4]. Hereby, we learned that there currently
exists no research taking EA planning into consideration that is able to overcome the
challenges of planning I4.0 transformation projects [4]. Furthermore, we were able to
identify one main cluster of researchers that is related to our research. Zimmermann et
al. published on the topic of Digital Enterprise Architecture in the context of the Internet
of Things (IoT). In their work, they discuss the evolution of EAs, the transformation of
EA for the IoT, and architectural decision-making for digital transformations [4, 28–
30].
Zimmermann et al. define an architecture reference model named Enterprise Ser-
vices Architecture Reference Cube (ESARC). It adapts already existing architectural
frameworks for services and cloud computing [4]. However, the authors do not discuss
how the planning of target architectures in the context of I4.0 or IoT should be con-
ducted. Additionally, Zimmermann et al. developed a metamodel for EA decision-mak-
ing that consists of a decision-making process. Yet, a method to support practitioners
to model their I4.0 transformation projects is still missing [4].
6 Stage of the Research & Conclusion
Our understanding of EA planning is based on the results of a literature review and a
series of interviews on the requirements of EA planning, which is discussed in [12]. We
were also able to identify current problems in the documentation and planning of I4.0
transformation projects. These results build the basis for my future research on the DSR
artifacts that aims to solve those problems. The next research step is to conduct a tool
survey that compares EA planning features of existing commercial EA tools in the con-
text of our interview results from [12] and [4]. This also concludes the theoretical back-
ground that is needed for working on the DSR artifacts. After that, the first and second
79
IT artifact, the metamodel and the process for EA planning in the context of I4.0, will
be developed. Both artifacts will be part of a TOGAF ADM extension that helps with
a structured way of planning I4.0 transformation projects and gives advice on how and
what to document for I4.0 in general. The majority of this work will be finished until
the end of 2018.
We studied the challenges of EA planning in general and specific to the context of
I4.0 transformations. We were able to extract possible solutions for these challenges
that are subject of my future work. From the interviews we have already conducted, we
learned that companies need a metamodel for EA planning and a specified EA planning
process to be able to conduct the planning in a structured manner. In general, the inter-
views suggest that there is a need for standardized models and methods for I4.0 initia-
tives.
Acknowledgements
This research was partially funded by the research project “txtureSA” (FWF-Project P
29022).
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