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The increasing use of smarter industrial machines necessitates smarter technologies. Raviteja Valluri, Founder and CEO, Minto.ai, and Surya Penmetsa, Founder and idea stage investor, Minto.ai, noticed that 93% of breakdowns in rotating electrical equipment in manufacturing plants are random in nature and most critical equipment in plants is old. This makes it difficult to predict faults that lead to breakdowns and unplanned downtime, negatively impacting a company’s revenue and profitability.

Available solutions are not effective, efficient, and scalable to monitor the health of the industrial motors and drive trains. Most available technologies can only diagnose limited fault modes and do not give system-level insights. Battery-powered sensors also pose a problem: compromising technology effectiveness for the battery life.

IoT sensors need to be installed on the machine at multiple locations across the drive train. But this type of setup causes disruptions in continuous monitoring and data capture, due to weather conditions and hazardous environments.

Raviteja says this led the duo to start thinking of building a solution around these challenges, adding that his work at construction and manufacturing companies revealed that unavailability of digital technologies for real-time monitoring and insights on critical assets leads to low productivity of manpower, impacts professional growth, and promotes reactive culture instead of preventive.

“More than anything, the lack of real-time monitoring technology makes disruptions to operations a constant challenge. This experience drove me towards building real-time intelligent systems to monitor critical assets. The tailwinds of Industry 4.0 helped us to start building Minto.ai at the right time,” he says.

Climbing up the ladder with spidersense™

The team introduced spidersense™, an industrial IoT platform that enables maintenance engineers at the shop floor to monitor the health of their machines and detect 80% faults as much as five months in advance.

The platform comes with an in-built IoT device, iHz™, an edge intelligent design that doesn’t need access to the machine’s location and can be installed inside the MCC panel in the control room. It monitors the real-time condition of legacy rotating equipment with IoT devices and sensors. spidersense™ let’s maintenance engineers know the primary fault in their machines in just five minutes.

“We started building the product in early 2018 and did the first installation as a pilot at a metals manufacturing plant in 2019. The technology digitised machines within minutes and clients started receiving real-time alerts on the health of the machine. But convincing the shop-floor team became a huge challenge. They couldn’t believe this technology could diagnose mechanical faults without even going near the machine,” Raviteja explains. 

The team went to the plant, gave detailed presentations, conducted workshops, and had to prove their product repeatedly with multiple incidents. Their client was soon convinced and Minto.ai scaled up their platform to many plants of the client.

“We saved more than 1,200 hours of downtime for the client by diagnosing more than 120 faults in the last three years,” he says. 

The spidersense™ impact

Currently, spidersense™ has been installed across steel and chemical plants of major companies such as Steel Authority of India, TATA Steel Long Products, CK Birla Group, Patil Group and others.

The company’s success is rooted in the impact the technology makes. A recent example was a metal factory facing a number of challenges. Before implementing spidersense™, the company had a preventive-based maintenance programme along with a run-to-failure maintenance, which involved performing physical checks for machines in the plant for any signs of failure. This was manual-labour intensive and time consuming. The company had difficulty in prioritising the maintenance as there was no way to know the fault precisely and find the root cause. This led to a number of breakdowns at their plants and subsequent production losses.

spidersense™ enabled maintenance engineers at the plant to monitor health of the machines in real time, along with faults developing at component level, helping them prioritise maintenance. The platform also provided the ability to monitor health and operational parameters of the machine, which helped triangulate the root cause of a fault.

In one instance, the platform not only diagnosed a gear chip failure and input shaft key-way damage in the gearbox but also found the root cause: overloading of the machine at specific time periods on a daily basis. The production team was quickly alerted.

Post the implementation of spidersense™ and the early diagnosis of mechanical and electrical faults, total breakdowns in the plant reduced by 80% and 1,200 hours of total downtime were prevented. 

Plans for the future

Raviteja claims the team is poised to offer its industrial IoT platform to process manufacturing plants across the globe. By March 2024, it had plans to monitor more than 5500 machines across the globe in the manufacturing sector.

“We are also exploring opportunities to expand our product offerings to help industries save energy. We are in talks with OEMs to offer our product as a part of their service to their end customers. The expertise we built is enabling us to expand our Industry 4.0 platform to not only manufacturing but also to energy, mobility, and utilities,” Raviteja says.

About Community Voices

Community Voices is a series of articles from the Plugin Alliance that spotlights solutions and startups helping India’s manufacturing and supply chain industries benefit from smart technology. The series leads into Innovent 4.0, an exclusive industry technology conclave from the Plugin Alliance — a first-of-its-kind Industry 4.0 alliance in India — with the aim to showcase India’s role in the Fourth Industrial Revolution. In tune with the event, the series will continue to highlight stories from Industry 4.0 startups.