A circular economy requires all supply chains to think creatively about waste by redesigning products, components and packaging to create safe compostable material enabling more products to be built. Wherever the raw materials of the product are not biodegradable, recycling the metals, alloys to make it useful beyond the products shelf life is needed. Rethinking on mechanism to return, renew and reuse is the key. In view to this, Artificial Intelligence is helping supply chains to be economically circular, writes Raghavan Santhanam, Senior Consultant, Stratadigm.
COVID-19 outbreak has forced people to become philosophical and has highlighted the importance of not interfering with nature. Almost all agree with Newton’s third law, which states that “For every action, there is an equal and opposite reaction”. The law of Karma also states the same. The Sanskrit word Karma simply means “action.” In essence, "what goes around comes around."
Nothing illustrates the interference with nature better than the current state of the Supply Chain in the fashion industry, which basically takes raw material, makes and disposes after usage. This take-make-waste describes the linear approach humans have taken. Fashion industry valued at over trillion dollars, expected to triple by 2050, has issues of human rights abuses, clogged landfills due to end of use clothes (synthetic and non-synthetic), ocean polluting micro plastics because of chemicals, dyes used in processing of textiles. Every second, the equivalent of one garbage truck of textiles is landfilled or burned. Of course, these issues exist in all industries and it is unfair to single out any one industry. Every time we dispose off a mobile phone to get a new one, or a new fridge or a new washing machine, we are contributing to a linear economy. This then brings us to the question – is there is an alternate way?
A circular economy requires all supply chains to think creatively about waste by redesigning products, components and packaging to create safe compostable material enabling more products to be built. Wherever the raw materials of the product are non-biodegradable, recycling the metals, alloys to make it useful beyond the products shelf life is needed. Recovering and restoring products, components, and materials through strategies like reuse, repair, remanufacture or (in the last resort) recycling is critical. Rethinking on mechanism to return, renew and reuse is the key. All transportation using renewable energy then completes the circular economy. The circular economy, in essence, is a closed loop based on the 7Rs – Reduce, Reuse, Renew, Repair, Recycle, Recover and Redesign. According to the Ellen Macarthur foundation, a circular economy is based on the principles of designing out waste and pollution, keeping products and materials in use, and regenerating natural systems. A circular economy is one that is restorative and regenerative by design.
The World Economic Forum defines ‘circular economy’ in a report as follows: “A circular economy is an industrial system that is restorative or regenerative by intention and design. It replaces the end-of-life concept with restoration, shifts towards the use of renewable energy, eliminates the use of toxic chemicals, which impair reuse and return to the biosphere, and aims for the elimination of waste through the superior design of materials, products, systems and business models.”
Many organizations and CEOs across industries have stated sustainability as their goal. Circularity and Sustainability are used interchangeably; however, they are different. According to the US Chamber of Commerce foundation, the practice of circularity is focused on a human construct designed to support the conversion of raw materials for human consumption beyond simple survival needs of food and water. The intentional design of a system is what separates circularity from sustainability. Many governments have realized and are encouraging the adoption of circular economy principles. At a global level, the Sustainable Development Goals, adopted by the United Nations Member States in 2015, include many related ambitions of a circular economy. Hence it is critical that organizations pay attention to incorporating circular economy principles while designing their supply chain.
IMPLEMENTATION CHALLENGES & SUPPLY CHAIN
Some would argue that the implementation of Circular economy in manufacturing companies is being done through Product Service Systems (PSS). Product Service Systems promote a focus shift from selling just products to selling the utility, through a mix of products and services while fulfilling the same client demands with less environmental impact. However, one should note that PSS might lead to inefficient practices and less circular models because of the rebound effect.
An example of the rebound effect is the way in which fuel efficiency improvements in passenger cars have made driving cheaper, resulting in users driving more and buying bigger cars (direct effect) and/or spending the remaining savings on other products (indirect effect). As a result, total fuel and energy savings are reduced. Therefore, it is important to look at all supply chains through the prism of circular economy afresh.
Technology is also altering the model of society’s consumption pattern to a sharing model. Pooling of resources and provision of services on demand is a reality today. The growth of platforms worldwide like Uber, Ola, Airbnb have propagated a buy-less, share-more ethos in the last ten years. Connected objects, automation and robotization is now a reality. This augurs well for the implementation of circular economy principles.
Artificial intelligence is now gaining acceptance across supply chains more than ever. This maybe the right time for all supply chains to relook at how artificial intelligence can be applied to convert linear economies to circular economies. Firstly, artificial intelligence has enabled faster and agile learning processes through iterative cycles of designing, prototyping, and gathering feedback. The increased virtualization is enabling design of circular products, components and materials. Secondly, advances in digital technology has enabled collection of real time data from products and users. This is leading to de-materialization, the capability of doing more with less by looking at circular business models like product-as-a-service and leasing.
Lastly, technology led feedback driven intelligence has led to circular operations & infrastructure optimization through increased transparency. Reverse logistics infrastructure required to ‘close the loop’ on products and materials through advancements in sorting and disassembling products, re-manufacture of components, and recycle materials is today easily creatable. End-to-End open source machine learning platforms like TensorFlow that are now available to everyone is making AI accessible to all.
TECH AT PLAY
A research paper by Google, McKinsey & Company, Ellen Macarthur foundation has explored the intersection between artificial intelligence and circular economy. The research, after examining the application of AI in two value chains: food and consumer electronics, concluded that the essential similarities between the opportunities in these two industries suggests that the opportunities for AI to unlock value in a circular economy are not industry specific.
Data is central for redesigning of business models and resource flows to suit the circular economy. According to Atos whitepaper, data plays a key role in sustainable sourcing, eco designing, ensuring compliance and regulation norms, organizing intercompany flows enabling “mutualization” of resources, enabling “servicization” of economy giving priority to usage over possession, allowing customers to be accountable for their choices by providing data on environmental impact. Research by Aris, Daniela and Tim also indicates that data collection (IoT), data integration (PLM) and data analysis (Machine learning) are playing a key role in accelerating supply chains towards a circular economy.
A collaborative white paper by MissionC and Fountech Solutions identified algorithms that can be developed and applied in Circular Economics across various industries. A ‘mix-and-match’ approach is what they recommend addressing potential needs. The algorithms identified were (a) data clustering (b) timeseries analysis (c) outlier detection (d) computer vision and object detection (e) chatbots (f) entity recognition (g) summarization (h) text classification.
Time series analysis is used to detect patterns enabling prediction of future events. For example, IoT sensors attached to whitegoods such as washing machines can monitor vibration frequencies during usage. If this data is used for maintenance, it can prolong the life of the machine. Outlier detection can help in urban resource monitoring (water consumption in a household) and healthcare to eliminate waste. This can also be used for waste materials sorting, enabling their proper separation and collection for potential secondary use. Computer vision and object detection has applicability in detecting when the crop is mature for harvesting (color, size), detecting weeds in soil. How much crop to grow and when to grow can be ascertained through analysis of end user supermarket data. Chatbots conversational agents can be used to answer queries such as origin of materials. Entity recognition has application within the healthcare and financial services industry. Prescriptions by doctors can be used to parse texts enabling creation of patient histories. Summarization can be useful where large bodies of text such as educational material need to be converted to summaries. Text classification involves using Natural Language Understanding (NLU) algorithms to parse the text and automatically classify risk of customer. Keywords such as money-laundering, imprisonment, etc., can describe someone with a high-risk profile.
There is no doubt that organizations would be well served to use the power of AI with a vision for a circular economy. This is still an area that is largely untouched and an opportunity does exist to fundamentally reshape the supply chains into a circular economy that is regenerative, resilient, and fit for the long term from the current linear economy that is extractive and consumptive. According to the circularity gap report 2020, the global economy is only 8.6% circular, just two years ago, it was 9.1%. There is a desperate need for transformative and correctional solutions. A 2018 research study by WBSCD and BCG found that 97% of respondents indicated that Circular Economics drove innovation and made companies more efficient and competitive. Around 51% stated that circular activities already add to company profits. Circular economy model is not just about doing the right thing. It will generate new jobs, encourage innovation and create trillions of dollars in net benefit.
Countries also have a role in shaping the circular economy. The global adoption of a universal development model is certainly not easy and complicated by development gaps between countries. The priorities of economic players (government, cities, sectors, companies, citizen) need to be balanced while working on initiatives. The silver lining is that examples like FairPhone do exist where markets have agreed on technical and functional requirements related to modularity of components. FairPhone was founded by Bas van Abel, Tessa Wernink and Miquel Ballester as a social enterprise company in January 2013. The company's website states that its mission is to "bring a fair smartphone to the market – one designed and produced with minimal harm to people and planet". This gives hope that it is possible to implement common governance tools for a circular economy. Standards about water reuse, eco-design or lifespan of products could also support the shift to smarter practices.
EU Government has already taken the lead by setting ambitious circular economy targets. In January 2018, the European Commission adopted a new set of measures, as part of a Circular Economy Action Plan that call for plastics packaging to be recyclable by 2030, a monitoring Framework on progress towards a circular economy at EU and national level. In 2016, Finland was the first country to publish a national roadmap to become circular by 2025. Netherlands aims to achieve a 100% circular economy by 2050. Significant EU investment and private funding is now available to businesses that can demonstrate use of artificial intelligence to further circular economy. For example, the European Investment Bank has provided EUR 2.1 billion in co-financing circular projects. The Dutch Government has announced an additional contribution of 80 million EUR to promote Circular Economy in 2019 and 2020.
Philips, a global firm, has already started incorporating circular practices, products and models into their business. 15% of its total revenues by 2020 is expected to be from circular products and services. In 2018, revenues from circular propositions was 12% (over 2 billion EUR). Adidas, Lego, IKEA, Akzo Nobel, DSM-Niaga, ING Bank and others are adopting circular business practices.
Organizations like Stuffstr that help consumers to sell their used clothing back, Optoro who help retailers to manage process and sell returns, TOMRA that uses images and data from cameras to identify non uniform produce, Wasteless that helps retailers sell food before it goes bad, Notco that creates plant based substitutes for foods made from animal products, Motivo that has developed a computational suite to reduce waste in the manufacturing process of integrated circuits are already leading the way in terms of applying artificial intelligence to accelerate circular economy.
Indian policy makers, to continue avoiding excessive degradation of natural assets, should look at their programs of much-needed development, and design it in a sustainable and circular manner. For instance, Indian policy makers have already made a start by supporting policy adjustments in the case of cold storage facilities for potato producing regions. As India embarks on its smart cities mission, circular economy principles hold great relevance. Creating buildings in cities with fully closed water, nutrition, material and energy loops will pave the way for living buildings of future. Circular mobility systems in cities would be multimodal. Smart cities would use artificial intelligence to suggest best mode of transport within the city. Cities like Helsinki have adopted it. India has embarked on a bold multi-modal logistics policy. Indian cities now need to incorporate it. Food systems in cities as well as the different products in cities need to be examined. This has repercussions on waste management in cities. India is at the cusp of major transformations with a slew of announced policies. Public-private and cross-sector collaboration at a scale, not seen in India thus far, would be needed to make it a success. It is now time for the Indian private organizations to play their part by developing a circular economy roadmap leveraging on advancements in artificial intelligence.