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Artificial Intelligence: Powering the Next Wave of MRF Efficiency and Productivity

November 5, 2020

By Rob Writz, Director of Business Development, AMP Robotics

AMP Robotics is sponsoring the MRF Summit session, “Improve Efficiency and Productivity Through Technology,” on Wednesday, November 18 at 3:15 p.m. EST. Ahead of the event, read on as Rob Writz describes the significant and growing role of AI. To register for the MRF Summit and hear more from Rob Writz and others on this topic, please visit

It’s been only a few years since robots first made inroads into recycling, and the impact they’re having on the productivity and efficiency of materials recovery facilities (MRFs) is evident. They’re addressing many of the central challenges the industry faces, from worker safety and bale purity to labor shortages and lowering the overall cost of recycling. And in a year upended by COVID-19, artificial intelligence (AI) and robotics technology have helped recycling businesses weather the challenges of the pandemic and be resilient as the importance of recycled materials as feedstock for our supply chain came sharply into focus.

As we look to the future, it’s AI that offers great potential to continue to transform recycling, delivering more value to MRFs and beyond. Robots are one application of AMP’s core AI technology today; each robot leverages AI to digitize the objects that pass by on a conveyor belt. Looking for specific colors, shapes, textures, logos, and more to recognize patterns correlated with material type, the platform learns to identify objects in the same way a human does. The software understands the heterogeneity, value, and contamination in solid waste streams. It grows smarter and more effective over time as our fleet of AI-guided robots expands. This is material intelligence—a new category of information.

The power of AI as a tool for boosting productivity and efficiency is still in its early stages, and we’re working with innovative customers like GFL Environmental on new product development efforts. We’ve been successfully beta testing solutions that will help the industry take advantage of this burgeoning potential. These are products that will further integrate AI and data into a MRF, allowing operators to do things like graphically compare material stream data to historical baselines, define material count thresholds and create alerts triggered by movement above or below these thresholds, export data for further analysis and integration into business intelligence platforms, and more. This is all intended to deliver real-time monitoring and analysis of material composition as it flows through a facility, providing visibility into and feedback about material streams. With data and tangible metrics, operators can get ahead of mechanical or configuration-based issues and communicate with business partners or key staff in the facility.

You can’t manage what you can’t measure, and the industry recognizes this. At last month’s MRF Operators Forum, Casella Resources’ Bob Cappadona pointed to the tremendous value associated with the reporting capabilities of new technologies that can quickly identify the product mix of an incoming stream, and Balcones’ Joaquin Mariel highlighted how the entrance of AI and robotics allows an operator to make split-second adjustments based on data and feedback. At Waste Expo a few weeks earlier, while discussing the benefits AI has already brought to his facility, GFL Enviornmental’s Brent Hildebrand explained, “We will see greater proliferation of AI, bringing transparency to material and trends and enabling thoughtful, intelligent business decisions at every stage of an operation.”

As we continue to listen to and partner with the industry, we’re focused on enabling action based on data. The continuous improvement of our software infrastructure enhances these data-based capabilities. We’re regularly adding new categories of material for identification. For example, Keurig Dr. Pepper (KDP) converted the material used in the container of its K-Cup coffee pods to polypropylene, a sought-after plastic for recycled materials, and worked with AMP to ensure proper identification of these #5 pods so they can be extracted from the recycling stream and properly processed. GFL Environmental in Denver now accepts emptied coffee pods via curbside recycling and processes them in its single-stream recycling line. This precise identification and continued addition of subcategories is meeting market needs for a higher-quality end product that isn’t contaminated by other materials, and a larger volume of recycled material that can be turned back into new packaging. It represents an expansion of AI’s role as the engine behind highly effective picks to one that can recount everything it saw.

The technology is coming, and we have seen this evolution in other industries with “material” flow, including electricity, wastewater, and water utilities. Each developed and deployed a form of meter to cost effectively count the movement of its “material,” then deployed various efficiencies to become “smart utilities.” As its sophistication and value grows, the AI technology powering robots can become the material flow meter for recycling, helping operators understand not just the what, but the why, behind changes in the material they’re processing. Today’s MRF will evolve from material hubs into information hubs. As we extend our efforts to deploy technology that shifts the economics of the industry and grows the circular economy, further embrace of AI and the data and insights it yields will keep the industry moving forward.

To register for the MRF Summit and hear more from Rob Writz and others on this topic, please visit

About the Speaker

Rob Writz is director of business development for AMP Robotics, a pioneer and leader in artificial intelligence (AI) and robotics for the recycling industry. His professional career has focused on the intersection of software with smart cities and the circular economy. Before joining AMP Robotics in 2016, Mr. Writz was a product manager for Intrado (acquired by West), and his teams developed the core location technology for mobile 9-1-1. He worked in technology commercialization at The Department of Energy’s National Renewable Energy Laboratory, and led the Cleantech Practice at Innosphere, Colorado’s seed fund and incubator for science-based startups.

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