Component Circularity Management with Scania

Circularity
Asset management
Artificial intelligence
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Industry

Sustainable Transport Systems

Revenue

2021

€14B

Employees

2021

54,000

Connected vehicles

2021

550k+

About

Scania, a world-leading provider of sustainable transport solutions, is looking to further improve the sustainability and circularity management of Scania product components. In case you are working on a solution that contributes to extending the life of components by increasing the visibility of their status and second-life availability throughout the life-cycle, we would like to hear from you.

Opportunity overview

For Scania, circularity involves every aspect of our business. It challenges us to rethink not just how we design and manufacture products, our impact and knowledge of the value chain, but also how we develop business models and provide value for our customers. Committed to sustainability, the circularity and transparency of components in Scania products for heavy transport applications are key. In compliance with regulations related to sustainability and the circular economy, Scania is focused on extending the lifetime of components, saving our customers’ costs by providing an option for second-life components. Alongside this, we would also explore new revenue streams by selling second-life components. Scania also prioritizes supply chain optimization and aims to create a competitive advantage by demonstrating its commitment to innovation and environmental sustainability.

To reach these goals, we are interested in asset tracking and management solutions that include but may not be limited to, traceability, quality, and financial value data of Scania product components throughout their life-cycle. The envisioned solution overall enables Scania to increase the efficient utilization of used parts in the circular system, ranging from manufacturing to scrapping or recycling. The solution should be able to provide both real-time and residual value information, while facilitating predictive data on component availability in a timely fashion based on data points such as component location, quality, or volumes. Ultimately, the potential solution needs to create value for Scania customers by extending the life-cycle of Scania vehicles.

Your opportunity with Scania

Working with Scania provides an opportunity to partner up with a world-leading provider of sustainable transport solutions and work with them in a strategically important field. With 550k+ connected Scania vehicles, global production and interchange of components and complete vehicles, and a global sales and service network, there are significant levels of high-value product and component flows, which makes this a remarkable opportunity to contribute to the circularity objectives of the automotive industry. With Scania’s commitment to sustainability, a potential partnership could enable a strategic role for a selected solution provider on Scania’s journey to a sustainable transport system. Moreover, as Scania has a key strategic focus on vehicle electrification, partnering up with Scania gives your company the chance to contribute to drive the industry’s transformation towards battery electric vehicle adoption and the circularity of BEV components.

Focus Areas

Examples of solutions we’re interested in

Component asset management

We seek solutions that can track, trace and manage assets on a component level. This means following and gathering life-cycle data and usage of different Scania vehicle components and providing accurate information regarding the component type, details, history and health.

Component value estimation

The envisioned solution can estimate conditions of the vehicle components and their financial value throughout the life-cycle. The solution should provide both real-time value and residual value of different vehicle components in order to increase their lifetime efficiency and value for the circular system.

Predictive analysis

The solutions we are looking for should offer Artificial Intelligence or Machine Learning based predictive analytics built on inputs like location, quality or volume of the components. Analytics would include, for example, the second-life component availability, volume across regions.

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