Innovate today, realize tomorrow
Antemia is a pioneering company in technology, consulting, and training dedicated to envisioning a future where complex engineering challenges are met with efficiency, precision, and innovation.
Our mission is to drive transformative change across industries by leveraging the power of systems engineering and model-based systems engineering to deliver practical, tangible solutions that address real-world needs. Going beyond theoretical frameworks to focus on practical applications that provide measurable value is at the core of our company. We strive to be pioneers in the field, pushing the boundaries of what is possible and setting new standards of excellence in engineering practice.
Our collaboration with Graz University of Technology ensures that cutting-edge academic research is seamlessly integrated into real-world applications. With this Antemia positions itself at the forefront of innovation, driving excellence in the engineering and technology sectors.
Founder's scientific references
Abstract: For the last century, the automotive industry has been dominated by internal combustion engines. Their flexibility of application, driving range, performance and sporty characteristics has resulted in several generations of this technology and has formed generations of engineers. But that is not the end of the story. Stricter legislation and increased environmental awareness have resulted in the development of new powertrain technologies in addition and parallel to the highly optimized internal combustion engine. Hybrid powertrains systems, pure battery electric systems and fuel cell systems, in conjunction with a diverse range of applications, have increased the spectrum of powertrain technologies. Furthermore, automated driving together with intelligent and highly connected systems are changing the way to get from A to B. Not only is the interaction of all these new technologies challenging, but also several different disciplines have to collaborate intensively in order for new powertrain systems to be successfully developed. These new technologies and the resulting challenges lead to an increase in system complexity. Approaches such as systems engineering are necessary to manage this complexity.
To show how systems engineering manages the increasing complexity of modern powertrain systems, by providing processes, methods, organizational aspects and tools, this book has been structured into five parts.
Starting with Challenges for Powertrain Development, which describes automotive-related challenges at different levels of the system hierarchy and from different point of views.
The book then continues with the core part, Systems Engineering, in which all the basics of systems engineering, model-based systems engineering, and their related processes, methods, tools, and organizational matters are described. A special focus is placed on important standards and the human factor.
The third part, Automotive Powertrain Systems Engineering Approach, puts the fundamentals of systems engineering into practice by adding the automotive context. This part focuses on system development and also considers the interactions to hardware and software development. Several approaches and methods are presented based on systems engineering philosophy.
Part four, Powertrain Development Case Studies, adds the practical point of view by providing a range of case studies on powertrain system level and on powertrain element level and discusses the development of hybrid powertrain, internal combustion engines, e-drives, transmissions, batteries and fuel cell systems. Two case studies on a vehicle level are also presented.
The final part, Outlook, considers the development of systems engineering itself with particular focus on information communication technologies.
Even though this book covers systems engineering from an automotive perspective, many of the challenges, fundamental principles, conclusions and outlooks can be applied to other domains too. Therefore, this book is not only relevant for automotive engineers and students, but also for specialists in scientific and industrial positions in other domains and anyone who has to cope with the challenge of successfully developing complex systems with a large number of collaborating disciplines.
https://link.springer.com/referencework/10.1007/978-3-319-99629-5
Abstract: The term ‘system model’ is used in many different domains, fields of application and in various forms with different meanings. One of model-based systems engineering’s targets is the generation of a system model, which is used to describe complex system aspects across multiple views of disciplines and technical domains. Often a system model generated with systems modeling language is used as a central placed model in development. Besides, there are practical approaches, where models generated with other languages are also sometimes called system models. The scope of this paper is a generic definition of the term ‘system model’ and its interactions with other types of models in a model-based development ecosystem. Based on the analysis of the actual situation, a concept for the definition of system models is presented, which enables the use of multiple system models and which helps to understand the interactions with other types of models. For better comprehension of a system model’s role in development, a three dimensional cube for visualization of system models and specific models is presented. Coupled with the definition of the term, interactions to other approaches like product lifecycle managementand the vision of a single source of truth for development are investigated and discussed.
https://link.springer.com/article/10.1007/s42452-019-1069-0
Abstract: In the field of model-based development, and especially model-based systems engineering, the efficient and effective use of system models and specific models is of great interest. However, models strongly depend on the method they are linked to. Methods require models as input and associated models that are part of the method itself. Subsequent, methods are applied to adapt, enhance or generate output models. If a model is analyzed regarding its fidelity, level of detail, or maturity, only a combined consideration of methods and models in the development approach leads to a valid assessment. Therefore, the principle link of methods, system models, and specific models is defined and a concept for the application in product development is presented. It is stated, that a combined view on methods and models leads to improved accuracy of information interpretation and therefore optimizes efficiency and effectiveness during the product development.
https://link.springer.com/article/10.1007/s42452-024-05651-5
Abstract: This paper describes the concept of a method that uses an existing system model to select the most suitable component or specific model for inclusion. The term model is understood to encompass models that are used during the development of systems that: have a certain degree of formalism, are digitizable, connectable and processable. The method describes how specific models that are required can be identified and how they could be connected. The approach is explained using a well-understood example taken from the development of automotive powertrains. After stating current challenges and problems in the development of complex systems in the automotive domain, a system cube is used as a structuring principle for models that describe certain system aspects such as structure and behavior. This concept acts as a starting point for the selection of the most suitable specific models allocated to system models based on the functional description of the system. Finally, the contribution of this research to the real-ization of a digital thread is discussed and future research topics are outlined.
https://incose.onlinelibrary.wiley.com/doi/abs/10.1002/j.2334-5837.2021.00885.x
Abstract: Current requirements for the reduction of CO2 emissions, as well as for the improvement of durability and reliability of sociotechnical systems such as passenger cars, lead to an increase in development effort in order to increase efficiency and system lifetime. Tribological systems play an essential role in the development of sociotechnical systems, but have proved to be particularly complex. The development of tribological systems, as part of the overall system under development, is an interdisciplinary effort. Involvement of solid mechanics, fluid mechanics, rheology, and many more scientific disciplines is essential to cope with the high number of nonlinear relationships, which often cause unpredictable system behavior. This paper contributes to the scientific field of tribology by introducing concepts of model‐based systems engineering for the specific case of elastohydrodynamic lubrication states. The elastohydrodynamic lubrication state of tribological system has been chosen as example to show how system models can be used to better describe the behavior of a system by connecting several specific models. In order to gain an overview of the models used in tribological system development, a system cube was used to structure the models. The system cube enabled gaps and overlapping model zones to be identified. Finally, the role of system models in development and the benefit of using system models to solve problems that cannot be solved by a single technical discipline but only in an interdisciplinary effort are discussed. An approach to connect models and methods to describe a system in an elastohydrodynamic lubrication state is presented.
https://incose.onlinelibrary.wiley.com/doi/10.1002/sys.21562
Abstract: Der Erstellung eines Digital Masters im Zuge einer Produktentwicklung liegen viele Entscheidungen zugrunde. In Hinblick auf die Erstellung eines Digital Twins, welcher als Abbild einer realen Produktinstanz angesehen wird, und in weiterer Folge auf dessen Anwendung spielen diese Entscheidungen eine essentielle Rolle. Der daraus resultierende Einfluss eines Entwicklers auf den Digital Master und Digital Twin wird in diesem Beitrag aufgegriffen und am Beispiel einer Fahrzeugbatterie erläutert.
https://www.degruyter.com/document/doi/10.3139/104.112302/html
Abstract: Digitale Zwillinge verbinden und erweitern die bisherigen digitalen Modelle in der Entwicklung mit den neuartigen Datenströmen des operativen Betriebs von Produkten, Maschinen und Dienstleistungen. Digitale Zwillinge werden die Produktentstehung nachhaltig verändern und neue Geschäfts- und Wertschöpfungsmodelle ermöglichen.
https://www.degruyter.com/document/doi/10.3139/104.112311/html
Abstract: In the development of complex mechatronic systems, interdisciplinary cooperation requires an exchange between stakeholders in order to ensure fulfillment of requirements and related functions. The cooperation of the stakeholders from different disciplines must be well coordinated to address systems changes. The system model as an essential aspect of model-based systems engineering, has to be linked to specific models of involved disciplines (mechanical, electrical/electronical and software) to enable a basis for automatic identification e.g., of affected subsystems and functions. This contribution discusses the potential of model linking from the perspective of change scenarios by considering published approaches to link system models and computer-aided design (CAD). A methodical approach on how descriptive system models can be used as base for computer-aided design is presented. This approach is analyzed by reviewing a use case for a design change scenario of an automotive eAxle.
https://incose.onlinelibrary.wiley.com/doi/abs/10.1002/iis2.13012
Abstract: This paper describes concepts to support the application of descriptive functions using artificial intelligence technologies. Descriptive functions are typically used in the system design phase to describe and specify the system behavior. In a model‐based systems engineering approach the system functions, their dependencies, and the allocation to the technical solution are typically documented in system models. Descriptive functions have a fuzziness that is beneficial in the solution finding process but also challenging in terms of development efficiency. To support development teams in formulation and working with descriptive functions in system design, and verification and validation phase several concepts with the use of artificial intelligence technologies are discussed.
https://incose.onlinelibrary.wiley.com/doi/10.1002/iis2.13109
Abstract: Modern engineering uses models for virtual verification of systems. Such models are usually combined in workflows, where the results of models are linked to verify system requirements. Model-Based Systems Engineering (MBSE) has evolved as an approach to ease the usage of models and workflows. One goal in MBSE is to reuse models and workflows from libraries. However, the step of identifying and classifying both models and workflows for such a library is not yet systematized. We propose a method on how to identify models and workflows for an MBSE model library. Possible purposes of models are identified and afterwards models satisfying that purpose are retrieved. The identified models are systematically combined to workflows. Thereby a systematic approach to create a model library is given.
Abstract: Decision-making is becoming more and more challenging due to the rise in complexity ofmodern technical products. A lot of industries are currently at a crossroads, and a wrong strategicor technical decision may have disastrous consequences for the future of the company. Within thispaper, the SMH approach, that supports decision making processes to put emphasis on sustainablesolutions regarding strategic and technical aspects, is introduced. SMH is an acronym that standsfor a decision making approach that includes systems thinking (S), model-based systems engineering (M) and the human factor (H). This approach deals with the challenge to consider overall boundary conditions and interactions of the system, the decision which models need to be built in orderto have the best data support possible, and the identification what influence the human factor playsin analyzing the data and the consequent decision making based on it. The importance of the humanfactor is often neglected in technical processes, which may lead to costly mistakes. This theoreticalapproach is applied to the use case of a chief executive officer (CEO) who has to decide on allocationof research and development (R&D) resources to future powertrain technologies.
AccCellBaT (Accelerated Cell and Battery Testing) is a European funded 3-year project aiming to advance virtualization, front-loading, and continuous validation and verification (V&V) in future technology battery development to optimise battery design, cost, and time-to-market.
A process-and-method manual applicable for future battery development will be built. The development tool will provide an integrated development environment for management, planning and execution of battery V&V.
To ensure validity and applicability of the AccCellBaT methodology across industries, the methodology is validated by two original equipment manufacturers (representing via automotive and stationary application a crucial share of the battery system market).
Presentation (@Siemens RealizeLIVE) showing the capabilities of extensive work with the help of MBSE.