Life Cycle-Oriented Evaluation of Cyber-Physical Systems
K. Höse and U. Götze
Faculty of Economics an Business Administration, Chair of Management Accounting and Control,
Technische Universität Chemnitz, 09107 Chemnitz, Germany
Keywords: Cps (Cyber-Physical Systems), Evaluation, Industrie 4.0, Life Cycle.
Abstract: Cyber-physical systems as technical enabler of “Industrie 4.0” (I4.0) have been discussed in many published
papers. The application of I4.0-technologies allows for an intelligent interconnection between product
development, logistics, customers and production. As a result, it is expected that the implementation of I4.0-
technologies contributes to the protection of economic wealth of companies and society. This trend enables
innovative processes and products right up to new business models. Nevertheless, companies often hesitate
to invest in I4.0-solutions. The uncertainty of the benefit of using I4.0 is one reason making an economic
consideration of I4.0-solutions necessary. Therefore, a structured analysis and evaluation of I4.0-solutions in
form of CPS is the topic of this paper. Firstly, the evaluation requirements are described. One main
requirement is the life cycle-oriented analysis of CPS, because not only the implementation costs and
expenditures are important, but also the prospective costs and benefits of the application of CPS. Afterwards,
a decision theory-based procedure model is suggested to handle the complexity of a life cycle-oriented
evaluation. Within the description of the steps of the procedure model, characteristics and challenges
regarding the evaluation of CPS are discussed. Additionally, instruments and methods, which support the
evaluation of CPS, are presented.
1 INTRODUCTION
The implementation of cyber-physical systems
(CPS), especially in value creation processes, has
become an often discussed topic for companies, since
the “Industrie 4.0” (I4.0)-development arised. I4.0 is
a term resulting from a project initiated by the
German government with the aim of protecting
Germany as competitive manufacturing base
(Sendler, 2013). The main objective of I4.0 was
considered to be the interconnection via internet,
which leads to a merger of the physical and virtual
world. The CPS are the technical enabler for this
connection (Kagermann, 2014). The implementation
of I4.0-solutions by means of CPS enables new
products, processes, business models and possibilites
to manage the value chain processes with new ideas
to organize the production (Kagermann, Wahlster,
Helbig, 2013).
The technical opportunities of the application of
I4.0/CPS have been discussed in many academic
papers. Nevertheless, many companies are hesitating
to invest in these solutions because of the fear of high
implementation costs and the uncertain benefit. Thus,
an economic consideration of I4.0 is necessary as
well. Some studies have been published discussing
the economic impact of I4.0-solutions, e. g.
Obermaier et al. conducted a process- and potential
analysis for an ex-ante assessment of investments in
I4.0 (Obermaier, et al, 2015). An ongoing research
project is examining this economic issue for the
intralogistics (IPRI, 2017). In other papers economic
influences of I4.0 are investigated as well (for an
overview see Braccini and Margherita, 2019), but
mostly for special purposes like the design and
examination of the productivity of a warehouse
management system for smart logistics (Lee, et al,
2017).
The model that is presented in this paper has an
universal character, it is not developed for a special
branch or scope. When examining the economic
impact of the application of I4.0-solutions, it is not
sufficient to analyse only the acquisition costs at the
beginning. Also the follow-up costs, e. g. for
maintenance and recycling, have to be analysed.
Additionally, the benefits of the usage of I4.0-
solutions by means of CPS have to be considered.
Thus, a life cycle-oriented analysis is essential.
332
Höse, K. and Götze, U.
Life Cycle-Oriented Evaluation of Cyber-Physical Systems.
DOI: 10.5220/0007746103320338
In Proceedings of the 4th International Conference on Internet of Things, Big Data and Security (IoTBDS 2019), pages 332-338
ISBN: 978-989-758-369-8
Copyright
c
2019 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
Within this analysis, various challenges like the
complexity of CPS or the uncertainties, especially for
input data and the expected benefit, exist. Therefore,
a set of evaluation tools is necessary. Thus, the
objective of this paper is to present the draft of such a
one. A life cycle-oriented analysis is conducted by e.
g. Thiede, who presents the Life Cycle Assessment
(LCA) as a method to evaluate the environmental
sustainability of cyber-physical production systems –
but without considering the economic perspective
(Thiede, 2018).
The following paper is divided into four sections.
After the introduction, the terms I4.0 and CPS are
explained and the necessity of a life cycle-oriented
evaluation of CPS is justified in more detail.
Afterwards, model requirements are posed and
finally, a general structure for a procedure model for
a life cycle-oriented evaluation of CPS with
suggestions for single evaluation instruments and
methods that can be used within it, is presented as a
basis for following studies. The procedure model is
generally applicable for evaluating all dimensions of
sustainability – the economic, the ecological and the
social one, with the possibility to include existing
approaches like LCA for CPS. However, this paper
mainly focuses on the economic evaluation
considering technical aspects as a basis.
2 CYBER-PHYSICAL SYSTEMS
2.1 Cyber-Physical Systems as Enabler
of Industrie 4.0
CPS are the technical basis of I4.0-solutions, which
include the connection of the production with modern
information and communication technology on the
basis of internet technologies. Beyond the technical
controllability of more flexible production and
supplier industries a profound economical change is
possible. A shift of the classical customer-supplier-
relation is expected, as the traditional supply chains
are broken up. Different areas of industry, e. g.
machinery and plant engineering, have to be enabled
to develop new products and services as well as
business models with the help of digital technologies
(Drossel, et al, 2018).
For I4.0, no homogeneous definition exist.
Therefore, different interpretations of the term were
compared and the following definition was developed
(based on an analysis of different definitions for I4.0):
I4.0 is the utilization of the Internet of Everything in
the production domain. On the basis of real-time
available intelligent data, elements like humans,
things, and services are linked and exchange
information. The crosslinking in form of integration
of IT-systems occurs internet-based – in vertical as
well as in horizontal direction. The crosslinking takes
place within companies, but also cross-company and
leads to a merger of the physical and virtual world.
CPS technically enable this (based e. g. on Roy,
2017).
2.2 Cyber-Physical Systems and Their
Elements
As mentioned in chapter 2.1, CPS act as technical
enabler of I4.0. Thus, they form the technical base for
the realization of the visions and ideas within I4.0.
For CPS, heterogeneous definitions do exist as well.
In Broy`s definition different aspects regarding the
functions and components of CPS are included. He
explains that the objective of CPS is the connection
of embedded systems with help of world-wide
networks. This enables a direct connection and back
coupling between the digital and the physical world.
This interaction of embedded systems, based on
software systems and interfaces, creates new system-
functionalities (Broy, 2010).
Beyond the connection between the physical and
digital world as well as the enabling of new system
functionalities, the following characteristics are
essential for a CPS. Access through networks needs
to be transportable and transregional; additionally,
time requirements exist. More characteristics are the
existence of sensors and actuators and the connection
within the systems and between different systems.
CPS should be applicable within difficult physical
environments and for long-time operations as well
(Broy, 2010).
A possible visualization of the structure of CPS is
presented below.
Figure 1: Structure of a CPS (based on Broy, 2010,
Siepmann, 2016).
Life Cycle-Oriented Evaluation of Cyber-Physical Systems
333
The general structure of the CPS shows that
different elements encounter each other. This leads to
technical, but also economic challenges (Broy, 2010).
2.3 Life Cycle-Oriented Analysis of
Cyber-Physical Systems
As shown in chapter 2.2, CPS consist of various
elements, e. g. the physical system and the included
software. While a machine can be used over some
years, software life cycles are much shorter,
sometimes only last some weeks (Drossel, et al,
2018).
To show the life cycles of the elements, life cycle
concepts provide support options. The aim of life
cycle concepts is to identify specific phases of a life
cycle and to visualize the time references of processes
(Herrmann, 2010). The considered objects of life
cycle models vary, e. g. organisations, technologies
or products can be in focus (e. g. Höft, 1992). A lot of
models that describe life cycles do exist.
One possibility to outline a life cycle is the system
life cycle referring to complex systems (Wildemann,
1982). In general terms, a system is a number of
elements which coact with each other to serve a
special purpose (e. g. Schenk, Wirth, 2004). The life
cycle phases of the system life cycle model are the
initiation phase, the planning phase, the realisation
phase, the use phase and the decommissioning phase
(more details about the phases: e. g. in Wildemann,
1982). Normally the phases are not strictly separated,
often they are characterized by an iterative and
parallel sequence (Wildemann, 1982).
As the characteristics of CPS in chapter 2.2 show,
CPS are systems that consist of different elements.
The system life cycle is an option to model, analyse,
evaluate and design the life cycle of a CPS and its
elements. The elements have own life cycles, too.
These heterogeneous life cycles enhance the
complexity of analysing CPS. Hence, a structured
analysis of CPS including the life cycles of the
different elements and their costs and benefits is
necessary.
3 MODEL REQUIREMENTS FOR
A LIFE CYCLE-ORIENTED
EVALUATION OF CYBER-
PHYSICAL SYSTEMS
For the implementation of evaluations in general as
well as for the realisation of life cycle-oriented
evaluations various requirements have to be met. The
requirements consist of diverse criteria which should
be adhered to enable a problem adequate evaluation
and assessment (Meynerts, 2017).
Models in general have to meet formal
requirements, e g. applicability/profitability,
rationality, acceptance, and closeness to reality (e. g.
Meynerts, 2017; Schmidt, 2014). To meet the demand
of applicability/profitability, the level of complexity
needs to be as low as possible. Thus, support in form
of IT-systems can be used to reach an appropriate
level between benefits and costs of model building
and usage (Faßbender-Wynands, 2001). The
rationality is a very important requirement, as the
model needs to have the capability to enable the
decision maker to select the best and rational solution.
To examine the rationality, the guidance of the
normative decision theory is advisable (Schmidt,
2014). Additionally, the model has to be structured as
simple as possible, so that it can be applied without a
lot of background knowledge. Thus, the acceptance
of the users can be enhanced (Meynerts, 2017).
Nevertheless, the contents of the model have to show
closeness to reality to support a well-founded and
rational decision-making (Schmidt, 2015).
Beside the general model requirements the
specialities of a life cycle-oriented evaluation have to
be noted. The key task of a life cycle-oriented
evaluation is to model the life cycle with its phases,
activities and the resulting monetary consequences.
Therefore, life cycle models (as mentioned in chapter
2.3) have to be considered as a basis for identifying
and analysing decision interdependences and
problem formulations (Kemminer, 1999), because
not only the acquisition costs, but also the follow-up
costs as well as the arising benefit should be included
for decision-making. In this context, the considered
objects and their costs have to be broken down into
their components (Meynerts, 2017, Kemminer,
1999). Furthermore, forecast models should be
included to estimate the costs and benefits over the
complete life cycle and to involve uncertainties (e. g.
Dhillon, 1989). Finally, appropriate calculation
methods for a determination of the life cycle-oriented
success have to be chosen (e. g. Riezler, 1996).
Beside the formal and the life cycle-specific
requirements, the characteristics of CPS have to be
considered within the evaluation model. Especially
the different kinds of elements a CPS consists of
should be investigated separately, as mentioned
regarding the life cycle-oriented evaluation, too. This
comes along with heterogeneous life cycles, which
implicate different lifetimes of the elements.
For the analysis of the life cycle of a CPS and its
elements, a structured approach is necessary.
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Therefore, a procedure model is recommended to
enable a transparent and significant evaluation of CPS
(e. g. Faßbender-Wynands, 2001).
4 PROCEDURE MODEL FOR A
LIFE CYCLE-ORIENTED
EVALUATION OF
CYBER-PHYSICAL SYSTEMS
Procedure models are models that describe
procedures of special projects or processes in an
idealising and abstracting way (e. g. Hesse, et al,
1992).
The procedure model should take into account the
requirements mentioned in chapter 3. Therefore, the
theory of decision-making can be used as a basis. The
basic model of decision theory consists of different
elements: objectives and preferential relations,
alternatives like actions, states of environment and
result functions (for more details about decision
theory see Sieben and Schildbach, 1994).
The procedure model suggested in the following
is appropriate for the structuring of decision problems
and the various activities and instruments for the
evaluation of CPS. It is based on preliminary studies
(e. g. Götze, et al, 2010; Weber, 2013) as well as
engineering approaches. The model enables the
evaluation of product- and process-based action
alternatives and consists of several linked levels. To
handle the variety of possible configurations and
influencing variables in a structured way, the
evaluation task can be divided into different parts.
This facilitates the detailed analysis of evaluation
tasks on subordinated levels (e. g. the evaluation of
software components within the CPS). The obtained
values can be merged within the top level to enable
the evaluation of the different alternatives. The
determination of the steps of the procedure model
follows the differentiation of the elements of decision
models according to the basic model of decision
theory. The majority of the steps refers to one of the
elements of this basic model (Götze, et al, 2014).
Figure 2 shows the top level of the procedure
model. Additionally, it is shown, how the evaluation
task can be divided into sub tasks. Within the step S0:
Determination of goal(s) and scope of study the
concern and conditions of the study are determined
closer (Ferry, Flanagan, 1991). Thus, the objective of
the analysis has to be defined. In the light of CPS, it
can be the development and choice of I4.0-solutions
which have the lowest negative monetary impact or
the highest economic success along their life cycle.
Beside the economic ones, also other objectives, e. g.
ecological ones, are possible, too. The superior
Figure 2: Procedure model for evaluation of CPS (based on Weber, T., 2013, Meynerts, L., 2017).
Life Cycle-Oriented Evaluation of Cyber-Physical Systems
335
objective needs further specification regarding the
results to decide why the analysis is necessary. In this
regard, a reason for an analysis can be to identify
relevant solution approaches, to choose a suitable
supplier and, as the most important cause, to find the
most advantageous alternative. Depending on the
goals of the study, the scope has to be defined as well
to enable a well-founded decision-making including
the relevant influences (Meynerts, 2017).
Step S1: Definition of system boundaries
(including alternatives and period of evaluation) is
necessary to determine the relevant system
boundaries. First, the system under study and the
different alternatives have to be distinguished. This
can be a CPS or a combination of different CPS – so
within the production area it can be one or more
machines right up to a whole factory. Furthermore, it
has to be determined, which environmental statuses
(e. g. legal background like existing data privacy acts)
have to be integrated in the evaluation. Additionally,
the evaluation period as well as the life cycle phases
which are considered have to be defined (Götze, et al,
2014). Therefore, a system- and project-analysis
should be conducted.
In step S2: Determination of target figure(s) and
preference relations the relevant technical, economic,
social and/or ecological target figures have to be
defined while analysing the determined requirements
(see S0). An example for an economic target figure is
the net present value; a possible ecological target
figure is the global warming potential. Afterwards,
these figures have to be weighted to define their
priorities. For this purpose, preference relations, e. g.
preferences regarding the type of target, risk or time,
can be used (Meynerts, 2017, Götze, et al, 2014). The
choice of suitable evaluation methods to determine
the target figures is necessary within this step, too. As
I4.0-solutions in form of CPS are normally causing
long-term effects, for economic targets reference can
be made to established methods such as the net
present value method (Götze, Northcott, Schuster,
2015).
Then step S3: Structural analysis and modeling of
action alternatives follows. It means that the objects
(e. g. one CPS, a system of different CPS) and related
decision alternatives have to be selected, analysed
and modeled. Therefore, product- and process-related
modelling approaches like the I-T-O-model can be
used (Götze, Hache, Schmidt, Weber, 2011). If partial
alternatives exist, it can be useful to explore them
detailed within a sub level (Götze, et al, 2014).
The next step is S4: Identification and analysis of
environmental factors/scenarios. The effects
resulting from the different alternatives are affected
by a lot of environmental factors, which arise from
within or from outside of the company.
Environmental factors can influence the payments
and costs directly, like market prices of technical
assets. Additionally, they might also determine the
way of usage of the CPS and its sub systems in an
indirect way. Examples therefore are the customer
demand or legal guidelines. The determination of
environmental factors depends on subjective
assessment (Meynerts, 2017). Additionally, the
interdependencies between the factors should be
analysed, e. g. with causal diagrams (e. g. Coyle,
1996). As a result, environmental scenarios can be
built. In terms of decision theory, this is the step of
developing the states of environment (Götze, et al,
2014). Therefore, forecast models should be used as
well (e. g. von Reibnitz, 1992).
Step S5: Determination of outcomes, target
elements and target values is characterized by the
forecast of costs or payments within the different life
cycle phases or the forecast of benefits (monetary and
non-monetary). Regarding the estimation of costs,
revenues or payments, methods of the development-
and development-concurrent cost calculation are
suggested (Ehrlenspiel, et al., 2007). Additionally,
instruments such as check lists or expert reports for
technical figures are applicable. In case of economic
figures, instruments like traditional cost accounting,
budgeting or activity based costing are recommended.
If ecological target figures are included, instruments
like Life Cycle Assessment can be utilized. The
Social Life Cycle Assessment or other instruments of
the Human Resource Management are suitable, if
social target figures exist. As a result, the values of
target figures are determined. If more than one target
figure exists, the decision value has to be ascertained
with help of methods of multicriteria decision-
making (Götze, et al, 2014). For applying the various
instruments, basic approaches of knowledge
management are recommended to facilitate a valid
database (Köhler, 2012).
Within the last step S6: Interpretation of results
and performing of sensitivity analysis the final
decision-making follows, e. g. in form of choice of
the CPS that will be realized. Therefore, the
determined target figures are compared (Meynerts,
2017). However, the results should be interpreted
carefully because of the high complexity, the limited
availability of data and the uncertainties involved.
Thus, it is advisable to conduct sensitivity analyses to
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336
show the consequences of deviations of the
influencing variables on the target values.
Alternatively, critical values of the influencing
variables can be identified (Götze, et al, 2014; Götze,
et al, 2015).
The different steps within all levels of the process
model are connected among each other in form of
information flows and feedback loops and the results
of one step can be input of another one (Götze, et al,
2014).
A special challenge within the model is posed by
the division of the evaluation tasks and the related
formation of sub levels. It depends on the structure of
the evaluation object and different approaches for the
division are possible (for more information about the
possibilities see Götze, et al, 2014).
5 CONCLUSION
The presented procedure model enables a structured
analysis and evaluation of CPS and supports the
decision-making regarding the use of CPS. The
decomposition into sub levels fosters the
transparency of the evaluation. This is important,
especially because of the typical complexity of the
evaluation object. CPS consist of different elements
and various challenges for their evaluation exist. This
especially refers to the handling of the heterogeneous
life cycles of the elements and the data acquisition.
Thus, a division into partial problems seems to be
unavoidable.
As shown in chapter 4, various instruments can be
used within the different steps and partial problems.
Following studies should focalize on the
concretisation of the model and its steps. Therefore,
existing studies (e. g. Götze, et al, 2014), which focus
on other evaluation objects, can be used as a basis.
Additionally, a refinement of the instruments applied
to the model, like the net present value method, is
necessary. Such refinements, for instance, should
refer to the precise determination of CPS-related
benefits as well as the integration of replacement
decisions.
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