How can logistics become more resource-efficient and produce fewer emissions?

At Fraunhofer IML, we have a holistic understanding of sustainability - in the interplay of economy, environment and society. We combine technology development and sustainability both in our publicly funded research projects and in our projects with companies, thus making an important contribution to a “twin transition” - a synergistically linked digital and sustainable transformation.

Every year, more than 100 billion parcels are shipped worldwide – with an upward trend. Depending on which study is used, logistics and transport are responsible for more than 5.5, 8 or, including logistics locations, even 11 percent of global CO2 emissions. In Europe, every fifth to second transport trip on the road is said to be empty. Yet, 45 percent of logistics companies do not record their CO2 emissions at all or only incompletely. Figures like these make clear how great the potential of logistics is for sustainability. Today, every company has to consider how emissions can be reduced and resources conserved in the various logistics processes. The researchers at Fraunhofer IML support the logistics industry and its companies, such as logistics service providers, manufacturing companies and system suppliers of logistics facilities, as well as municipalities and organizations, with practical solutions and innovations to protect the environment and conserve resources. With new and innovative approaches, they provide a central contribution to the sustainability of the economic system. Their solutions range from the reduction of packaging material, the optimal utilization of warehouses and containers, to optimized routes and sustainable site conditions.

The challenges of climate change and resource scarcity, combined with the upheaval in mobility, require innovative, scientifically sound solutions. The work of Fraunhofer IML is based on the Sustainable Development Goals (SDG) of the United Nations. We see sustainability as a joint project for all players in logistics. Our research and our projects contribute in particular to five of the 17 global sustainability goals: “Decent work and economic growth”, “Industry, innovation and infrastructure”, “Sustainable cities and communities”, “Sustainable consumption and production” and “Climate action”.

Using digital technologies to make processes and systems more efficient and resource-friendly. 

Digital technologies offer the opportunity to make products and processes more efficient, resource-saving and socially responsible. Digital platforms can be used to link sectors and create synergy effects across industries and sectors. Digital solutions, on the other hand, make it possible to network existing supply and recycling chains to create circular value chains. Specific projects are being developed at the institute: from smart mobility concepts that reduce pollutant emissions and conserve natural resources to new approaches for the recycling and utilization of existing resources and products in the sense of a circular economy. 

Objectifying sustainability by measuring it with digital technologies.

In addition, companies need information about the sustainability criteria of their products and services for a sustainable logistics system. Digital technologies help them to measure this sustainability - whether emissions, inefficiencies or workplace impacts induced by digitalized environments. This makes sustainability objectifiable and comparable

Reduce resource consumption and emissions of digital technologies.

However, digital technologies consume resources such as rare earths or energy during their production and operation and cause (greenhouse gas) emissions themselves. Research therefore also focuses on the sustainable development, sustainable design and sustainable use of digital technologies. The aim is to reduce energy requirements through optimized resource management of hardware and software - e.g. communication networks, IoT devices and mobile robots. Storage systems should be based on principles of data economy, and concepts for training AI models are being tested for efficiency.