Cyber-physical systems involve entirely new capabilities for people and machines. In cyber-physical systems, physical and software components are deeply intertwined, able to operate on different spatial and temporal scales, exhibit multiple and distinct behavioral modalities, and interact with each other in ways that change with context.

It is necessary to make a paradigm shift into digital transformation to support current and future trends.  The following business enablers need to align with current and future trends:

1.   Digital Thread: This describes the framework which connects data flows and produces a holistic view of an asset’s data across its product lifecycle from development, manufacturing, in-service operation, retirement. Typically, the digital thread connects digital twins, digital models of physical assets, or groups of assets.

2.   Digital Twin: This is the virtual representation of properties and behavior and is a virtual replica of systems or processes used to anticipate and optimize performance along with maintaining digital synchronization with systems or processes.

3.   Model Based Systems Engineering (MBSE): This is a systems engineering approach that focuses on creating and exploiting domain models as the primary means of information exchange between engineers, rather than on document-based information exchange.

MBSE is the first building block of the digital value chain.

The Cyber-Physical Systems Experience enables all the Dassault Systèmes’ industry solution experiences, which are based on the 3DEXPERIENCE platform. It generalizing systems engineering for developing the “Internet of Experiences” – the smart and autonomous experiences which address System of Systems Engineering, System Engineering and Discipline Engineering to digitally connect products, nature and life in the physical world.

The key values are:

• Modelling & Simulation (Mod-Sim): The ability to not only design and model but to simultaneously simulate the model for validation, all in a methodological framework.
• Federation: The ability to:
  • Federate system engineering data, irrespective of the authoring tool, with end-to-end traceability for compliance assessment and impact analysis in the case of an engineering change.
  • Federate discipline engineering within a system architecture to master interfaces and predict system behavior in order to accurately specify  the solution under design.
  • Federate the system engineering experiences from local to global, irrespective of the authoring tool, in order to experience a digital replica of the cyber-physical system.
• Governance: In a regulatory context, the capability to maintain in configuration, an authoritative single source of truth for compliance assessment with full control of the system engineering activities of the project.
• Openness: Leadership in standards definition to support state-of-the-art modelling and simulation, and the support of interoperability tools  for semantic integrity and exchanges within the value chain.

The Dassault Systèmes landscape for Systems Engineering landscape includes the following layers:

• System of Systems / Enterprise layer: Understanding the missions, scenarios, usage as a specification for the systems & organisations.
• System layer: Defining the functional behaviour, scenarios as a specification for the solution design system.
• Solution layer: Designing the solution from global to detail, as a product with components (hardware, software, parts) considering the functions as both control and plant behaviours.
• Implementation layer: Developing the discipline-specific components as specified in the solution layer.

The 3DS Portfolio for Cyber-Physical systems, also enables program/project development (variants, change, configuration, scheduling, tasks, workflows) and Systems Engineering activities which are important ingredients for mastering product quality and performance and for controlling program/project cost and delays.

• 3DEXPERIENCE Roles for Systems Engineering
• CATIA Magic Roles
• Stimulus Requirements Simulation Engineer Role
• Reqtify
• Control Build
• Autosar Builder
• Dymola

Systems Engineering is a transdisciplinary field of engineering and engineering management that focuses on how to design, integrate, and manage complex systems across their lifecycles.

Systems Engineering is a systematic approach that provides a global view and helps to:

• Manage complexity, master interfaces and reduce risks.
• Better understand stakeholder needs to conceptualize real world changing issues.
• Deliver quality and robust products that meet the stakeholder needs with optimized efficiency.
• Accelerate collaboration within the value chain and avoid unnecessary rework loops.
• Manage and control project costs and time scales by integrating system engineering activities with project management.

Model-Based Systems Engineering (MBSE), as a cross-discipline collaborative activity, is a strong business enabler to address industry issues and to align organizations with current and future trends.

Model-Based Systems Engineering is the formalized application of modelling to support system requirements, design, analysis, verification and validation activities beginning in the conceptual design phase and continuing throughout development and later lifecycle phases.

MBSE is simply a set of visual representations based on a consistent and complete system model, which reflect multiple viewpoints of the system. These representations can be either static or dynamic (simulation), descriptive or predictive. It improves understanding, early in the development phase, system behaviour as a functional digital twin of the product.

In the system development process many challenges and issues emerge which need to be addressed:

• Lack of control on the engineering of the project: No single source of truth of Engineering Project data to make relevant decisions.
• Inefficient requirements engineering: An uncontrolled number of ambiguous and redundant requirements.
• Reactive approach rather than proactive: Lack of understanding of system behavior before prototyping.
• Inconsistencies between disciplines: Disciplines operate in silos, resulting in lack of control over dynamic behavior of interfaces.
• Discontinuities throughout the supply chain: Exchange with supply chain is document based and therefore  cumbersome.
• Costly compliancy process: With no single source of truth of engineering data, compliancy reports are developed at the end of the development phase with high risk of incompleteness and errors.