Industrial Automation Magazine India

Startups born with a Digital-First mindset will make faster strides

Published on : Friday 07-10-2022

Dr Raunak Bhinge, Founder and CEO – Infinite Uptime.

Condition monitoring is commonly understood to apply to rotating machinery. What assets in the plant can benefit from condition monitoring?
Online Condition Monitoring is all about continuous monitoring of the health of critical equipment and types of machinery like gearboxes, kilns, separator fans, crushers, belt conveyors in a cement plant, and similarly cold rolling mills, presses, coke ovens, hot pumps, and exhaust blowers typically found in a steel manufacturing setup. Continuously monitoring these mission-critical applications can lead to signs of significant changes indicating potential failures.

Smart data collection and advanced analytics using online condition monitoring techniques allow plant maintenance and reliability teams to anticipate how an asset may perform over time and take complete control over maintenance schedules thus avoiding unplanned downtimes. As manufacturing leaders realise more value beyond just downtime; the use cases of predictive maintenance methods are becoming widespread across applications and industries.

What is an estimate of the size of the market? How much of this market is accessible to Indian companies?
Experts estimate that the current market size of the Predictive Maintenance (PdM) Industry may be around $4 bn worldwide. However, with the advent of IoT, edge computing, big data, Machine to Machine communications, and business drivers such as reducing the TCO through asset optimisation, the need for operational efficiency, higher plant reliability, and widespread use-cases across industrial applications will catalyse the adoption of PdM. Again, the experts believe we are looking at a potential of $15-18 bn by 2027 which may grow exponentially at a 25-30% CAGR.

From a market accessibility standpoint, factors such as highly matured processes, customer-centric innovation, high-quality services, and scalable and secure infrastructure supported by the right talent and technology will define who takes the larger pie. So, it could be anybody’s game because SaaS and global delivery models make it possible. It is also critical to be objectively aligned with the customer’s vision.

Condition monitoring and prescriptive analytics are business activities different from legacy sales and services activities. Do you think MSMEs and startups have an inherent advantage in getting market share?
Startups born with a Digital-First mindset will make faster strides with an early-mover advantage. As I mentioned earlier, you need to be aligned with the customer’s vision. Startups and MSMEs only with a large appetite to innovate and invest in risk can sustain. Condition monitoring has been around for decades, so it is the delivery model of diagnostics and predictive analytics that has changed – it is now real-time, scalable, accessible from anywhere, and available for all. Startups that can innovate around the delivery model will succeed in this space, as the inherent knowledge of condition monitoring is more or less the same.

Are there real studies done to establish proof of concept using simulation and digital twin techniques? This needs intensive collaboration between prospective buyers and vendors. Is it happening in India? With what success?
Studies indicate that the average cost of downtime may range between $5000-$100,000 per hour. Factories of the future are embracing Industry 4.0 capabilities to implement intelligent and sustainable processes in plant maintenance and save these downtimes. There are real case studies done on gas compressors and turbines where simulation and digital twin techniques have actually created value. Thermodynamic performance simulation combined with real-time data helps plot the real-time performance of thermodynamic cycles and pinpoint problems. Intense collaboration, high engagement, and co-innovation are needed between the vendor and the buyer to make such a digital twin possible. Currently, digital twin technology with successful cases at scale is still in its infancy and will gain traction over the years to come.

Is the appetite for such systems bigger at large plant operators like power plants and refineries?
The appetite is large in asset-intensive industries.

Underperforming critical assets like gas turbines, pumps, heat exchangers, motors, compressors, and many more can wreak havoc in process plants. For example, early detection and prediction of a crack in a turbine rotor can save a power plant from an unexpected breakdown and save a few million in lost production. 

Monitoring a host of assets in the Oil & Gas industry for real-time equipment inspection using industrial IoT and edge analytics cuts maintenance costs and reduces failures. Equipment in oil drilling operates at variable speeds and generates vibrations. This equipment is at the heart of the drilling operation and must be well-maintained. Diagnostics and fault notifications can alert the rig managers in advance before any actual occurrences and losses.

The appetite for predictive maintenance is directly proportional to the cost of downtime. This is why heavy industries like power plants, cement plants, steel plants, and refineries invest heavily in plant reliability and uptime.

Can the government play a role in accelerating the deployment of such systems? Are there any schemes for promoting better maintenance using data technologies?
India is a land of new opportunities and in the last 3 decades, it has transformed into a technology and innovations hub while retaining its status as an emerging global manufacturing destination. Initiatives like Samarth Udyog Bharat 4.0, Atmanirbhar Bharat, MSME Technology Development Centres, and Centre of Excellence for 4th Industrial Revolution initiated by the Government of India along with industry bodies like NASSCOM and CII are catalysing the Industry 4.0 transformation efforts.

However, it’s more than inspiring to see private players like the Vedanta Group enabling startups to create a large-scale impact on business. Vedanta’s ‘Spark- Igniting Future’ is a global corporate innovation program aimed at strategic innovation and digital enterprise-wide transformation leveraging transformative & sustainable technologies.

Does engineering education prepare graduates/postgraduates to design, specify, evaluate, and implement such new-age solutions?
In this digital age, we are experiencing a huge shift in talent development and academia. The All India Council for Technical Education (AICTE) and several premier institutes have synergised their course syllabus with the National Policies of Industry 4.0. Organisations such as the National Productivity Council, Quality Council of India, The National Program on Technology Enhanced Learning (NPTEL), and industry associations such as CII, FICC, and ASSOCHAM have taken this to a new level by developing learning content and promoting the importance of Industry 4.0.

The transformative change to the business environment has created a perfect storm for talent transformation and human resource management prompting a need to explore the implications of this context and we are just at the cusp of it.

Dr Raunak Bhinge is the Founder and CEO of Infinite Uptime, one of the fastest-growing Predictive Maintenance and Plant Reliability solution providers across the globe. For over a decade, Dr Bhinge has been active in the field of smart manufacturing, Industry 4.0, innovation, and applying digital technologies for transforming manufacturing businesses.
 
He completed his post-graduation in Automotive Design and Engineering from IIT Madras, followed by higher studies in Mechanical Engineering at the University of California, Berkeley where he has conferred a Ph.D. He has five patents to his name and owns several high-authority publications in the areas of manufacturing and technology. He is passionate about connected ecosystems, advancements in digitalisation, and sustainable manufacturing. Key areas of business interest include industrial IoT platforms, industrial diagnostics, data science, predictive analytics, and asset maintenance.
 
Dr Raunak Bhinge actively engages in public service as a speaker and mentor. He is also an avid bird watcher and loves exploring the latest innovations in deep-tech.
 
(The views expressed in interviews are personal, not necessarily of the organisations represented)