Symphony AzimaAI helps manufacturers save millions in operational downtime with Azure IoT and Machine Learning
Case in point: Nuvoco
At a glance
Focus: Symphony AzimaAI helps manufacturers save millions in operational downtime with Azure IoT and Machine learning
Challenge: Manufacturers have a wealth of operational data, but many find it challenging to use advanced analytics to turn their data into insights that improve decision making
Approach: Symphony AzimaAI applied its expertise in manufacturing and data science to build the Asset 360 AI and Process 360 AI predictive
Impact: Nuvoco, one of the largest cement manufacturers in India, partnered with Symphony AzimaAI to optimize its vertical roller mill (VRM) grinding units?a critical component of a cement plant?with…
Microsoft India
Overview
Symphony AzimaAI provides operational and process solutions for asset-intensive industries, including oil and gas, chemicals, metals and mining, and pulp and paper. The organization applies industry domain and data science expertise to develop AI and machine learning solutions that help clients optimize operations and grow their business.
Business challenge
Manufacturers have a wealth of operational data, but many find it challenging to use advanced analytics to turn their data into insights that improve operations. Symphony AzimaAI estimates that most industrial companies use only 5 percent of the data they collect. As a result, they’re more likely to suffer operational losses and downtime than if they took advantage of AI and machine learning solutions.
Industry 4.0 solution
Symphony AzimaAI applied its expertise in manufacturing and data science to build the Asset 360 AI and Process 360 AI predictive solutions. Asset 360 AI predicts equipment failures and degradations, while Process 360 AI analyzes and evaluates scenarios that can lead to process trips. Combined, these solutions give manufacturers a simple way to visualize, analyze, and optimize equipment performance and manufacturing processes.
The solutions are built on Microsoft Azure, using Azure IoT and other Azure services. Edge devices run Azure Edge agent and Azure IoT Edge hub for secure data and device management. Raw data is temporarily stored in Azure IoT Edge hub before it’s written to permanent storage on Azure VMs. The Azure Event hub caches storage for real-time alerts or visualization requirements, and security and stability features within Azure help to ensure the platforms are reliable and secure.
“Why Microsoft? One reason is the technical capabilities within Azure. The second is that we felt Microsoft is ahead of cloud competitors, in terms of the enterprise space,” notes Hari Menon, Chief Strategy Officer at Symphony AzimaAI.
Symphony AzimaAI uses Microsoft Azure Machine Learning to develop models that anticipate where and when equipment failures and process trips are likely to occur, preventing unplanned downtime and reducing maintenance expenditures. The analysis helps to enhance manufactured product quality and reduce process inefficiencies by identifying equipment and process irregularities.
“Microsoft is providing all of the cloud and software capabilities, and we’re creating pre-built solutions that allow you to jumpstart the digital transformation journey,” says Menon. “Microsoft has a better understanding of the use cases that we go after, and they’ve been providing software for industrial controls and industrial automation.”
To accelerate time to value, the company built a large equipment and process template library that enables manufacturers to quickly tailor and implement solutions regardless of their data science expertise.
Business outcomes
Nuvoco, one of the largest cement manufacturers in India, partnered with Symphony AzimaAI to optimize its vertical roller mill (VRM) grinding units?a critical component of a cement plant?with predictive advisory services that help increase production yields. Powered by Symphony AzimaAI predictive models and soft sensors, Nuvoco can realize a throughput increase of over 2 percent with a lowered power usage in excess of 5 percent, which results in an incremental million-dollar output over a three- to four-year period per plant.
Symphony AzimaAI is building out its predictive equipment model template library by developing additional models that help optimize operations and reduce production losses. The company is broadening its scope into industries like cement and glass manufacturing, helping more companies start their digital transformation and reach a new level of operational excellence.