ManufacturingJune 10, 2024

Sustainability in Manufacturing – How Can You up Your Game?

If you are serious about improving the overall sustainability of your manufacturing operations, investing in innovative technologies that promote sustainable practices is a great place to start. Machine learning and generative AI have the potential to revolutionize sustainability in product design and supply chain management, as they can reduce mistakes and product wastage.
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Avatar Wendy (Klotz) Mlynarek

Sustainability has played an integral role in manufacturing over the past few years and there’s no denying that sustainable manufacturing will only become more important in the future. With more reliance than ever before on sustainable manufacturing by customers and end users, those within the sector must have robust plans on how to not only become more sustainable in their operations, but also how to communicate this to prospective buyers.

But what can your manufacturing organization do to ensure it operates as sustainably as possible while also maintaining high levels of service and product quality? Our team at DELMIA explores four of the best tried-and-tested methods of becoming a sustainable first manufacturer.

Invest in innovative technologies for sustainability

If you are serious about improving the overall sustainability of your manufacturing operations, investing in innovative technologies that promote sustainable practices is a great place to start. Machine learning and generative AI have the potential to revolutionize sustainability in product design and supply chain management, as they can reduce mistakes and product wastage.

Generative AI and augmented reality can make a real difference when manufacturers want to take more control of sustainable practices. For example, augmented reality (AR) allows you to virtually experience real-world issues to improve production, assembly, quality and inspection. By utilizing AR, you can significantly reduce product quality testing waste in the real world and implement training that would otherwise have been conducted on real products.

Another key benefit that generative AI and AR can bring to the table is detecting an anomaly on a machine as soon as it happens, which leads to less downtime for fixes and less product wastage if the machine is churning out products with defects.

Leverage technology for sustainable outcomes

In years gone by leveraging technology for optimal performance has always been about increasing the profit margin, and while this is still the case, sustainability is front of mind when taking on new technologies. For example, virtual twin experiences and simulation tools are key strategies for enhancing sustainability in product design and manufacturing processes, allowing for more efficient resource use and lower environmental impacts.

We are seeing more and more manufacturers setting environmental KPIs, such as cutting CO2 emissions, which is a great step in the right direction for the sector. Adopting technologies such as virtual twins as part of the supply chain is growing in popularity as manufacturers can model the entire network, from raw material to the product being on the customer’s shelf. This catch-all solution is perfect, as we are finding more manufacturers are factoring in things like logistics planning and measuring Co2 emissions as part of the decision-making process, and virtual twin technology can help with this.

Adopt a circular economy for your manufacturing

The principle of adopting a circular economy has rapidly grown among manufacturers around the world in recent years, and there’s good reason for this. Businesses who were early adopters of circular economies have been able to showcase a shift to more sustainable production and consumption models, by recycling, reusing and repairing materials to reduce raw material consumption and reduce wastage.

Manufacturers who have adopted a circular economy have seen a plethora of benefits from:

  • Vastly reduced waste
  • Cost savings over time
  • Increased customer loyalty

If you are looking to make a start on your circular economy for your manufacturing business, we would recommend taking the time to map out all of your key process touchpoints.

In areas where you see lots of waste, why not see if there are any ways you can recycle or reuse any of those wasted materials anywhere else in the production line? While this only feels like a small change, it’s a step in the right direction and will allow your business to fine-tune other areas of your manufacturing process and find more ways to reduce waste and recycle parts where appropriate.

Collaborate across disciplines

The necessity of cross-departmental and interdisciplinary collaboration and data sharing is a fundamental component for achieving significant strides in sustainable manufacturing practices.

While this may sound simple, it’s an effective way of ensuring that all areas of your business work together toward the same common goal, whether optimizing productivity, increasing output or finding ways to reduce the business’s carbon footprint.

As part of a deep dive into the various areas of your business, you’ll likely find some crossover in several departments, where slight adjustments in ways of working could lead to a positive outcome from a sustainability perspective. For example, one department could have a lot of waste products currently not serving another purpose, but you might find that another area of your business could put those waste products to use. Not only is this a great way to reduce waste and enhance your company’s sustainability, but it’s also a great example of a circular economy, which is important for all businesses today.

 While it’s fair to say that some sustainable practices are easier to implement than others, the important thing to consider is that any steps your business can take to minimize its overall carbon footprint is a positive. There’s a clear correlation between AI, AR and virtual twin technology and vastly improved sustainability figures, thanks to their ability to iron out mistakes more effectively than trial and error.

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