Grantee Research Project Results
Enhanced Efficiency of UBC Recycling Powered by Artificial Intelligence
EPA Contract Number: 68HERC24C0032Title: Enhanced Efficiency of UBC Recycling Powered by Artificial Intelligence
Investigators: Molstad, Emily
Small Business: Valis Insights, Inc.
EPA Contact: Richards, April
Phase: I
Project Period: December 1, 2023 through May 30, 2024
Project Amount: $100,000
RFA: Small Business Innovation Research (SBIR) - Phase I (2024) RFA Text | Recipients Lists
Research Category: Small Business Innovation Research (SBIR)
Description:
VALIS’ long-term vision is to create software tools for the entire recycling value chain from point of collection, to processing, to melting.
Achieving a circular economy requires a systems approach in which the interdependence between upstream and downstream
processes, supply and demand, and policy and design is considered and built into solutions. VALIS aims to be the bridge between
disjoint equipment, processes, and stakeholders along the recycling value chain. VALIS technology will facilitate the sharing and
utilization of data that allows for inter- and intra-plant optimization for the maximized recovery of recyclable materials drive reduction in
greenhouse gases by more than half a gigaton by 2050.
To execute on that vision, VALIS has developed products focused on increasing the sustainability, stability and profitability of metal
recycling. Operational effectiveness and equipment utilization at recycling facilities is limited by human decision making. Process
changes today involve slow feedback cycles between facility stakeholders and are not robust to dynamic trends in material content and
commodity values resulting in operational inefficiencies that lose material and lose money. VALIS is helping recyclers recover those
losses through its flagship product VALI-Sort, a recycling software tool powered by artificial intelligence. VALI-Sort integrates directly
with advanced sensor-based sorters (SBS) to recover valuable material and process data that is otherwise lost at the end of a process
run. VALIS captures this data and relates it to information external to the SBS including operational production data, quality assessment
data, market trends and sales. VALI-Sort leverages proprietary algorithms and AI models to deliver data insights and visualizations such
that recycling facilities can:
• Monitor material flows in real-time and increase inventorying accuracy.
• Access automated process data with minimal human input.
• Observe impact of process changes on material outputs.
• Relate material data back to vendors/material sources enabling data driven procurement.
• Track product quality data, as it relates to material purity or compliance with customer-driven specifications.
• Increase the return on investment associated with sorting equipment.
VALIS has intentionally designed its VALI-Sort product to be system agnostic such that it can tie into a multitude of equipment types, and
existing software tools. This allows recycling facilities to build out a suite of physical equipment and benefit from enhanced data quality
and insights that shortens the equipment payback period. This Phase I effort will support the adaptation of VALI-Sort, which has been
historically focused on supporting automotive shredding and recycling processes, to enhancing UBC recycling operations.
Progress and Final Reports:
SBIR Phase II:
Enhanced Efficiency of UBC Recycling Powered by Artificial IntelligenceThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.