Stora Enso is seeking to revolutionize its wood harvesting process by automating the selection of compartment harvesting sequences. The goal is to develop an AI model that can analyze historical data, making sure the supply needs are met, and identifying the optimal order of compartments for wood harvesting. This solution should not only ensure that industry supply commitments are met but also prioritize environmental sustainability, biodiversity and maintain an optimal stock level for future harvesting.
Opportunity overview
Stora Enso, a global leader in renewable materials, is focused on optimizing its wood harvesting operations to stay competitive and boost sustainability. The diverse composition of forests and varying demands from mills make it essential to choose the right order for harvesting compartments. With up to 16 different wood assortments from a single harvest and limited roadside storage life, the complexity of managing this process is increasing. As the amount of data per compartment grows, along with increasing operational restrictions, efficiently managing the harvesting process has become more challenging. Additionally, the model and data should consider the environmental aspects of the forest.
To tackle these challenges, Stora Enso is seeking innovative partners to develop AI-driven solutions that streamline harvesting operations. By leveraging advanced technologies, we aim to enhance efficiency, ensure timely delivery of the right wood, and minimize environmental impact, all while maintaining optimal stock levels for future needs.
Opportunity with us
Stora Enso Forest Sweden is at the forefront of integrating AI into its operations and eagerly looking for innovative partners to collaborate with in this pilot project. We offer access to extensive datasets for model training and the chance to develop a solution that, if successful, will be implemented and refined across our entire Swedish supply chain. This is a unique opportunity to make a significant impact in the forestry industry and shape the future of sustainable wood harvesting.
Examples we're looking for
Optimize Harvesting Sequence
Develop an AI-driven solution to determine the optimal order for harvesting compartments based on existing data and constraints. The system should adapt in real-time as new compartments become available.
Enhance Data Quality
Identify key data attributes that require improvement to enhance decision-making accuracy. The AI model will help pinpoint data sources that need refinement, ensuring more precise harvesting decisions in the future.
Stora Enso
Part of the global bioeconomy, Stora Enso is a leading provider of renewable products in packaging, biomaterials, and wooden construction and one of the largest private forest owners in the world. We believe that everything that is made from fossil-based materials today can be made from a tree tomorrow.
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