Towards a method to quantitatively measure toolchain interoperability in the engineering lifecycle: A case study of digital hardware design

The engineering lifecycle of cyber-physical systems is becoming more challenging than ever. Multiple engineering disciplines must be orchestrated to produce both a virtual and physical version of the system. Each engineering discipline makes use of their own methods and tools generating different types of work products that must be consistently linked together and reused throughout the lifecycle. Requirements, logical/descriptive and physical/analytical models, 3D designs, test case descriptions, product lines, ontologies, evidence argumentations, and many other work products are continuously being produced and integrated to implement the technical engineering and technical management processes established in standards such as the ISO/IEC/IEEE 15288:2015 "Systems and software engineering-System life cycle processes". Toolchains are then created as a set of collaborative tools to provide an executable version of the required technical processes. In this engineering environment, there is a need for technical interoperability enabling tools to easily exchange data and invoke operations among them under different protocols, formats, and schemas. However, this automation of tasks and lifecycle processes does not come free of charge. Although enterprise integration patterns, shared and standardized data schemas and business process management tools are being used to implement toolchains, the reality shows that in many cases, the integration of tools within a toolchain is implemented through point-to-point connectors or applying some architectural style such as a communication bus to ease data exchange and to invoke operations. In this context, the ability to measure the current and expected degree of interoperability becomes relevant: 1) to understand the implications of defining a toolchain (need of different protocols, formats, schemas and tool interconnections) and 2) to measure the effort to implement the desired toolchain. To improve the management of the engineering lifecycle, a method is defined: 1) to measure the degree of interoperability within a technical engineering process implemented with a toolchain and 2) to estimate the effort to transition from an existing toolchain to another. A case study in the field of digital hardware design comprising 6 different technical engineering processes and 7 domain engineering tools is conducted to demonstrate and validate the proposed method.The work leading to these results has received funding from the H2020-ECSEL Joint Undertaking (JU) under grant agreement No 826452-“Arrowhead Tools for Engineering of Digitalisation Solutions” and from specific national programs and/or funding authorities. Funding for APC: Universidad Carlos III de Madrid (Read & Publish Agreement CRUE-CSIC 2023)

Model-Based Systems Engineering Approach to Distributed and Hybrid Simulation Systems

INCOSE defines Model-Based Systems Engineering (MBSE) as the formalized application of modeling to support system requirements, design, analysis, verification, and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases. One very important development is the utilization of MBSE to develop distributed and hybrid (discrete-continuous) simulation modeling systems. MBSE can help to describe the systems to be modeled and help make the right decisions and partitions to tame complexity. The ability to embrace conceptual modeling and interoperability techniques during systems specification and design presents a great advantage in distributed and hybrid simulation systems development efforts. Our research is aimed at the definition of a methodological framework that uses MBSE languages, methods and tools for the development of these simulation systems. A model-based composition approach is defined at the initial steps to identify distributed systems interoperability requirements and hybrid simulation systems characteristics. Guidelines are developed to adopt simulation interoperability standards and conceptual modeling techniques using MBSE methods and tools. Domain specific system complexity and behavior can be captured with model-based approaches during the system architecture and functional design requirements definition. MBSE can allow simulation engineers to formally model different aspects of a problem ranging from architectures to corresponding behavioral analysis, to functional decompositions and user requirements (Jobe, 2008)

Integrating models and simulations of continuous dynamic system behavior into SysML

Contemporary systems engineering problems are becoming increasingly complex as they are handled by geographically distributed design teams, constrained by the objectives of multiple stakeholders, and inundated by large quantities of design information. According to the principles of model-based systems engineering (MBSE), engineers can effectively manage increasing complexity by replacing document-centric design methods with computerized, model-based approaches. In this thesis, modeling constructs from SysML and Modelica are integrated to improve support for MBSE. The Object Management Group has recently developed the Systems Modeling Language (OMG SysML ) to provide a comprehensive set constructs for modeling many common aspects of systems engineering problems (e.g. system requirements, structures, functions). Complementing these SysML constructs, the Modelica language has emerged as a standard for modeling the continuous dynamics (CD) of systems in terms of hybrid discrete- event and differential algebraic equation systems. The integration of SysML and Modelica is explored from three different perspectives: the definition of CD models in SysML; the use of graph transformations to automate the transformation of SysML CD models into Modelica models; and the integration of CD models and other SysML models (e.g. structural, requirements) through the depiction of simulation experiments and engineering analyses. Throughout the thesis, example models of a car suspension and a hydraulically-powered excavator are used for demonstration. The core result of this work is the provision of modeling abilities that do not exist independently in SysML or Modelica. These abilities allow systems engineers to prescribe necessary system analyses and relate them to stakeholder concerns and other system aspects. Moreover, this work provides a basis for model integration which can be generalized and re-specialized for integrating other modeling formalisms into SysML.M.S.Committee Chair: Chris Paredis; Committee Member: Dirk Schaefer; Committee Member: Russell Pea

Model Based System Engineering for the development of System on Chip

Abstract. Model Based System Engineering (MBSE) has been utilized in auto manufacturing industries, airplane manufacturing and maintenance, and factory process automation industries. These are some of the complex fields. As SoC design is a complex process and requires years of work, MBSE can reduce time, complexity, reuse, and maintenance costs. It seems a fruitful idea/decision to take MBSE into use in SoC design depending on the previously mentioned elements. System on Chip (SoC) is obtaining the interest of many big companies. Therefore, MBSE will represent a huge competitive advantage once it is taken fully into the systems engineering roles of SoC. The existence of geographically dispersed teams, complexity of systems, interdisciplinarity, personalized system description, and their integration can be enabled by MBSE. As an emerging paradigm for the systems of the 21st century, MBSE paved the way for creating successful systems (for the companies) that are end to end connected. This research focuses on making use of MBSE in SoC. The thesis will show how SoC processes can be implemented in one complete model with top to bottom approach. Firstly, the traditional systems engineering approach has been explained with its tools and examples. Secondly, the need for taking up MBSE by the systems engineers is expressed. This contains the applications, use in modern systems, and benefits of MBSE. Moreover, MBSE methodology tools, languages, and their use in SoC is illustrated with examples. As SoC development is a huge and complex process; therefore, a small component of the chip has been taken in consideration for the purpose of understanding and making of the thesis. MBSE is a model-based approach hence a language needs to be present to produce these models and that language is SysML and OPD/OPL. SysML language and MagicDraw tool is used for expressing the architecture of the system. MagicDraw supports several external evaluators for evaluation of expressions and MATLAB is one of them. With MagicDraw we can do simulations, input parameters, and analyze data by processing on it using algorithms developed in MATLAB

A framework for Model-Driven Engineering of resilient software-controlled systems

AbstractEmergent paradigms of Industry 4.0 and Industrial Internet of Things expect cyber-physical systems to reliably provide services overcoming disruptions in operative conditions and adapting to changes in architectural and functional requirements. In this paper, we describe a hardware/software framework supporting operation and maintenance of software-controlled systems enhancing resilience by promoting a Model-Driven Engineering (MDE) process to automatically derive structural configurations and failure models from reliability artifacts. Specifically, a reflective architecture developed around digital twins enables representation and control of system Configuration Items properly derived from SysML Block Definition Diagrams, providing support for variation. Besides, a plurality of distributed analytic agents for qualitative evaluation over executable failure models empowers the system with runtime self-assessment and dynamic adaptation capabilities. We describe the framework architecture outlining roles and responsibilities in a System of Systems perspective, providing salient design traits about digital twins and data analytic agents for failure propagation modeling and analysis. We discuss a prototype implementation following the MDE approach, highlighting self-recovery and self-adaptation properties on a real cyber-physical system for vehicle access control to Limited Traffic Zones

Improving System Design Through the Integration of Human Systems and Systems Engineering Models

The human is a critical aspect of many systems, but frequently there is a failure to properly account for human capabilities and involvement during system design. This inattention results in systems with higher lifecycle costs, decreased user compatibility, and the potential to produce disastrous consequences. This research presents an approach to integrating the human into system models by using two methods: static and dynamic modeling. The static method uses a user-centered design framework to create system- and human-centered models that deconstruct the system and user into their respective components. These models are integrated to create system models that include relevant information about the human and highlight potentially conflicting tasks. The dynamic method uses a human performance modeling tool to create a discrete event simulation (DES) of the system. This DES model is used to perform an analysis between system trades, by which constraints and assumptions placed on the human are verified. Data gained from the analysis are integrated back into system models in order to reflect true system performance. By applying these two integration methods early in the system’s lifecycle, system models can more effectively account for the human as a critical component of the system, thus improving system design