Factory Resource and Energy Efficiency through Digitalization (FREED)
| Reference number | |
| Coordinator | Chalmers Tekniska Högskola AB - Industrial and Materials Science |
| Funding from Vinnova | SEK 990 947 |
| Project duration | April 2021 - December 2021 |
| Status | Completed |
| Venture | FFI - Sustainable Production |
| End-of-project report | 2020-05180eng.pdf (pdf, 2530 kB) |
Important results from the project
Environmental impacts need to be considered as high-priority drivers of performance alongside cost, quality, safety, delivery times and customer satisfaction. Increasingly complex factors of performance need to be monitored, often resulting in large amounts of data, presenting a new challenge for production management. Through its specific objectives, FREED aimed to support resource-efficient/green manufacturing by investigating how data-informed approaches could support the implementation of eco-efficiency and circular economy concepts at factory level.
Expected long term effects
The FREED pre-study focused on data-informed environmental improvements in manufacturing. The main outcomes are: - Literature review of current empirical research on green manufacturing, including suggestions to overcome industrial challenges using digitalization as an enabler - Industrial practice review to create a typology for data-informed environmental improvements and for learning/dissemination of good practices - Maturity assessment model and procedure to evaluate the maturity of current data management systems to support environmental performance management
Approach and implementation
The pre-study focused on digital maturity to support green manufacturing. Accordingly, two main activities were conducted: a state-of-the-art review and a maturity assessment. The state-of-the-art review covered scientific publications and industrial practices to bridge the knowing-doing gap. The maturity assessment model was tested at Autoliv and Volvo to further develop it. The results point to strengths and areas of improvement which can be used as foundations for future projects and initiatives on data-informed approaches for environmental performance management.