How Data Can Help Optimize a Product’s Ecological Footprint


By Cedrik Neike, Member of the Managing Board of Siemens AG and CEO Digital Industries

You could see the bottom of the lagoon in Venice. People in Asian megacities could breathe a sigh of relief. And residents in the north Indian state of Punjab could once again see the Himalayas clearly.

The coronavirus gave nature and the climate a brief respite from its stress. Nitrogen oxides, particulates, and above all CO2 emissions plummeted. The Global Carbon Project estimates that fossil emissions fell by a record 7% in 2020, by 2.4 billion tons of CO2, to 34 billion tons. An encouraging sign of what is possible.

But let’s not kid ourselves. As soon as the pandemic ends, we’ll be traveling more again for both business and pleasure. We’ll no longer all work from home; many will resume commuting. And we’ll use more resources again, maybe even more than before the crisis.

Experience shows that a rebound effect often sets in after a crisis, leading to an even higher consumption of resources. That is, unless we take countermeasures.

That’s why it’s especially important now to use our resources more sparingly and efficiently than before the outbreak. And industry can make a major contribution here. The key strategy is the same one used for dealing with the pandemic: digitalization, automation, and the intelligent use of data. After all: resources are finite, but data is infinite.

Data and Digital Twins

Digitalization and automation not only help make production more flexible, enabling it to quickly adapt to changing requirements and demand. They also minimize the use of resources by analyzing and optimizing operations in the virtual world.

The virtual commissioning of a machine tool with the digital twin saves time and resources.

Dashboards show when, how, and where the most energy is used. Data acquisition and analysis show which components in a system are not running optimally and where improvements are needed. And virtual prototypes replace the need for physical models.

With a digital twin—a virtual model of a product or a process—you can test and adapt various designs to meet new requirements. At the same time, you can plan production processes digitally and adapt them to new needs before you even touch a real sheet of metal or screw.

Machines don’t have to drill countless holes in a workpiece until the optimal drilling or milling positions are determined; that’s done beforehand, using a virtual machine tool. This practice obviously reduces material rejects and waste, saves energy and time, and reduces CO2 emissions.

But the analysis and use of data doesn’t stop here. Data can also flow from operations back to the developers to help them improve a product’s design and plan its production. As a result, there’s a continual optimization in both the consumption of resources and the product’s ecological footprint.

Greener Manufacturing

Our manufacturing experts have gone even further at the electronics plant in Amberg, Germany, which the World Economic Forum (WEF) recently acclaimed as a Lighthouse Factory, one of the world’s most advanced factories, which are leading the way in the adoption of Fourth Industrial Revolution technologies.

The experts wanted to determine the complete ecological footprint of a given product. Since many companies claim their products are “green,” it’s important to have comparable, real values based on a common standard across the entire value chain—all the way from the extraction and delivery of raw materials to delivery of the finished product: “from cradle to gate,” so to speak.

WEF Lighthouse factory Amberg, Germany: permanent recording and evaluation of the facility’s energy consumption.

It was easy for the Amberg experts to calculate how much CO2 the factory’s production and controls emitted: they permanently record and evaluate the facility’s energy consumption.

It proved more difficult, however, to determine the size of the “CO2 backpack” before the various product parts reached the factory. Still, almost all manufacturers rely on rough, globally standardized estimates and may have “feel-good” contracts with their direct supplier.

But the Amberg experts wanted more. They not only sought greater transparency in their own supply chain but planned to develop a scalable solution for the entire industry. After all, everyone faces the same problem: on average, 90% of emissions are produced in the supply chain, not in a company’s internal production.

Abstract lock background

The best solution here proved to be cryptographic processes already being used by the food industry for tracking ingredients. Using the same principle, companies can also accurately provide CO2-equivalent data (including five other greenhouse gases along with CO2) to one another. Rather than being stored on a central server, the data is distributed over many individual computers.

Climate Neutral by 2030

Trustworthy CO2-equivalent data can be exchanged in this ecosystem of manufacturers, suppliers, customers, and other partners—and everyone benefits from having a complete and precise CO2 footprint covering the entire supply chain. This makes it easy to see when and where most of the carbon dioxide is produced. One can then target those problematic points and make the value chain more sustainable.

To push their already much smaller CO2 footprint towards zero, our colleagues in Amberg will be able to use local carbon sinks such as sustainably managed forests in the future. In the end, the customer will get a CO2-neutral automation control, a truly “green” product.

This is just one solution Siemens AG is using to become climate-neutral by 2030. That’s our goal—and we’re not that far from reaching it.

Learn more about how Siemens can help your organization use data and achieve more with less.

Cedrik Neike is Member of the Managing Board of Siemens AG and CEO Digital Industries. Furthermore, he is leading IoT business, cybersecurity, and IT.

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