Project cooperationUpdated on 28 May 2025
Con(Knit)uous Rubble
About
As renovation and demolition trends are increasing, there is an anticipated volume of concrete rubble. Current methods include crushing the material for recycled concrete aggregate, and others propose computationally intense 3D-scanning and match-making algorithms, usually with the addition of mortars.
We offer a solution that reduces pre-sorting complexity, the need for high-precision joinery and embraces the heterogeneous and granular nature of rubble.
We propose a material system which consists of a knitted soft container, and jammed concrete rubble up to 30cm in width. The knitted container is used to restrict the rubble at a certain volume, while the rubble is responsible for the majority of load bearing.
The automation of the system includes developing a robotic end-effector featuring a circular knitting machine for continuous knitting, a funnel for pouring, and a percolation machine. The benefit of knitting on the fly is the better control of material jamming, material deposition, and hence the creation of precise, compressive architectures similar to very low resolution concrete 3D printing.
We envision the system for initially creating single-storey compressive elements such as columns, arches, vaults and shells.
We are currently looking for industry partners with expertise in industrial knitting, adaptive fabrication with reused materials, as well as support in the production of robust hardware for our end-effector setup.
Stage
- Early idea
- Already defined
Topic
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Enabling technologies | Robotic / handling - and assistance systems
- Enabling technologies | (Advanced) Materials and additive manufacturing
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
Type
- Consortium seeks Partners
Attached files
Similar opportunities
Project cooperation
- Early idea
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
Rebecca Pahmeyer
Research Scientist at Fraunhofer IPA
Stuttgart, Germany
Project cooperation
Al and Circular Economy in Coating and Insulation
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Enabling technologies | Network design of reverse supply chains
- Data technologies | (AI based) process and system control technologies
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
- Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
Kaan AKSOY
Advanced Technologies and Sustainability R&D Department at BETEK BOYA VE KİMYA SANAYİ A.Ş
İSTANBUL, Türkiye
Project cooperation
- Already defined
- Expertise offered
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Enabling technologies | Network design of reverse supply chains
- Enabling technologies | Robotic / handling - and assistance systems
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Data technologies | Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across systems
- Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
- Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
Justus von Geibler
Co-Head Research Unit Innovation Labs at Wuppertal Institut für Klima, Umwelt, Energie
Wuppertal, Germany