7 ways Artificial Intelligence (AI) can support a Circular Economy
The Industrial Revolution 4.0 has caused a rapid shift to using highly advanced, smartly automated, and quickly evolving technologies for not just daily duties but also workplace efficiency. Artificial Intelligence (AI) is one such technology that has blurred the boundaries between the physical, biological and the digital world.
The current linear economy is leading to resource scarcity and pollution. To establish a Circular Economy, there are disruptions required across the whole supply chain, right from Cradle to Grave - to help a Cradle to Cradle value chain with continuous closed loops of Material Flows. Industries and organisations would need to transition in their design, processes, stakeholder management and decision making to include circularity in their working.
This is a challenging prospect in the current world scenario and would require new emerging technologies to be utilised and incorporated. Blockchain, IoT, Data Mining, Machine Learning and AI are some ways these challenges can be tackled.
Here we look at 7 ways how AI can support a Circular Economy:
AI and Material Science: Through the mode of Machine Learning and AI, large amount of material related data can be analysed to understand their properties, applications and flows. This can help incorporate these materials towards a circular and regenerative design.
Using AI for Circular and Regenerative Design: Artificial intelligence can be used to effectively incorporate circularity in the design of products and services. It would help render different materials into a design with adjustments or a complete redesign thus helping to visualise a design for environment product. This would be done more efiiciently and provide a perspective to design for environment and design out waste.
AI and circular production lines: Robotics has already been used in manufacturing industries since some years. This can be further expanded upon helping in efficient production lines within the organisation and reducing human error or fatigue. Waste production can be reduced in the process as pre-visualisation would include optimal usage of raw materials and resources for the production process.
AI and circular business value chains: Artificial Intelligence can aid businesses to track and keep a record of the upstream and downstream supply chains including reverse logistics. This would help record the flow of products (at end of life) back to facility to be reused, refurbished or remanufactured OR the flow of resources and molecules to be recycled and re-incorporated into the production lines. Furthermore, the quality of these materials can be assessed automatically.
AI and pricing: Due to a track record on the material flows along business models, a changing price can be included based on the shelf life of products so that once nearing expiry could be purchased and used instead of being thrown to waste.
AI and rental businesses: Machine Learning and AI would be a boon for businesses working on the service as rental model. These circular businesses of the performance economy can easily track the movement of their products and services including the number of times it is reused, further aiding in quality maintenance.
AI and waste management infrastructure: Identification, segregation and recycling of waste streams can be easily performed through AI technology. Due to use of AI in designing, disassembly and reassembly would be done with less complexity.
"AI presents opportunities not just in circular economy but for an overall sustainable developmeent"
Artificial Intelligence presents with many innovative and exciting opportunities in the present time when the world is looking to move towards a sustainable and circular economy. There are challenges yet to be overcome to incorporate machine learning and robotics in businesses and industries, including a just trnsition. However, the potential of this technology is promising and can make the transition less complex and efficient. It can keep a check on all the forms of capital - natural, finance, human and cultural.