Systems Engineering

Products are becoming more and more complex and interconnected. With the uprising of the “Internet of Things (IoT)” this is becoming even more relevant. Further the trend of software taking over more and more functionalities from what used to be implemented with hardware or mechanics, due its intrinsic advantage of "no" maintenance costs, needs a more holistic view on product development. On the other hand this trend brings also higher complexity which needs to be handled.

Wiki defines Systems Engineering as the interdisciplinary field of engineering that focuses on how to design and manage complex engineering projects over their life cycles. Another definition from Derek Hitchins, Prof. of Systems Engineering and former president of INCOSE defines Systems Engineering as "The art and science of creating optimal solution systems to complex issues and problems". For us both have their value and message.

The traditional areas of Systems Engineering such as aircraft, ships or trains are thus reaching out to many more fields and are underlaid by high dynamics in the market. This is being further pushed by changing market forces and global competition. One of the major challenges is connecting the engineering disciplines with the aim to:

  • improve coordination of processes and data from multiple engineering disciplines
  • streamline development of innovative products and systems
  • prove compliance to regulations and standards
  • achieve quality that grows your business and protects your brand
  • address needs of specific industries
  • find ways to validate earlier on in the product development lifecycle (shift left)
  • find ways for mutidisciplinary, heterogenous co-simulation
  • helping to reach the Digital Twin
  • helping organisation developing complex systems to prosper in the digital age 

At EVOCEAN, we have established developed Serenity to address these challenges. Serenity ia a model driven process framework , focusing on improving systems development. Serenity includes a common language to communicate more effectively and coherently to speed up product and systems development and innovation enabling prosperous organizations.

Modeling – a fundamental part of engineering

Models have become essential for understanding the structure and behavior of complex systems. Modeling helps in simulation and early validation and is a fundamental part of engineering. It is an effective way to manage the complexity of system and software development, enabling communication, design and assessment of requirements, architectures, systems and software. That's why the industry is moving towards Model Based Systems Engineering  (MBSE). However, there is more to MBSE: executable models leading to Model Driven Systems Engineering  (MDSE).

MDSE leverages graphical models and pre-built application components so that users not only can visually construct but also virtually interact with the system and test their complex systems through executable graphical models. As such, the models not only contribute to a better understanding of structure and behavior, but also help understand the system more clearly earlier on in the development phase. As a result, models increase the ability to improve and validate ideas and concepts as early as possible in the process when it costs less to adapt.

An effective approach to drive the challenging tasks of improving Systems Engineering in a structured way is the Systems Development Taxonomy. This classification has been established based on many different domains, projects and customers. It determines seven practice stages and also helps in laying out a path for the incremental adoption of MDSE within an organization.

Systems Development Taxonomy

An effective approach to drive the challenging tasks of improving Systems Engineering in a structured way is the Systems Development Taxonomy (refer to Figure hereafter). This classification has been established based on many different domains, projects and customers. It determines seven practice stages and also helps in laying out a path for the incremental adoption of Model Driven Systems Engineeing (MDSE) within an organization.

The journey starts at Stage 1 with the simple idea and may finally lead to Stage 7 on the other end of the spectrum with the tested and proven model. The importance and value of each of these consecutive 7 stages is given in order to continuously improve the Systems Engineering capabilities. 

The System Development Taxonomy is field agnostic: It can be applied on each system development phase and is applicable to every domain – being it mechanical, software, analogue and digital electronic, optics, etc. Let us briefly go through the stages:

Serenity - a cutting edge Systems Engineering Approach

At EVOCEAN, we have established a model driven process framework called Serenity, focusing on improving systems development. Serenity includes a common language to communicate more effectively and coherently to speed up product and systems development and innovation enabling prosperous organizations.

Serenity is not just a technical approach to improve the working processes in Systems Engineering. It is a proven and innovative method which positively affects the entire organization and paths the way to benefit from digital twins. By enhancing multi-disciplinary interactions and collaboration, it contributes to cope with the constant changes within the own ecosystem as well as in the business environment and supports the transformation towards a lean and more collaborative organization.

Learn more about Serenity here.

Our services in the field of Systems Engineering

  • Continuous Improvement in Systems & Product Development
  • Introducing Lean Practices in Systems & Product Development
  • Increasing agility in Requirements Engineering in Systems & Product Development through a collaborative approach
  • Introducing Modelling with SysML (System Modelling Language) and UML (Unified Modelling Language)
  • Improving and optimising quality activities through collaborative planning, automated testing and defect management
  • Achieving compliance combining Model Based Design, Model Based Testing and formal methods
  • Ease collaboration by using models, social platforms and visualisation
  • Introducing analysis tools specifically designed for visualizing, analysing and organising engineering data
  • Introducing executable modelling for faster feedback, earlier validation and increased development agility.

Always keeping in mind the aim of achieving faster feedback for reducing time to decision, thus focusing the resources on activities with highest value and introducing tools which help to achieve goals faster, better and with less cost bringing sustainable successful products and systems to market.

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