Industrial Automation Magazine India

CBM plays a key role in optimising service intervals without impacting safety

Published on : Friday 07-10-2022

Gangadhar Krishnamoorthy, Associate Partner, KPMG in India.

Condition monitoring is commonly understood to apply to rotating machinery. What other assets in the plant can benefit from condition monitoring?
Rotating machinery is the most common of prime movers that translate rotary motion to various kinds of movements for enabling a machine to perform its functions. However, there are many static assets that constitute an important asset base to be monitored through Condition based Monitoring (CBM), such as transformers used in power distribution, boilers used for steam generation, heat exchangers in various applications, industrial oven or furnaces used for heating, reheating or remelting, many types of high temperature static parts of aero and land gas turbines including stator blades, combustor and turbine casings, solar and wind farms assets to name a few. Then there are assets such as diesel generators, water pumps, air compressors, ventilation fans with motors as the prime mover but with heavy mechanical systems as per the application requirements. The benefits of CBM depends on the kind of industry and asset condition monitoring requirement, and can be extended to monitor fatigue, stress, erosion, corrosion, soot, deposits, wear and tear. The application is clearly a wide gamut and covers both rotating and static machinery.
 
What is an estimate of the size of the market? How much of this market is accessible to Indian companies?
The market for CBM, predictive and prescriptive maintenance exists across all sectors, viz., manufacturing, utilities, mining, infrastructure, agriculture that have usage of assets/machines whose performance drives profitability of operations. These assets are either maintained by the in-house engineers, outsourced AMC contracts, or operated through lease. Any improvement in availability, capacity utilisation and performance is a market opportunity and can be easily valued as such.
 
The aerospace sector can be viewed as a pioneer in adoption and has significantly benefited from CBM. Service and repair costs of each aero gas turbine range approximately from $1 to $5 million.CBM plays a key role in optimising service intervals without impacting safety. Almost all CBM and assessments are performed in-house by aero-engine OEMs; however, these companies rely on support from analytics service providers to provide them better insights. This market is accessible to Indian companies and its size is estimated to be approximately few million dollars per year.
 
Additionally, we believe that vibration based monitoring and cloud deployment services have huge potential under the larger CBM umbrella. This means that companies who have not yet onboarded modern vibration based monitoring systems or have not yet leveraged cloud deployment are a part of the larger market.
 
Condition monitoring and prescriptive analytics is a business activity different from legacy sales and services activities. Do you think MSMEs and startups have an inherent advantage in getting market share?
Each asset or machine is different and unique depending upon the sector in which it is used. The application in the sector use, the criticality of the machine in the industrial value chain, makes it difficult for any one solution provider to address all the assets that exist in the manufacturing industry. A motor used in a conveyor belt for bulk material handling needs to be monitored differently from the way the motor will be monitored for an industrial ventilation fan. 
 
What is required to stitch the solution together is asset knowledge – the parameters to monitor, the performance quotient, the engineering knowledge of the asset behaviour and the sector usage know-how. This includes (the purpose the asset serves, the ambient conditions, the technology landscape to gather data, retrofit sensors, and an understanding of how to manage aid the process in building asset performance intelligence). While we have big platform players in the market, which offer a generic framework, most of the successful players have been the niche players based on the assets and sectors that they have focused on. 
 
Are there real studies done to establish proof of concept using simulation and digital twin techniques? This needs an intensive collaboration between prospective buyers and vendors. Is it happening in India? With what success?
Proof of Concept (PoC) is the basic step to establish that a technology based solution will work in an environment where the asset operates. This could involve an independent initiative by the solution provider or a joint proposition by the buyer and the vendors. There are well established digital twins for critical and high cost assets like a turbine and generator in a power plant, a standalone wind turbine, but these are supplied by the OEMs or asset suppliers. Many analytics service providers have tried to implement pure machine learning models to estimate Remaining Useful Life (RUL) based on past trends. The success of such models has been limited. For high cost assets, studies are focused around developing a hybrid machine learning based on a core  physics based model  and data based statistical models that are more accurate in predicting RUL. Typically, equipment OEMs have collaborated with boutique analytics service providers to develop such hybrid models as PoC.
 
India now is slowly witnessing the adoption of Digital Twin, which is a virtual replica of the asset, its condition and performance. Industries such as Power and Utilities, Chemicals, Metals and Automotive are at forefront of such adoption. For every new technology adoption, collaboration is always desired. Co-creation is helping industry to evolve the knowledge gained by both buyers and vendors.
 
Is the appetite for such systems bigger at large plant operators like power plants and refineries?
Large plants like the power plants and refineries are supplied and built by OEMs who supply the design, operational technology and the machine while building the plant. The CBM systems are part of the plant erection and commissioning packages offered by the OEM. But there exists opportunities for CBM based asset performance management to be tapped into at these power plants and refineries. Today we are seeing many older plants and refineries being retrofitted with sensors to track performance of critical assets and optimise service and repair intervals.
 
Additionally, refineries have their own complexities, owing to oil characteristics, in building and maintaining digital twins. For example, crude Pre-Heat train (PHT) is a classic example where all refineries are interested in getting the most out of the PHT so as to minimise fuel fired in the furnace, but a digital twin that adapts to changing crude basket is not easy to build/maintain which makes traditional ways ineffective. Thus opportunities for modern CBM exist at such refineries. In addition to power plants and refineries, the appetite for CBM systems is significant in industries that have high cost safety critical assets such as aerospace, metro/high speed railways, heavy construction/mining equipment. There is a lot of knowledge gained by large plants and refineries over the years. They are now providing means to spread this knowledge. Condition monitoring methods are also evolving as now we are seeing adoption of drone and robots based inspection and remote monitoring services being offered. 
 
Can the government play a role in accelerating deployment of such systems? Are there any schemes for promoting better maintenance using data technologies?
While upkeep of the asset is the responsibility of the asset owner (public, private or government owned), the government surely can frame policies for governance of asset performance in terms of energy optimisation, GHG or CO2 generation. The other area where the government can guide the industry is to standardise the industry protocols used for data collections, storage, data security and data sharing. There is a need for increased data security norms/laws for which will help in creating awareness. The GHG norms could be made into a law with a revival of Carbon Credits program. Government can also look at bringing policies for increased Public-Private partnership. Lastly, government intervention could ease knowledge dissemination in SMEs though industry associations and incentivise such deployment.
 
Does engineering education prepare graduates/post graduates to design, specify, evaluate, and implement such new age solutions?
Engineering education does prepare a candidate with the basics required to understand and appreciate CBM for any asset. The application of the engineering know-how and matured use would require the candidate to have industrial exposure to understand the usage of the asset in a particular sector and the various conditions of process where the asset is used. Having said that, the education system needs to be augmented with professional courses, which can prepare fresh graduates for the ever changing market. We need to include credits on digital technologies and application of IoT, RPA, Cybersecurity, etc. The Industry-Academia relations are required to be strengthened further to accelerate implementation of new age solutions.  
 
(With inputs and contributions from KPMG in India's Industry X.0 consulting team)
 
Gangadhar Krishnamoorthy is a Business Advisory Consultant with a unique blend of solution design and delivery, business development and pre-sales, technical expertise in shop floor automation and strong manufacturing domain knowledge in providing transformational Digital Engineering solutions towards smart manufacturing (Industrie 4.0) and IIoT.
 
(The views expressed in interviews are personal, not necessarily of the organisations represented)