Systems Architecture App from Aras: Bringing Together MBSE and Systems Thinking

Aras introduces a new Systems Architecture app, reinforcing the value towards effective simulation lifecycle management.

As Aras put it: “building an effective Digital Thread that represents the specific needs of [an] enterprise is not easy; (…) Aras low code platform and Systems Thinking enables building a custom, flexible and extendable Digital Thread that connects requirements, systems model, variability and simulation within a single traceable and reusable environment.” (Image courtesy of Aras)

As Aras put it: “building an effective Digital Thread that represents the specific needs of [an] enterprise is not easy; (…) Aras low code platform and Systems Thinking enables building a custom, flexible and extendable Digital Thread that connects requirements, systems model, variability and simulation within a single traceable and reusable environment.” (Image courtesy of Aras.)

With its new Systems Architecture app, Aras is bringing together the coordination of “systems model definition with tool independent data from all engineering disciplines including mechanical, software, electronics, simulation, etc.” This is to be achieved by harmonizing “incompatible system modeling methodologies, languages and tools—breaking down data silos—to enable creative freedom in Model-Based Systems Engineering (MBSE).”

The value of MBSE specifically comes into perspective when considering the distributed nature of data, across product requirements, design, engineering, simulation, material physics, test data, etc. The wide variety of simulation tasks and deliverables presents a typical challenge for cross-functional collaboration, management visibility, result traceability, certification and compliance justification.

The International Council on Systems Engineering (INCOSE) defines systems engineering as “a transdisciplinary and integrative approach to enable the successful realization, use, and retirement of engineered systems, using systems principles and concepts and scientific, technological and management methods.” 

Systems Thinking to Manage Product Complexity

Systems thinking is the foundation of systems engineering, bridging virtual and physical representations, concepts, causes and effects, assumptions, principles and patterns applied to a given science, discipline, or set of disciplines altogether. Connected products require the management of multi-disciplinary data and complexity, which is accelerating with the rise of integrated software-driven products. 

Systems engineering strategies include a combination of simplification and holistic views of a system or system of systems. As Aras put it, systems engineers and engineers across the field need to perform continuous system exploration and validation, with “system architecture” as the connecting platform to meet the changing needs of the enterprise- from design, test, simulate, build, measure, share and re-use across the enterprise digital thread. Systems architecture joins up requirements management with systems engineering, capturing the “descriptive parts of the systems model—often referred to as the functional and logical breakdown of a product.” It also connects them with other aspects of the product design and across the RFLP testing cycle: requirements/ functional/logical/physical.

With their new Systems Architecture app, Aras aims to provide “a system architecture-centric view of products with traceability to all related details, regardless of the tool used to create the model.” Translating this into layman’s terms, the ability to choose the relevant model, process, tools and associated characteristics specific to the relevant engineering activities, tracing and managing data dependencies throughout. For example, this might include CAD and BOM data, combined with other material properties needed for a finite element analysis (FEA), kinematic simulations and thermal analyses. Based on product complexity, it is expected to track such dependencies across product lines and variants, at a given module level, or across multiple data and functional interfaces.

A Platform to Accommodate Systems Modeling, MBSE Methodologies and Tools

Product lifecycle management (PLM) is all about the concept of tracking usage, version and maturity across product development activities and sub-components. It provides visibility of design variables and interdependencies between datasets as well as across data functions and relevant input and output, deliverables and results. Simulation lifecycle management is a typical case for complex data management across numerous data input and output—involving the use of multiple solvers and result formats, either for research study or compliance and certification of a product system.

John Sperling, SVP Product Management at Aras, highlighted that “Aras Systems Architecture together with Aras Requirements Engineering, Aras Simulation Management and Aras Product Engineering provide a key enabler for systems thinking and digital transformation strategies at our customers. These interconnected applications on the Aras platform enable Model-Based Systems Engineering to truly become the driver of next-generation design.” John Sperling also elaborated that “Aras Simulation Management is not a stand-alone modeling capability, [as] it is part of the overall suite of applications on the Aras platform and along with Aras Requirements Engineering, Aras Systems Architecture and Aras Product Engineering [are] a key enabler of Systems Thinking and Digital Transformation strategies for our customers.”

Simulation Management introduced by John Sperling, SVP Product Management at Aras: “innovator platform to bridge the gap between product engineering context and domain-specific activities to foster a more informed decision making” (Image courtesy of Matteo Nicolich, ACE Europe 2019.)

Simulation Management introduced by John Sperling, SVP Product Management at Aras: “innovator platform to bridge the gap between product engineering context and domain-specific activities to foster a more informed decision making” (Image courtesy of Matteo Nicolich, ACE Europe 2019.)

In an eBook published in 2019, Aras described systems of systems simulation in the context of “automating mixed-fidelity, multiphysics and multi-domain simulations at scale [as] the key to designing tomorrow’s smart products: systems of systems with sensor technology that helps them to recognize and adjust to inputs from their environments, or the broader systems of which they are a part.” Simulations contribute to both product virtual verification and validation as well as design and engineering iterations and optimization. This ranges from traditional design and topology optimization to rapid simulation, generative design and additive manufacturing. Simulation lifecycle management contributes to making better quality products, but also cheaper, durable and lightweight ones. It uses reliable and reduced quantities of materials, improves manufacturing processes and possibly delivers them faster to certification and their target markets.

It would be interesting to understand in more detail how the new Systems Architecture app will connect to multiple methodologies and tools. Some questions I have, include: 

  • How would these be embedded into the Aras platform? 
  • What level of configuration and integration might be required to pull information from multiple sources under a single umbrella to manage traceability and feedback loops? 
  • Is Aras referring to systems architecture in the wider sense, or context of a given dataset or application set? 
  • Does this approach include external simulation engines and other data sources?

Over a year ago, Aras announced a licensing partnership with Ansys. It was then described by Peter Schroer, president and CEO at Aras as “a potential game-changer in connecting simulation to engineering processes for traceability, access and reuse across the product lifecycle.” This is why I ask one final question, how does the Systems Architecture app help improve integration with Ansys, and possibly other simulation software vendors?

What are your thoughts?

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Written by

Lionel Grealou

Lionel Grealou, a.k.a. Lio, helps original equipment manufacturers transform, develop, and implement their digital transformation strategies—driving organizational change, data continuity and process improvement, managing the lifecycle of things across enterprise platforms, from PDM to PLM, ERP, MES, PIM, CRM, or BIM. Beyond consulting roles, Lio held leadership positions across industries, with both established OEMs and start-ups, covering the extended innovation lifecycle scope, from research and development, to engineering, discrete and process manufacturing, procurement, finance, supply chain, operations, program management, quality, compliance, marketing, etc.

Lio is an author of the virtual+digital blog (www.virtual-digital.com), sharing insights about the lifecycle of things and all things digital since 2015.