FFI report - Factory Resource and Energy Efficiency through Digitalization (FREED)

Report, 2021

Sustainable industrial digitalization is fast-growing research area but still in its infancy. Despite the positive outlook of digital technologies in manufacturing, they also present the risk of accelerating our linear economy with faster and more efficient production of goods and services, thereby further trespassing planetary boundaries already exceeded. It is critical to align the goals of sustainable development and industrial development so they reinforce each other. The FREED pre-study focuses on data-informed environmental improvements in manufacturing.
In response to the need for sustainable action, this pre-study is composed to two activities:
WP1. State-of-the-art review: Investigate how digitalization can enhance the environmental sustainability of production systems by reviewing empirical studies demonstrating a broad range of environmental solutions for more sustainable manufacturing. Identify industrial challenges and propose ways in which digitalization should support sustainable production to overcome these challenges. Use published industrial cases of sustainable digitalization to create a good practice typology to organise information around data-informed environmental improvements and support learning/dissemination of good practices. Collect and analyse examples at the partners’ manufacturing sites to check alignment with current knowledge sharing practices.
WP2. Maturity assessments: Develop an assessment model to evaluate the maturity of current environmental approaches and supporting data management systems in manufacturing companies. Identify areas of strengths on which promising sustainability initiatives can be built, as well as potential areas of improvements which should be prioritised to achieve significant environmental benefits. Create pilot specifications to test data-informed approaches for environmental assessment, reporting and improvement (integrate environmental information in performance management via robust data management system).
Ultimately, the project aims to ease the process for collecting, analysing and communicating environmental information so more focus can be placed on systematically integrating this information in decision-making processes and continuous improvement activities.