Shedding light on sustainable product design with AI
Designing a successful sustainable product these days is frequently a careful balancing act, navigating trade-offs between environmental impact and other important factors such as cost, ease of availability, and more. Yet too often is the total information needed to make these trade-off decisions unavailable to engineers and designers, and by the time it becomes available, the product’s sustainability can already be set in stone. Would it not be better to have those insights sooner and enable companies to build greener products from the beginning?
In an episode of The Industry Forward Podcast, Eryn Devola, Head of Sustainability for Siemens Digital Industries, and Neil D’Souza, founder and CEO of Makersite, talk about just that. They discuss the challenges of designing sustainable products, why early design decisions are critical to product sustainability, and how digital technology like artificial intelligence (AI) can grant insights into those decisions and enable companies to shift left in their design processes.
What makes a good sustainable product?
Neil states early on in the episode that a good product is one that is successful, but ensuring success is easier said than done. Developing a successful product requires making a series of considerate decisions that balance a wide variety of factors intrinsic to the product. Products with an emphasis on sustainability obviously want to minimize environmental harm, but companies must also contend with material costs, manufacturability, requirements for specific features, things that determine whether they can get a serviceable product out in the first place.
The problem, Eryn explains, is that the implications of those decisions are not always clear when initially designing the product. Engineers and designers often lack the information or data required to make informed design decisions, and as products today grow more complex, the more likely the final product will not meet intended goals, such as environmental impact. Neil calls this process of designing without key insights “designing in the dark,” and unfortunately it is all too common.
The case for shifting left
Perhaps obviously, designing with all the relevant information readily available would be preferred when developing products of any kind. Companies would be able to get products right the first time, reducing the chances of starting the design process over and saving time and money as a result.
For sustainable products specifically, however, ensuring informed design decisions as early as possible is especially critical. The majority of a product’s sustainability impact is in fact determined in the design stage, and the chances to change said impact decreases later on in the product lifecycle. As Eryn explains, once the parts have been sourced, the equipment bought, the manufacturing begun, it is too late to have a substantial impact on sustainability metrics. Hence, such metrics need to “shift left” and be determined as soon as possible.
AI in the lifecycle
The key to realizing this relies on having effective lifecycle analysis (LCA) tools that can measure the impact of design decisions across the product lifecycle, from design to manufacturing to suppliers and beyond. With the increasing complexity of products, however, Neil cautions traditional approaches to mapping datasets may not be enough. The more complex products are, the more complex their data becomes, as do the methodologies used to manage said data and calculate metrics.
Here is where AI can play a pivotal role. When integrated into LCA processes, AI removes some of that complexity away from engineers and designers, taking on some of the burden to simplify some of the processes and methodologies. By letting AI perform calculations, the impact of design decisions can be revealed quicker, allowing engineers more time to optimize product designs to manage requirements while achieving sustainability goals.
Developing successful sustainable products will require a careful understanding of their impact across their lifecycles as early as possible. AI, when employed in LCA processes, can be a critical step in helping engineers and designers attain that foresight, ensuring they are “designing in the light” and that their products contribute to a more sustainable world in ways they intend.
Stay tuned for further episodes on AI in sustainable product development on The Industry Forward Podcast.
Siemens Digital Industries Software helps organizations of all sizes digitally transform using software, hardware and services from the Siemens Xcelerator business platform. Siemens’ software and the comprehensive digital twin enable companies to optimize their design, engineering and manufacturing processes to turn today’s ideas into the sustainable products of the future. From chips to entire systems, from product to process, across all industries. Siemens Digital Industries Software – Accelerating transformation.
