Use case type
Intelligent waste management solutions use data and automation to sort, track, route, or process waste more efficiently. They address operational inefficiency, poor recycling outcomes, and the need to reduce environmental impact.
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12
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11 mo
Adoption over time
By case publish month · completed months only
5 cases documented across 37 months (Jul 23 – Jul 26), peaking at 1 in December 2024.
6 earlier cases before Jul 23 not shown
Each column counts every documented case of this type by its publish month, across the full corpus. The in-progress current month is excluded from columns and surfaced separately, and cases published before the charted window are summarized as earlier cases instead of plotted.
Company examples
10 shown from 12 use cases
Michelin aimed to optimize its global profit margin, enhance supply chain resilience, and improve manufacturing operational efficiency under complex global market conditions.
Krones, a leading provider of packaging and bottling systems, partnered with Synopsys to deploy a cutting-edge digital twin framework leveraging Microsoft Azure and NVIDIA Omniverse. Traditional fluid simulation in manufacturing took several hours per run, limiting real-time process optimization and scenario testing. By implementing a GPU-accelerated, cloud-native simulation environment hosted on Azure, Krones reduced simulation runtimes from hours to under 5 minutes.The system integrates Ansys Fluent physics, Omniverse libraries, and Azure AI, resulting in a virtually realized factory floor for real-time scenario comparison and adjustment. Enhanced collaboration is enabled across engineering, operations, and R&D teams, thanks to seamless concurrency and data-driven decision-making capabilities.CADFEM Germany GmbH customized solver settings for Krones’ needs and SoftServe provided system integration for the full deployment on Azure cloud infrastructure.The technical architecture enables scalable digital twins across industries, making sophisticated simulations accessible, which significantly reduces waste, increases resource efficiency, and speeds up product development cycles.Collaboration between Synopsys, NVIDIA, and Microsoft demonstrates how digital transformation can deliver practical, rapid agility to manufacturing operations, ultimately raising productivity to new industry standards.
Tracer, a company based in Sharjah, UAE, in collaboration with Verofax, developed a food waste prevention platform built on Microsoft Azure. The platform integrates smart serialization and traceability technology, offering enterprises a powerful method to improve inventory oversight. The solution connects manufacturers, retailers, and consumers to address the global issue of food waste, benefitting from real-time decision-making and automated enterprise processes. Using Verofax's suite hosted on Azure, the platform guarantees data privacy, seamless integration with Dynamics 365, and operational savings by automating decision points for food nearing expiration.
The Onesait Platform by Minsait utilizes cutting-edge Microsoft technologies to streamline and optimize waste management while contributing to the circular economy. The platform integrates advanced analytics, IoT, digital twins, and machine learning capabilities, with elastic deployment powered by Azure Cloud. A major component of this innovative system is Onesait Recycling, which is designed to address the challenges of inefficient waste collection and processing, offering sophisticated digital tools to monitor, analyze, and boost recycling rates. Additionally, the Onesait Platform fosters a broader value ecosystem by uniting transactional and big data processes under a cohesive integration.
OtherBASF, in collaboration with partners Endress+Hauser, TechnoCompound, and various German universities, launched an advanced initiative to optimize mechanical recycling of plastics using artificial intelligence. By integrating spectroscopic methods with AI models, plastic waste composition can now be identified in real-time, improving the quality and efficiency of recycling processes. This project, funded partly by Germany's Federal Ministry of Education and Research, aims to address significant challenges in the consistency of recycled plastic output and contribute to sustainability in the circular economy.
Anheuser-Busch InBev (AB InBev), the world's largest brewer, undertook a large-scale digital transformation initiative to modernize its global brewing and packaging operations. By implementing AI-powered predictive maintenance, Azure Digital Twins for real-time monitoring, and Microsoft Project Bonsai for deep reinforcement learning, AB InBev aimed to create a digital factory environment. This transformation enabled real-time visibility into complex brewery processes, seamless remote collaboration for frontline workers, and optimized packaging lines. The digital technologies also contributed to enhanced product quality, improved operational efficiency, and supported AB InBev's ambitious sustainability goals. The shift included a change management focus to ensure workforce readiness for new technologies and processes. Azure AI solutions made possible a 100% uptime mindset, ultimately redefining the brewery's operational standards.
A collaborative project in southern Sweden established a Waste Identification Testbed using AI-powered sensors and robotics to automatically identify and sort recyclable materials in industrial waste streams. Led by Innovation Skåne and Mobile Heights, and supported by Microsoft Datacenter Community Development, the testbed allows engineers to test sensors and improve accuracy and speed in real-life waste environments. This has resulted in technology innovations, such as deploying the world’s fastest camera sensor for material detection and advanced AI algorithms for instance segmentation to distinguish overlapping materials. The initiative aims to support a circular economy in Sweden by enhancing recycling rates, resource recovery, and operational efficiency, with prospective applications in more complex sectors such as hospital waste. The innovations catalyzed by this project lay the groundwork for industry-wide adoption of improved automated recycling solutions, contributing to a more sustainable future.
OOCL, a global shipping and logistics company based in Hong Kong, faced persistent challenges related to traffic disruption, container equipment management, and operational efficiency across its worldwide vessel network.By leveraging Microsoft Azure and AI solutions, OOCL implemented advanced technologies for traffic disruption detection and improved visibility into global vessel and terminal congestion.OOCL deployed AI-enabled Robo-Advisors for route and resource optimization, allowing them to automate route planning, equipment management, and detection of damaged containers.The company streamlined its repair approval process and minimized unnecessary container repositioning using predictive analytics provided by Azure AI solutions.This tech-driven transformation resulted in more efficient container utilization and improved predictive capabilities for vessel routing and port operations.Overall, OOCL increased operational efficiency and reduced logistics costs by using Microsoft AI to automate and optimize critical elements of their global supply chain.
Astellas Pharma in Japan transformed its IT core platform by migrating global operations onto a cloud-based system, powered by Microsoft Azure and SAP S/4HANA, with Accenture as the implementation partner. The new platform integrates data across supply chain, HR, and finance for a single unified view, supporting business agility and rapid responses to market changes. AI, robotic process automation, and analytics are leveraged to automate and optimize enterprise operations. Astellas can now simulate organizational processes using an enterprise digital twin, enabling advanced modeling, risk analysis, and improved decision-making. The solution accelerates research and drug discovery processes, allowing employees to prioritize high-value work while optimizing administrative costs. The project demonstrates a real-world application of AI-enabled digital transformation in the pharmaceutical sector, with a focus on business continuity, enterprise agility, and innovation on a global scale.
The National University of Singapore (NUS) undertook an ambitious project to refresh its aging campus infrastructure, which includes 260 buildings with disparate standalone systems. Facing challenges in interoperability among legacy technologies—ranging from air conditioning to fire protection—NUS partnered with Microsoft and Johnson Controls to create a unified smart campus. After a fact-finding tour of Microsoft's own modernized Redmond campus, NUS deployed Microsoft Azure Digital Twins as the digital backbone, integrating with Johnson Controls’ OpenBlue cloud platform. This system creates real-time operational models, allowing for predictive maintenance, automation, and sustainability simulations. University staff have received specialized training for ongoing digital transformation. The initiative aims to make the campus carbon neutral and reduce ambient temperatures, leveraging AI, IoT, and data visualization through Power BI. Early impacts include improved energy management and data-driven planning for future campus enhancements.
Common questions
