It’s good to plant trees to tackle air pollution. It’s even better if you leverage the right tools to reduce carbon emissions – and/or at least to try understanding the potential savings that may exist when it comes to this topic. That’s the reason why I advocate for solutions such as the CO2e Reduction Indicator, DiManex recently unveiled.
DiManEx develops an AI-driven, AM platform–based service that can help users identify the right parts eligible for on-demand manufacturing and for re-engineering using the supply chain and technical data.
Its CO2e Reduction Indicator aims to help AM users understand the potential CO2e annual savings that can be achieved when switching from traditional manufacturing to Additive Manufacturing (AM).
Indeed, as AM has been tagged as a sustainable technology, it makes sense for technology providers to help industries that adopt the technology to understand the reduction of waste material they can achieve or even scrapping of unsold parts.
Potential savings from inventory and local sourcing
Slow moving stock with high minimum order quantities can ultimately result in scrap parts at the end of a service lifetime of a component. Not resorting to minimum quantities ordered, but reordering these items using AM results in fewer parts manufactured, less material used and fewer parts being scrapped. With Dimanex you are able to see the potential savings as well as the quantity and mass of components you can remove from warehousing when AM is adopted, DiManex promises.
Furthermore, it’s important to note that the CO2e Reduction Indicator looks at the benefits of locally sourced components by helping assess the difference in carbon emissions between traditional sourcing and sourcing locally.
Lastly, the launch of this tool emphasizes the importance of relying upon local 3D printing of parts which is what DiManex enables through its global network.
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