Build a better business with sustainable product design

Designing a successful product has always been a balance of performance, cost, and quality to meet market needs. But these metrics do not take the full, lifetime environmental impact of a product into account. Sustainability is being added to the triad of metrics to ensure the full, lifetime environmental impact of a product is addressed in even the most complex systems. The only effective way to do this is from the very beginning as nearly 80 percent of a product’s lifetime environmental impact is determined during the design phase – what materials are used, how it’s manufactured, energy efficiency, and what comes of it after its usefulness ends. The solution to these problems is to deploy sustainability as an additional business metric and use digitalization to get there faster than the competition.

Finding a truly sustainable solution in the design phase requires a wide understanding of environmental impacts early in development. These include insight into all the product’s material and energy use, the manufacturing process’ environmental impacts, and its expected resource consumption and carbon footprint in the real world. The designer must also account for the suppliers, distributors, and logistics providers, and how they influence resource consumption and circularity. All while balancing sustainability with the traditional profitability, performance, and quality goals. Data and digitalization are the foundation for creating such a holistic approach to design, leveraging the collective intelligence of the digital enterprise. Achieving this, however, requires reimagining the product design process to be built on a system of systems approach, a connected industrial ecosystem, and holistic sustainability indicators.

Start with systems of systems design

A system, in this case, is an overly broad term. It can be as specific as a feature of the integrated circuit in an electronic device or as extensive as the environment that product will occupy. Most modern products cannot be described as a single system because of the many engineering disciplines required for development. Instead, these products are considered a system of systems. An outboard motor for a boat is a good example of this complexity – electronics control operation, hydrodynamic geometries create thrust efficiently, and a ballet of moving parts extracts kinetic energy from chemical potential in the engine. Coordinating these diverse disciplines when working on a project requires simulation early and often to optimize individual systems and then balance how they interact.

This robust simulation is enabled by the comprehensive digital twin of the product, first and foremost. For an outboard motor, increasing the blade pitch may improve the hydrodynamic efficiency, but it relies on the engine and every system in between to deliver enough power and remain within specification for carbon emissions in operation. These multidisciplinary optimizations are faster than ever and require fewer resources to find the best solution considering performance, cost, quality and sustainability.

The value of simulation is not limited to the product.  There is also great value in simulating the production process.  The digital twin of production is also imperative to a system of systems approach, providing an understanding of how the product is produced, its logistics costs, its usable lifetime, and how it fits into a circular economy through reuse or recycling. It binds the design space to what is viable, profitable, and sustainable for the business.

When assessing the sustainability, cost, performance, and quality of a product this early in development, broad exploration provides a more intelligently defined design space. Sustainability requirements and assessments must be seamlessly woven in from the beginning to make informed decisions. One material may be selected over another due to a superior strength to weight ratio for product performance. A material may be avoided due to the estimated CO₂ emission cost of extraction over the recyclability of yet another material, and components might be designed for a specific manufacturing process like 3D printing to minimize material waste.

Cox Marine is a great example of a company embracing a system of systems design approach for sustainability improvements. They achieved a 25 percent more fuel-efficient motor design that stays in operation three times longer than the prior generation. By embracing this system of systems approach within an end-to-end digital process they could more readily balance their competing product goals.

Stay on track in a connected industrial ecosystem

Making the right sustainability decisions during the design phase requires access to the most accurate and broad collection of data to create a truly comprehensive digital twin of the product and production that includes the extended network of suppliers, logistics operations, and energy infrastructure. Bringing information together from these entities in the industrial ecosystem provides all entities with a more comprehensive and dynamic understanding of the product, process, and operations of a business. This understanding provides all entities with the collective intelligence to make better decisions. This collective intelligence expands and evolves, more data is collected from simulation, manufacturing data, real-world performance information, and secondary emissions analysis from operations, to optimize current product design as well as future designs. This intelligence across the industrial ecosystem enables informed and collective decisions among every partner and supplier.

A robust communications ecosystem for product design must cover the entire value chain, but it also needs to be established early on in development. This means coordinating actions and data exchange with the suppliers, distributors, and other partners as they are key contributors to the data stream for an ecosystems’ collective intelligence. This gives designers direct access to sourcing information on materials and contracted sub-systems. Simultaneously, a robust product lifecycle management system, built on digitalization, weaves together all the engineering work needed to create today’s complex products, ensuring decisions are made with input from subsystem suppliers, and taking into account the available resources of the enterprise. Integrating these once disparate or siloed parts helps bring a better and more sustainable product to market faster.

Next, a well-connected industrial design ecosystem also provides feedback loops between design and the value chain. Returning to the 3D printing example, the mechanical designers may have requested and designed a product around one aluminum alloy in initial design iterations, but the supplier discovers a slightly different alloy with comparable properties but with better print viability within the existing infrastructure. Whether the business decision is to change the alloy or contract with a different manufacturing supplier that can reliably print in the initial alloy, this new data point is added to the collective intelligence for future iterations.

Supplier decisions can have dramatic impacts on the sustainability of a product. One supplier might be able to employ renewable electricity because of their proximity to wind, solar, or other sustainable energy sources. Another might be closer, geographically, to the rest of manufacturing which limits the emissions due to transportation and logistics. And if a business has in-house manufacturing operations, selecting the right energy supplier can be just as critical – energy availability forecasts based on weather patterns for wind or solar collection can help optimize the secondary emissions from energy consumption. These types of metrics are critical in making products more sustainable across the entire value chain.

With enough foresight, the collaborations can extend even further in the value chain to what happens when the product reaches end-of-life, working towards a circular economy. Choosing a stronger material means it could be re-used, but if the design is expected to change dramatically, a more recyclable material might be selected instead. A stronger component may also be more difficult to manufacture, requiring more energy intensive processes or expertise not available to the business’ suppliers. The volume and variability of these decisions is why digitalization and simulation are so important to sustainable design – simpler decisions can be automated, and complex ones are infused with greater intelligence.

Further optimize design with holistic sustainability indicators

Finally, it is important to revisit and evaluate the decisions at every stage of the product lifecycle.  Holistic sustainability indicators must be integrated into the digital twin of the product from the beginning to gain an ongoing visibility and better evaluate sustainability goals in concert with the more traditional goals of cost, quality, and performance. For many systems, this requires the design to include physical sensors that collect diagnostic and environmental conditions of a product through manufacturing, delivery, and usage on top of business data like associated carbon footprints and material costs. With a larger dataset, it is even possible to include virtual sensors that rely on the models created in the digital twin. Finally, to process the massive, ongoing data collection into actionable insights some form of artificial intelligence or machine learning will be needed.

Physical sensors continually feed updated data into the simulation models, providing a clearer understanding of the impact of decisions early in design while virtual sensors employ data from physical understanding and models to interpolate and extrapolate sustainability indicators in complex systems. These indicators enable closed-loop optimization between design, manufacturing, and usage. But reaching that breadth requires adoption across the entire value chain. These continuous data and sustainability indicators help optimize, for example, a vehicle on the road to meet or improve the expected emissions targets defined in the product design. When the physical sensors raise a flag that efficiency is suppressed, the data can be brought back into the digital twin to quickly determine the root cause. From there, an over-the-air update can be pushed to the vehicle resolving the issue without the customer needing to visit a service center. If it is a hardware issue, the data can be shared with the organization and supplier network to correct the problem.

Ready for your next, sustainable design

Sustainable design is about intentional decisions based on the collective intelligence of a product’s design, manufacturing, and operation across the entire value chain. It enables a product to be delivered with the fewest number of resources, be they material, energy, or otherwise. This requires a system of systems approach to create a comprehensive digital twin that accurately reflects all the diverse disciplines needed to create a complex product and establishing the digital environment for simulation. It also needs to be built upon an industrial design ecosystem that facilitates the flow of crucial, real-time data across the enterprise and with external suppliers and subcontractors by digitalizing every task in the workflow. And holistic sustainability indicators must be included to ensure decisions are well-informed to meet sustainability targets alongside other business goals. Sustainable products start with sustainable designs, created with intention.