This emerging methodology enables engineers to design software-defined products in concert between domains, rather than in isolation.
Siemens has sponsored this post. Written by Nand Kochhar, Vice President of Automation & Transportation, Siemens Digital Industries Software.
Numerous industries from automotive to industrial machinery are undergoing radical transformations. Companies across the board are reevaluating the ways they conduct their businesses to account for an evolving combination of consumer demands, environmental pressures and a changing workforce. Within every major change is the potential for new opportunities, and new technologies are the key to enabling these opportunities.
Software is one such technology that is continually improving and is already a critical component of many products. Everything from household appliances to cars are integrating new software-enabled features to improve product functionalities and customer experiences. Despite these benefits, however, software also brings increasing product complexity and new cross-domain interactions, creating a need for new methodologies in product design and development.
Software and systems engineering (SSE) is a methodology that establishes a connective development process enabling engineers to design software-defined products in concert between domains rather than in isolation. It helps create a robust digital thread of design data, test results, simulations and other artifacts of product development, ensuring this data is accessible when and where it is needed. This methodology will be a core component of a wider effort by industries to mature their digital transformations.
Connecting tools and processes
Future product development will increasingly rely on SSE as software platforms become more advanced and readily available. More and more engineers are designing their products’ features to operate on software. In the automotive industry, for example, many manufacturers are turning to making software-defined vehicles (SDVs), in which seemingly mature systems such as parts of the steering, throttle and braking systems are rebuilt in software. Using SSE methods in these instances will better account for new software systems’ effects on other systems.
Design tools will also need to enable a more holistic picture of the product to ensure the integration of all these systems is successful. With software impacting multiple engineering domains from mechanics to electrical systems, tools will need to incorporate new features that enable cross-domain data management and verification. By introducing these features into design tools, engineering teams can co-develop all the hardware including silicon, board systems and electronics with the software and mechanical systems to ensure everything is properly integrated into a working, cohesive product.
Toward digital transformation maturity
These actions are just a portion of those that can be undertaken by companies in their larger digital transformation journeys. Digital transformation enables companies to promote innovation across engineering domains and product functions, as well as address standing industry-wide issues in the short and long term such as workforce shortages. Creating a long-term digital transformation strategy gives companies the potential to go even further than data connection to incorporate new, advanced functions such as automated data management, generative artificial intelligence (AI) and the closed-loop optimization of products, software, manufacturing and beyond.
This is outlined in a five-stage framework developed by Siemens Digital Industries Software to help companies gauge the maturity of their own digital transformation journeys. The five stages include configuration, connection, automation, generative design and closed-loop optimization.
Most companies are somewhere along the first two stages in the process of digital transformation, configuration and connection. Configuration is the transition from document-based methodologies to model-based methodologies, while connection is about bridging data between multiple engineering domains.
SSE works hand in hand with these two stages, utilizing model-based systems engineering and connected domains to ensure the integration of software is successful from the very beginning of design. With enhanced traceability and easier cross-domain verification, engineers can better co-develop hardware, software and other systems and ensure they all work in harmony as a functional software-defined product. However, utilizing the full potential of digital transformation requires companies to go beyond configuration and connection, integrating AI into engineering processes to empower engineers. Companies can begin by automating mundane tasks that are critical but keep engineers from performing work with greater value, before moving on to automate more complex tasks. As AI grows in ability, it can then be relied on to perform generative design, automatically generating new designs based on a company’s data. The ultimate goal is for companies to one day be able to perform closed-loop optimization by generating, evaluating and iterating designs before selecting the most optimized.
A future for software-defined products
The five stages of digital transformation maturity are meant to guide companies and their engineers in determining their path toward optimizing their future product design and development methodologies. They will ensure that products designed with SSE methodologies are not only successful in integrating software with the rest of their systems, but that they are designed to function at their very best.
The connectiveness SSE brings to development processes and design tools is not only critical to building the products of the future, but also vital to building the foundation for digital transformation maturity. As companies continue maturing these processes toward greater automation, generation and optimization, new design methodologies will emerge that allow their engineers to create software-defined products that bring the future to customers today.
This article is the second in a new five-part series on digital transformation. Read the first article, The comprehensive digital twin is a foundation for digital transformation, and don’t forget to check back next week as one of my colleagues takes a closer look at the convergence of information and operation technologies.
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