The next generation of model-based systems engineering provides a digitalized solution that can harness the complexity of these integrated systems and deliver superior products.
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Written by: Tim Kinman, Vice President, Trending Solutions Consulting & Global Program Lead for Systems Digitalization, Siemens Digital Industries Software.
The world of engineering and product development is built on the constant improvement of processes and technologies. There are advancements we intentionally interact with every day and infrastructure improvements making our lives better as a whole that may not be given a second thought. Regardless of whether a company is developing the next personal electronic product or working toward a more sustainable transportation system, the engineering work required for improvement is expanding.
That work is also diversifying in discipline for many industries, such as software and electronics becoming major points of value for traditionally mechanical products. Engineering executives around the world are looking for better methods to integrate these systems for developing the next generation of innovative products. They are searching for a solution to bring these products to market faster and to capitalize on the growing demand for smart and connected products.
The next generation of model-based systems engineering, or MBSE, is that method—providing a digitalized solution that can harness the complexity of these integrated systems and deliver superior products.
What MBSE Are You Talking About?
For many out of the automotive, electronics and aerospace industries, the MBSE methodology may be familiar. Earlier implementation and toolsets have been deployed for decades in these industries as an evolution on systems engineering. However, it is important to understand that a modern MBSE approach looks and functions very differently from previous iterations.
Possibly the most important distinction is how the information on the system is captured, stored and shared. Rather than diagrams on a chalkboard or models constructed in PowerPoint, data is stored centrally with secure connections to other relevant information to constitute the system architecture or roadmap for development processes through to service operations. The various processes throughout product development are supported by digital thread workflows that tie decisions and work made in a domain tool to the digital twin.
This single source of truth makes data more readily accessible and valuable to the multi-disciplinary development of today’s and tomorrow’s products.
Establishing the Architecture
The system architecture is the most important aspect of model-based systems engineering, and while it encompasses many roles in a business, the primary function is managing development processes across the entire business and value chain.
Work on the system architecture begins with any project. It might be in the concept phase of a new product or in qualifying the needs of a brownfield product. The system architecture becomes the definition of what the market requires and the blueprint for development. What qualifies a success? How will development decisions be verified and validated? And who will be tasked with refining systems into a domain-specific definition, be it mechanical, software, electronic or even business operations?
The information contained in a system architecture can be quite broad, including requirements from regulatory agencies, to manufacturing limitations of existing infrastructure, into trade-off studies being conducted early on in development. Coordinating this information effectively requires a standardized methodology; for system engineers, this relies on a modeling language such as SysML and a modeling tool like System Modeling Workbench.
Traditionally, every decision, analysis and process within development was aggregated back to a small group of system engineers who would redistribute knowledge between different groups. But the growing interconnectedness of today’s products make this a difficult, if not impossible, endeavor.
Instead, companies developing smart and connected aircraft, automobiles, heavy equipment—you name it—are beginning to democratize the process through digitalization. Relevant decisions are handed off to the multi-disciplinary groups and their investment in the system of systems is delivered back to everyone impacted by the changes. Applying this methodology is only possible through effective communication.
Communicating Effectively
Having a robust system architecture is a great value to most any company, but without communication between all stakeholders, there is no streamlined delivery between departments—and it may not exist at all. A system architecture relies on every department adding context to the system. Communication has seen dramatic improvement in the MBSE workflow over the past few years and is set to accelerate even more with SysML v2, the next-generation modeling language for systems engineering.
Most innovative industries still work with digital documents to communicate the understanding of their complex systems. However, there is a disconnect between wanting a reliable thread from concept to service and having one, which comes down to a lack of capability in the tools and the culture change required in trusting a single source of truth.
SysML v2 is aimed at improving communication for MBSE methodologies between mechanical, electronic, electrical and software domains. Previous implementations could not model many of the complex systems required for aircraft or automobiles as the modeling language was built on top of Universal Modeling Language—originally created for software development only.
Native functionality that was missing pushed large OEMs and design houses to purchase and create custom extensions for SysML to fill the gap. These, however, negate the purpose of a standardized modeling language because suppliers, and even internal departments, could not consume the information and models within the system architecture.
The goal with SysML v2 is to shed the limitations imposed by a UML legacy and build in the syntax to handle the models that system architects and businesses use every day. Proper communication will drive the value associated with downstream reuse, possibly the greatest value proposition of a modern MBSE approach.
Downstream Applications
Communication is important in creating an accurate system architecture and disseminating one across an organization to map development. Communication also enables the reuse of the highly valuable information that these models contain.
Downstream reuse is one of the more difficult benefits to define for an organization, because it can emerge in a very wide set of applications. One example that is highly valuable in creating smart products is reusing software functions to reduce code complexity. For example, in an autonomous vehicle’s emergency braking system, the electronics and software need to understand a variety of factors to identify an obstacle to stop safely. How far away is the object? What is the current velocity? What are the road conditions? Are the brake pads somewhat worn and compensation is needed?
Fulfilling these questions would optimally be completed through software functions that already exist in the vehicle. This reduces the amount of code needed for the vehicle and enables greater optimization of electronic controllers. The alternative would require generalized processors calculating a wider data set with less efficiency. The emergency braking system, for instance, might pull data from the anti-lock braking system, receive velocity and distance measurements from adaptive cruise control and road conditions derived from on-board temperature sensors integrated with cloud-based weather data.
The exact flow of data may be very different, but using the system architecture to plan these use cases and optimize processing greatly improves the effectiveness of these interconnected systems.
Downstream data applications may also influence more business-oriented domains of a product’s development. CAD data from engineering can be used to create marketing materials earlier in the design cycle. Decision traceability provides critical safety information to regulators. Purchasing managers have the required insight on product decisions to pick the right suppliers or wholesalers and improve collaboration between the OEM and supplier network. And the sustainability metrics of a product and its manufacturing process can be evaluated for continued investment in the technology, especially as more investment sources are looking for positive ESG (environmental, social and governance) characteristics.
MBSE for a Global Economy
Model-based systems engineering means many things to many businesses, but every implementation relies on an accurate and communicable system architecture.
To develop a successful product, you need to understand the requirements, costs, materials, manufacturing processes, safety and competitive products to differentiate yours in time, cost, quality and sustainability, or a combination of the four. Knowing these bits of information as a part of an interconnected system provides even more value than discrete knowledge.
Your analysis can be conducted early on with the right software solution, enabling a wider design space to select the best implementation for any situation. And once an optimal architecture has been defined, communicating that plan accurately ensures the right product gets built right and delivered to the customer in a timely fashion.
As supply chains become more complex and span more regions in the global economy, it will be critical to have a development approach that handles the growing complexity. And at Siemens, we are refining the model-based systems engineering approach within our Xcelerator portfolio of software for the future of complex and global development programs, to accelerate your business today.
About the Author:
Tim Kinman is the executive leader for Trending Solutions Consulting and the Global Program Lead for Systems Digitalization. He has over 36 years of product development experience spanning CAD applications, PDM data management and 17 plus years guiding customer business transformation.
In his current role, Tim works with customers worldwide regarding Engineering and Consulting Solutions for enablement of leading edge, trending solutions. Tim acts as a trusted advisor for major accounts with focus on customer business transformation and time to value. As Global Program Lead for model-based systems engineering (MBSE), Tim is engaged across all development and functional organizations to deliver on MBSE vision and working with customers on realization plans addressing their business drivers.
