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        <article-title>A new approach to master complexity in model driven Systems Engineering</article-title>
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      <abstract>
        <p>Companies in the Engineer-To-Order (ETO) business are facing various challenges [1][2]. The competitive pressure is rising, new competitors are emerging, and customers call for higher flexibility and global presence of ETO companies. Engineering [3]is a core activity of the ETO business, defining 50-60% [4]of the total life-cycle cost of the produced solutions, yet causing just 5-15% [5]of the internal delivery costs, engineering is the starting point to tackle complexity.</p>
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      <p>Just like any other systems engineering method, core
modeling must resolve the dilemma of supplying an adequately
complete description on the one hand (all necessary
requirements that are needed for the following steps and
decisions) but, on the other hand, remaining transparent and
communicable and also feasible in terms of scope and effort
when creating it. The needed focus is achieved by the
following characteristics:
</p>
      <p>The core model only contains content from the problem
space;
The core model only contains content at a commonly
agreed abstraction level, i.e. all descriptions are at the
same level of detail;
The core model only contains content that is relevant to
economic success or a necessary prerequisite for
implementation or boosts internal benefit (e.g. reducing
production efforts).</p>
      <p>By combining the two viewpoints (i.e. tasks, interests) a
‘core model matrix’ is created as a consistent view on the
system. At the intersection (matrix cell) of an interest and a
task, the specific requirements/impacts are described.</p>
      <p>As a result, potential contradictions between requirements
can be systematically detected, analyzed and resolved still in
the problem space. The matrix representation also allows for
precisely recognizing for which of the tasks which interest has
to be considered in which way (i.e. interest only influences
specific tasks). The complexity of the system architecture to be
defined later can therefore be substantially reduced.
Furthermore tasks and interest can be prioritized in order to
ensure focus and enable trade-off analysis. The overall model
can also be communicated in a structured way and a common
understanding across all participating stakeholders can be
achieved.</p>
      <p>In the next step, the transition from the problem space to
the solution space must be accomplished. This can happen in
parallel and can be continuously reviewed for target
achievement with the defined ‘core’. The core model approach
provides also guidance for the architecture model as a suitable
component structure can be obtained by weighing up tasks and
interests and by balancing out conflicts from the core model to
the best possible extent. Complex systems can be modeled by
applying this model in a recursive approach on identified
subsystem or component if necessary.</p>
      <p>This approach has been piloted in different industrial
domains and examples from these projects will be shown to
illustrate the implementation of this new method.</p>
      <p>Core modeling has proved to be helpful in practice as a
highly efficient and target oriented method. This approach
showed in the pilot projects, that an improved and common
understanding of the overall system, fewer inconsistencies in
communication thanks to a common basis, faster and more
comprehensible decision making and continuous review of
target achievement could be realized. The possibility to model
the system on different, but well defined, levels of abstraction
helps to manage and even to reduce the complexity. As the
core model is situated in the problem space, the creativity of
finding new solutions is strongly supported.</p>
      <p>Above and beyond system development, core modeling
also offers portfolio strategy advantages. Products can be
aligned to the tasks to be performed, several products in one
domain are delimited from one another in relation to their
purpose and in a clearly communicable manner, and
unnecessary overlaps and product complexity (i.e. variants) are
reduced and last but not least customer satisfaction can be
improved as the products are addressing the ‘real’ user purpose
and support them in fulfilling their tasks.</p>
      <p>The linking between the core model and other relevant
models (e.g. requirements model, test model), as well as the
tool support for the core model and the implementation in
existing tool landscape will be a topic for future research.</p>
      <p>AUTHOR BIOGRAPHY</p>
      <p>Jan Vollmar is Principal Engineer at Corporate
Technology of Siemens AG. He is responsible for improving
and developing internal engineering organizations. He is
managing consulting projects focusing on engineering strategy
development, Systems Engineering implementation and global
engineering collaboration. In international research project his
focus is on improving and developing new methods for
Systems Engineering. Before joining Corporate Technology
Jan Vollmar has been senior project manager within Siemens
plant building business in the automobile industry. He has
studied mechanical engineering at the Karlsruhe Institute of
Technology.</p>
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