AI-powered circular economy
AI and ML / April, 25 2022

Building an AI-powered circular economy

Over the last 100 years, large-scale manufacturing gained momentum, and consumerism worldwide grew leaps and bounds, thereby resulting in more waste, impacting the ecological balance in more than one way. This means municipalities and local corporations have to spend a substantial part of their budget on solid-waste management. But addressing a problem with exponential growth demands an innovative solution and the employment of the latest technologies to deliver efficient, low-cost approaches. New technologies offer faster and agile learning processes with iterative designing, prototyping, and feedback cycles. 

Artificial intelligence (AI) can play a defining role in enabling this systemic shift. AI is the fundamental driver of the Fourth Industrial Revolution, which uses models and systems that mimic human intelligence functions such as reasoning and learning. The power of AI is that it allows us to learn faster from feedback, address any complex problem effectively, and derive actionable insights from data. A growing number of experiments are being conducted to apply AI can accelerate the transition to a circular economy. The three governing principles of circular economy are to keep out design waste and pollution; produce and retain products and materials at their highest value, and regenerate natural systems. 

AI provides the capability for AI-Powered Circular Economy innovation to take place across many industries in three ways:

Product design, prototype, and testing

When you design for circularity, you have to design the products and select components and materials that can be conducive for disassembly, upgrade, and recycling. Added to this complexity of the design considerations, we have a broad choice of materials, manufacturing techniques, and design options. AI and ML-assisted design can accelerate this complex process through rapid prototyping, testing, and feedback to improve the overall product offering, lead times, and product development cost. 

Develop new circular business models

In the last decade, we have witnessed and participated in several circular economy models such as asset sharing or product as a service. As we have become comfortable with sharing cars and bikes, we may develop higher comfort factors; several other industries are ripe for disruption by introducing circular business models. The development of circular business models that can offer a compelling alternative to the existing linear models demands the cohesive working of all functions such as design, development, production, sales, marketing, pricing, customer support, and reverse logistics unified by circular economy principles.

Effective advancement and adoption of shared economy models in many industries require a robust, dependable infrastructure for handling reverse logistics and remanufacturing. AI as technology lends the technology strength for this. AI uses Real-time insights and historical behavioral data from products and users to predict demand and pricing curves. It also serves well to increase product circulation and asset utilization. Further, AI empowers manufacturers to offer better predictive maintenance for large machinery and adopt more innovative inventory management techniques. 

Optimize Circular Infrastructure

A vital feature of a circular economy is that materials and products are repeatedly used rather than the widespread use and throw model. Hence the products naturally require the feature of reusability, repairability, remanufacturing, and recycling capability. It becomes challenging when we are looking at reclaiming the nutrients from biological waste streams as collecting, sorting, separating, and treating this for redistribution is laborious and expensive. Similarly, winning back the material from used computers is tricky as the waste streams are mixed and heterogeneous. Suppose we can build an effective channel that allows a homogeneous flow of material and products. In that case, our recovery levels improve exponentially, and we can efficiently sort the components that can be put to reuse or remanufacture. 

AI-assisted reverse logistics brings process improvements to material handling, sorting and disassembly of products, recycling materials, and remanufactured components.  

For an AI-powered circular economy to succeed and organizations to use it as a reliable business model, it requires the commitment of all stakeholders. The following examples here can inspire different industries and their leaders to explore further in this direction.

  1. Manufacturing design teams can use AI to improve and speed up the material selection process.
  2. Material scientists involved in the plastic packaging industry can use AI to develop solutions that allow an effective way to repurpose. 
  3. Engineers and Architects can use AI to optimize the building design features based on circular design principles. 
  4. By integrating AI technology and computer vision, we can automatically identify components or parts that require maintenance and reduce the lead time for spare part procurement.
  5. The AI-driven robot system can autonomously or semi-autonomously inspects and disassembles returned pieces of equipment.
  6. Advanced data analytics and AI is being used in the chip design industry to reduce the lead time of the yield ramps and the number of iterations required to eliminate the problems with new products. 
  7. Researchers at Stanford have used AI and machine learning to screen more than 12,000 lithium-containing compounds using several criteria such as stability, cost, and abundance of availability, to identify 21 solid electrolytes that could potentially replace the volatile liquids.

Other examples of using AI to optimize a system for a beneficial outcome include:

using real-time traffic camera data to reduce traffic congestion in cities; optimizing energy usage for cooling the thousands of servers housed in data centers; using EVs for the last mile delivery, integrating AI and autonomous network solutions to ensure that charge points and refueling stations can match electric vehicle demand.

To realize the full potential of AI-powered circular economy solutions, one needs a thorough understanding of the maturity and limitations of AI. Executing solutions similar to those shared above will need a four-step framework that includes data collection, engineering, development, and refinement of the AI models. We also need access to relevant, high-quality data to train algorithms and use as input data to develop AI applications.  Above all this, it is evident that for organizations to harness the power of AI to help reshape the economy into regenerative, resilient, and fit for the long term, it needs a trusted technology partner who has the entire know-how. 

Get in Touch

Newsletter

Stay up-to-date with our latest news, updates, and promotions by subscribing to our newsletter.

Copyright © 2008-2023 Saxon. All rights reserved | Privacy Policy

Address: 1320 Greenway Drive Suite # 660, Irving, TX 75038

We Help Enterprises Achieve Their Transformation Goals

Request a callback

Saxon AI

Address:  1320 Greenway Drive Suite # 660, Irving, TX 75038 United States.
Phone: +1 972 550 9346
Mail: info@saxon.ai

Sija Kuttan

Sija Kuttan

Vice President - Sales

Sija.V. K is a distinguished sales leader with a remarkable journey that spans over 15 years across diverse industries. Her expertise is a fusion of capital expenditure (CAPEX) machinery sales and the intricacies of cybersecurity.

Currently serving as the Vice President of Sales at Saxon AI, Sija adeptly navigates market dynamics, client acquisition, and channel management. Her distinguished track record of nurturing strong relationships, leading diverse teams, and driving growth underscores her as an adaptable and seasoned sales professional.

Gopi Kandukuri

Gopi Kandukuri

Chief Executive Officer

Gopi is the President and CEO of Saxon Inc since its inception and is responsible for the overall leadership, strategy, and management of the Company. As a true visionary, Gopi is quick to spot the next-generation technology trends and navigate the organization to build centers of excellence.

As a digital leader responsible for driving company growth and ROI, he believes in a business strategy built upon continuous innovation, investment in core capabilities, and a unique partner ecosystem. Gopi has served as founding member and 2018 President of ITServe, a non-profit organization of all mid-sized IT Services organization in US.

Vineesha Karri

Vineesha Karri

Associate Director - Marketing

Meet Vineesha Karri, the driving force behind our marketing endeavors. With over 12+ years of experience and a robust background in the B2B landscape across the US, EMEA, and APAC regions, she is pivotal in setting up high-performance marketing teams that drive business growth through a transformation based on new-age marketing practice.

Beyond her extensive experience driving business success across Digital, Data, AI, and Automation technologies, Vineesha’s diverse skill set shines as she collaborates with varied stakeholders across hierarchies, cultivating a harmonious and results-driven workspace.

Sridevi Edupuganti

Sridevi Edupuganti

Vice President – Cloud Solutions

Sridevi Edupuganti is an innovative leader known for strategically enhancing business opportunities through technology planning, orchestrating roadmaps, and guiding technology architecture choices. With a rich career spanning over two decades as a Senior Business and Technology Executive, she has driven teams to empower customers for digital transformation.

Her leadership fosters democratized digital experiences across enterprises. She has successfully expanded service portfolios globally, including major roles at Microsoft, NTT Data, Tech Mahindra. Proficient in diverse database technologies and Cloud platforms (AWS, Azure), she excels in operational excellence. Beyond her professional achievements, Sridevi also serves as a Health & Wellness coach, impacting IT professionals positively through engaging sessions.

Joel Jolly

Joel Jolly

Vice President – Technology

Joel has over 18 years of diverse global experience and multiple leadership assignments across Big 4 consulting, IT services and product engineering. He has distinguished himself by providing strategic vision and leadership for solving common industry problems on cutting-edge technologies.

As a leader surfacing and operationalizing next-generation ideas, he was responsible for exploring new technology directions, articulating a long-term technical vision, developing effective engineering processes, partnering with key stakeholders to build a strong internal and external brand and recruiting, mentoring, and growing great talent.

Haricharan Mylaraiah

Haricharan Mylaraiah

Senior Vice President - Strategy, Offerings & Sales Enablement

Hari is a Digital Marketer and Digital transformation specialist. He is adept at cultivating strong executive and customer relationships, utilizing data across all interactions (customers, employees, services, products) to lead cross-functionally as a strategic thought partner to install discipline, process, and methodology into a scalable company-wide customer-centric model.

He has 18+ years experience in Customer Acquisition, Product Strategy, Sales & Pre-Sales Management, Customer Success, Operations Management He is a Mechanical Engineering Graduate with MBA in International Business and Information Technology.