Organizations and people need to simplify to manage complexity and derive "big or complex things" into smaller and manageable systems – where a system is a set of interacting elements (or subsystems) with an internal structure that connects them into a unified whole. To do this, optimizing or implementing a new system requires a clear articulation of its boundaries and the internal structure (logical, technical, physical, etc.) that connects its elements.
Due to increasing complexity and the need for speed of development, systems engineers are beginning to use models to simulate structural stability, behavior, cost, and other technical aspects, or to replace actual physical verification.
Systems engineering helps combine multiple technical and business disciplines while focusing on how to optimally design and manage complex systems throughout their respective lifecycles.Historically, product lifecycle management (PLM) models have been developed in the classical way of a feature-driven approach based on knowledge, with mechanical product structures integrated with electrical, control electronics, hardware, and software units. Traditional mechanical, electrical, and materials engineering concepts, methods, and processes should be revised to prepare for the revolution in PLM modeling of multidisciplinary products.
Modern PLM platforms are expected to embed modeling approaches with a systems engineering approach and combine the mechatronic structure with associated materials engineering and software management as the core of the engineering-manufacturing cross-loop. From a broad perspective, this is also known as model-based systems engineering (MBSE), which supports feedback loops across systems and disciplines through the application of formal modeling.
The MBSE workflow applies to the entire "V-model", starting with the product concept design phase and continuing through its development and later life cycle phases.The use of RFLP structured product models provides a solution for multidisciplinary modeling at the conceptual product design level, which has the potential to bring the following benefits:
From mechatronics to software development (horizontal integration: functional adaptation) to deliver innovation faster across the entire value chain and across disciplines.
Improve concept modeling, downstream validation, and data reuse (systems, hardware, and software assets).
Helps enhance collaboration and achieve better results, including a strong feedback loop between engineering and manufacturing (vertical integration: upstream and downstream).
Validate complex behaviors early in the design lifecycle.
Combine all engineering and related information (enterprise-wide interlocking and data alignment) to deliver faster, better business analytics.
Better manage overall traceability and knowledge.
It's important to note that each discipline may follow its own life cycle and V model. The key success factor is to manage consistency through requirements cascade and dependency management, rather than trying to align all requirements with a single model, but with an ecosystem of interdependencies – for example, which can be accounted for and managed according to the IT4IT architecture framework.
MBSE is one of the key applications of the systems engineering approach, which is the connection between requirements and functional, logical, physical structures (RFLPs). Developing large, complex products requires an adequate systems engineering process based on hierarchical RFLP to provide a closed-loop system design before delivering requirements to lower-level systems.
Requirements and test cases, which define the contextual requirements for use cases, functional and non-functional requirements.
Functional architecture, which describes what the system must do in terms of capabilities.
A logical architecture that defines how the system is implemented.
Physical, including components of the software, implementation parameters, virtual definitions of real-world products, including a 3D representation of the concept of the target system "visualized" at an early stage.
PLM is the de facto platform that provides the processes and tools to manage the product development lifecycle in a common environment; It includes the logical interdependencies that govern them in order to effectively manage the work products of mechanical, electrical, and software engineering. However, overall hardware and software integration has traditionally remained informal and rarely well documented.
Current RFLP practices seem to be tracking multiple structures (one for R, one for F, one for L, and multiple for P), revising control over these structures, and interconnecting structures with traceability relationships.End-to-end change and configuration management integration and automation become key enablers for RFLP practices to be optimized and effective in every RFLP element and every discipline.
Horizontal integration is becoming increasingly important, especially in providing the relevant data backbone for manufacturing execution.
With smart manufacturing, the Industrial Internet of Things (IIoT) and Industry 4With the rise of 0, model-based development methodologies are becoming more and more powerful, allowing the definition of relevant "digital twins" for product development and plant operations optimization. In the new era of the smart factory, cyber-physical systems (CPS) combined with MBSE have the potential to monitor processes, create virtual reality of actual operations, act independently, and use IIoT to communicate and collaborate with other systems and humans in real time. Manufacturers must demonstrate that products are carefully developed and manufactured using state-of-the-art methods to successfully guarantee safety and regulatory compliance.
Going forward, MBSE and PLM are expected to converge to true model-based engineering (MBE) and enable an effective transition from document-based to model-based.The ecosystem is expected to include a set of interdisciplinary engineering approaches, using models as an integral part of the technology baseline, including requirements, analysis, design, implementation, and validation of capabilities, systems, and/or products throughout the acquisition lifecycle.
MBE is a challenging problem, but one that can be solved by combining standards (industry level and/or company level) and linked lifecycle data (requirements and change management, combined with automation, performance monitoring, and continuous quality improvement). Standards such as Lifecycle Collaboration Open Services (OSLC) or Product Lifecycle Support (PLCS) help integrate standalone software and product lifecycle tools to integrate their data and workflows to support end-to-end lifecycle processes.