OMG SysML™ is a modeling language for specifying, analyzing, designing, and verifying complex systems. It is a general‐purpose graphical modeling language with computer‐sensible semantics. This Part 1 paper and its Part 2 companion show how SysML supports simulation‐based design (SBD) via tutorial‐like examples. Our target audience is end users wanting to learn about SysML parametrics in general and its applications to engineering design and analysis in particular. We include background on the development of SysML parametrics that may also be useful for other stakeholders (e.g, vendors and researchers). In Part 1 we walk through models of simple objects that progressively introduce SysML parametrics concepts. To enhance understanding by comparison and contrast, we present corresponding models based on composable objects (COBs). The COB knowledge representation has provided a conceptual foundation for SysML parametrics, including executability and validation. We end with sample analysis building blocks (ABBs) from mechanics of materials showing how SysML captures engineering knowledge in a reusable form. Part 2 employs these ABBs in a high diversity mechanical example that integrates computer‐aided design and engineering analysis (CAD/CAE). The object and constraint graph concepts embodied in SysML parametrics and COBs provide modular analysis capabilities based on multi‐directional constraints. These concepts and capabilities provide a semantically rich way to organize and reuse the complex relations and properties that characterize SBD models. Representing relations as non‐causal constraints, which generally accept any valid combination of inputs and outputs, enhances modeling flexibility and expressiveness. We envision SysML becoming a unifying representation of domain‐specific engineering analysis models that include fine‐grain associativity with other domain‐ and system‐level models, ultimately providing fundamental capabilities for next‐generation systems lifecycle management.

Abstract-Small spacecraft are more highly resource-constrained by mass, power, volume, delivery timelines, and financial cost relative to their larger counterparts. Small spacecraft are operationally challenging because subsystem functions are coupled and constrained by the limited available commodities (e.g. data, energy, and access times to ground resources). Furthermore, additional operational complexities arise because small spacecraft components are physically integrated, which may yield thermal or radio frequency interference.In this paper, we extend our initial Model Based Systems Engineering (MBSE) framework developed for a small spacecraft mission by demonstrating the ability to model different behaviors and scenarios.We integrate several simulation tools to execute SysML-based behavior models, including subsystem functions and internal states of the spacecraft. We demonstrate utility of this approach to drive the system analysis and design process. We demonstrate applicability of the simulation environment to capture realistic spacecraft operational scenarios, which include energy collection, the data acquisition, and downloading to ground stations.The integrated modeling environment enables users to extract feasibility, performance, and robustness metrics. This enables visualization of both the physical states (e.g. position, attitude) and functional states (e.g. operating points of various subsystems) of the spacecraft for representative mission scenarios.The modeling approach presented in this paper offers spacecraft designers and operators the opportunity to assess the feasibility of vehicle and network parameters, as well as the feasibility of operational schedules. This will enable future missions to benefit from using these models throughout the full design, test, and fly cycle. In particular, vehicle and network parameters and schedules can be verified prior to being implemented, during mission operations, and can also be updated in near real-time with operational performance feedback.

Model-Based Systems Engineering is founded on the principle of a unified system model that can coordinate architecture, mechanical, electrical, software, verification, and other discipline-specific models across the system lifecycle. This vision of a Total System Model as the digital blueprint (or digital twin) of a system, federating models in multiple vendor tools and configuration-controlled repositories, has gained tremendous support from the practitioners. A software platform, Syndeia, developed by Intercax, provides capabilities for seamless model-based communication between systems engineering and X (where X = mechanical/electrical, simulation, PLM, ALM, project management, and other disciplines), replacing the existing document-centric approaches. This paper elaborates research and development performed by NASA JPL and Intercax for integrating system architecture models (SysML) and mechanical design models (CAD) with applications to the Europa Clipper Mission. Specifically, this paper demonstrates (1) seeding of mechanical design models from system specifications (SysML) as a starting point for mechanical design, (2) model-based connections between system and mechanical design parameters, including compare and bi-directional synchronization, (3) abstracting system architecture from mechanical assemblies for transitioning existing/old projects to a model-based systems approach, and (4) use of persistent, fine-grained connections between system architecture and mechanical design models for continuous verification and communication between the two disciplines. The paper also covers organizational, cultural, and technical challenges that need to be addressed for seamless integration between system architecture models and mechanical/electrical design models, as well as other disciplines.

Smart manufacturing promises to provide significant increases in productivity and effectiveness of manufacturing systems by better connecting the data from people, processes, and things. However, there is no uniform, generalized method for deploying linked-data concepts to the manufacturing domain. The literature describes and commercial vendors offer centralized data-repository solutions, but these types of approaches quickly breakdown under the intense burden of managing and reconciling all the data flowing in and out of the various repositories across the product lifecycle. In this paper, we introduce a method for linking and tracing data throughout the product lifecycle using graphs to form digital threads. We describe a prototype implementation of the method and a case study to demonstrate an information round-trip for a product assembly between the design, manufacturing, and quality domains of the product lifecycle. The expected impact from this novel, standards-based, linked-data method is the ability to use digital threads to provide data, system, and viewpoint interoperability in the deployment of smart manufacturing to realize industry’s $30 Billion annual opportunity.

Model Based Systems Engineering (MBSE) is an evolving practice in the early stages of adoption similar to the mechanical, electrical and software domains 20 to 30 years ago. Today there is increasing recognition of the potential MBSE brings to system life cycle processes with the increasing complexity of systems and the demands of the global marketplace. In order for the practice to realize this potential, system modeling and MBSE must be part of the larger model based engineering effort, and integrate with other engineering discipline models and modeling activities across the life cycle of a system. This is placing increasing demands on the need for Model Lifecycle Management (MLM) as an essential part of an MBSE infrastructure. This paper establishes the motivation for MLM, as well as laying the foundation for addressing challenges that lay ahead. The paper is focused on describing key concepts, requirements, current practices, and future directions of MLM, and setting the basis for more in depth overview of MLM solutions and vendor offering that are beyond the scope of this paper. Motivation -Model Lifecycle Management as an Enabler of Model-Based Systems Engineering (MBSE)Smarter and more complex products enter our lives every day. The modern society in the 21th century is more dependent than ever on such systems that serve our basic needs for health, communication, transportation, financial management, education, entertainment and much, much more. These smarter products today are not independent. They usually consist of collections of other constituent systems, and often dependent on the behavior of external systems. Products are more and more autonomous, capable of optimizing their operation and perform goal-seeking behaviors. Moreover, we witness the growing importance of smarter, cyber-physical systems that combine software, hardware, mechanical and electrical components. Ever increasing demands on system performance is driving tighter integration of the engineering disciplines to provide this performance. This convergence of engineering disciplines, as well as growing business challenges such as shorter time to market, strict safety requirements, higher product quality and stricter regulatory compliance increase the need for new and holistic system approaches and methodologies that support system design. These factors have led to the the engineering domain innovators to modeling, abstraction and multi-disciplinary