Industrial Automation Magazine India

Indian railways are adopting a board condition monitoring system

Published on : Friday 07-10-2022

Sureshbabu Chigurupalli, Board Member-Director, Balasore Alloys Ltd.

Condition monitoring is widely used to ascertain the health of machinery, equipment, vehicles, and other valuable assets. It provides crucial information that ensures equipment is operating at optimum efficiency, minimising downtime, and reducing defects. Condition monitoring has been useful for understanding historical performance and status of equipment, but it does not do a great job of preventing or mitigating potential downtime.
 
There are two broad techniques in condition monitoring – condition checking and monitoring changes in performance over time. Condition checking assesses the state of a machine at a specific moment in time and takes a performance snapshot, from which to derive its current operational health. These snapshots are evaluated over time through trend monitoring to identify patterns in various performance indicators based on handheld sensors.
 
Changes in performance mapped over time enable manufacturers to uncover any possible machine degradation, down to which components might be wearing out, and how urgently they need servicing. If cross-referenced against other data – such as new process roll-outs, or a new staff cohort—it may be possible to pinpoint out-of-spec production to causes outside of component deterioration. The challenge with this type of monitoring is it won’t guarantee you detect performance issues before it results in downtime.
 
Assets/Machines are the core strength of any manufacturing industry. Asset Condition Monitoring is a technique to measure the machine usage and performance to predict the maintenance cycle. Asset condition monitoring can be achieved by connecting machines and by deploying internet-enabled sensors or IoT connectors that facilitate data collection and transfer of machine data to the cloud platform for further analysis to monitor and schedule maintenance. As part of Industry 4.0 technologies, IoT facilitates the real-time monitoring of asset conditions and performance without human efforts.
 
Asset Condition Monitoring is the process of monitoring each parameter of conditions in equipment or machines to identify a notable change that is indicative of developing a possible failure. It helps to identify machines’ run-time and downtime status, maintenance status, and health based on a few specific parameters like vibration, noise, fuel requirement, temperature, etc. It monitors all the possible parameters that are required to keep a machine in a better condition. Asset condition monitoring plays a key role in predictive and preventive maintenance. Implementing ACM allows scheduling maintenance and preventive actions to avoid failure and subsequent unplanned downtime. The systematic approach to tracking and monitoring the physical assets across large industries from acquisition through to disposal is also known as Enterprise Asset Management (EAM). Industry 4.0 enables plant managers, factory engineers, and other users to monitor the asset condition remotely. Hence this helps to quickly respond to the changing conditions and operational trends and improve forecasting to maximise the performance and efficiency of a larger system.
 
Condition monitoring is commonly understood to apply to rotating machinery. What other assets in the plant can benefit from condition monitoring?
Condition monitoring is an essential part of predictive maintenance that allows maintenance actions to plan to avoid failures and their consequences. It is an approach that predicts machine health and safety by combining machine sensor data that measures vibration and other parameters (in real-time) with state-of-the-art machine monitoring software.
 
Assets and equipment ‘communicate’ and alert monitors to a problem through signals such as vibration, sound, higher than average temperatures, etc. Condition monitoring reads these ‘communications’ and tracks, projects, and measures asset health. 
 
When the health of an asset begins to deteriorate and the potential for failure begins, this is when condition monitoring helps to remedy the issue quickly. It uses sensor devices to collect real-time data and measurements of an asset – allows maintenance personnel to perform the required work at the precise moment it is needed, and completely avoids asset failure.
 
Most types of condition monitoring analysis for asset health are non-invasive, meaning maintenance specialists do not have to go into the machine's moving parts to figure out the problem. Instead, they utilise various measurements, including performance data, visual inspection, and scheduled test results.
 
There are many other sophisticated assets in the plant which can benefit from condition monitoring, i.e., furnace shells, electrical equipment (panels, switchyard equipment, transformer, etc).
 
Condition monitoring techniques include:
• Temperature/infrared monitoring
• Radiation analysis
• Acoustic/ultrasonic analysis
• Oil analysis, and
• Electromagnetic monitoring.
 
What is an estimate of the size of the market? How much of this market is accessible to Indian companies?
The global machine condition monitoring market size reached US$ 2.4 bn in 2021. Looking forward, the market is predicted to reach US$ 3.6 bn by 2027, exhibiting a growth rate (CAGR) of 7% during 2022-2027. 
 
Increasing digitisation, along with significant growth in the oil and gas, automotive, defense, aerospace, manufacturing, food and beverage and marine industries, is one of the key factors creating a positive outlook for the market. Additionally, various technological advancements, such as the utilisation of secure cloud computing platforms, wireless technologies and the integration with the Internet of Things (IoT), are acting as other major growth-inducing factors. Furthermore, increasing awareness regarding preventive maintenance among the masses is also driving the market growth.
 
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?
The potential benefits of condition monitoring to Micro, Small and Medium Enterprises (MSMEs) and startups are variedly known. It can enhance MSMEs' efficiency, reduce costs and expand market reach at the domestic and international levels. As the MSME sector plays a vital role in the nation's economy, the industry benefits individual MSMEs collectively rendering positive results, leading to employment creation, revenue generation and overall country's business competitiveness.
 
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?
More recently, there have been increasing references to digital twins. It creates a physical asset replica by combining simulation models, IoT sensors, time series data and maintenance records to build a picture of an asset and its current operating condition. Digital twins can make a massive difference in helping the manufacturing industries by turning data into a competitive advantage. One can select specific product lines instead of the entire process to create a digital replica to eliminate variability, defects or inefficiencies. Digital twins hype has reached its peak. Now is the time for organisations to take a step back and understand what these technologies can achieve in-depth. When one looks at an asset in isolation, which is the definition of a pilot project, one will likely see some good results. However, the algorithms are based on one asset and related sensor data. When you try to scale hundreds or thousands of similar assets, the problem is. The predictions you created are specific to the asset in the original pilot project. Applying these predictions to other assets could lead to many issues, resulting in unforeseen failure (e.g., two similar product lines might have different electrics and different manufacturers and different characteristics; one may last longer and one may fail early). The collaborations between vendors and buyers shall continue at each stage to develop a robust control strategy capable of dealing with the vast array of possible scenarios that can occur on site. Use IoT sensors and data compared against an individual asset’s configuration, not the generalisation of all ‘like’ assets; doing the latter will result in weak results.
 
Is the appetite for such systems bigger at large plant operators like power plants and refineries?
Power generation plants are vital, so many major industry leaders are turning to wireless sensors to ensure that they don’t face any unnecessary power cuts and that all major components remain stable. Steam turbines, gas turbines, generators – the list is endless, with each component equally as crucial as the next. Condition monitoring offers businesses and heavy machinery industries the unique opportunity to assess the viability of vital components without needing to schedule routine maintenance checks. This means we can now monitor the condition of our machinery while it stays operating, ensuring that downtime and unnecessary maintenance fees are a thing of the past.
 
The market conditions are indeed challenging for refineries in the 21st century. Fluctuating crude prices, demand ebbs and flows and changing energy costs cut into profit margins. And compliance with tighter environmental and safety regulations can be both difficult and expensive. At the same time, the opportunity to increase profit by refining poorer grade crudes requires machines to run at higher temperatures, putting greater stress on machines. With so much at stake, mechanical assets need to run at or even beyond original design condition or capacity, reliably and predictably. Condition monitoring solutions can help to improve the PQCDSME (Productivity, Quality, Cost, Delivery, Safety, Morale and Environment).
 
Can the government play a role in accelerating deployment of such systems? Are there any schemes for promoting better maintenance using data technologies?
Transportation, health, and defence services are a few areas where the government is deploying condition monitoring. Indian railways are adopting a board condition monitoring system, the fourth-largest rail network in the world, to monitor the condition of tracks, coaches, wagons and locomotives and send an early signal to the control room in case of any deficiency. Micro-analysis of data will help in reducing the possibility of sudden catastrophic failures. This system is used by Railways of the US and UK, while Israel uses it in aircraft and helicopter service. The sensor-based equipment system is fitted on wheels, and the control room will receive signals through vibrations.
 
Does engineering education prepare graduates/post graduates to design, specify, evaluate, and implement such new age solutions?
The modern engineering profession constantly deals with uncertainty. The chalk and talk methods are ineffective due to growing globalisation and continual technological and organisational change in the workplace. 
 
In addition, they must cope with the commercial realities of industrial practice in the modern world and the legal consequences of every professional decision competing and conflict in demands from clients, governments, environmental groups and the general public. It requires skills in human relations, as well as technical competence. While mastery of the technical aspects of engineering must remain at the curriculum’s core, one needs to add new dimensions that will better prepare students for the world of today and tomorrow.
 
Students need exposure to industries to understand concepts through practical demonstrations. Communicate their technical ideas and concepts, galvanising a wide array of people. Effective linkages with concerned sectors are significant to get hands-on experience.
 
Sureshbabu Chigurupalli is on the Board of Directors/Operations & Maintenance/Keynote Speaker/Lean Practitioner/Production Management/TPM Practitioner with 26+ years of experience. He is Director (Operations) at Balasore Alloys Limited, Balasore, Odisha. He did his B.Tech.in Instrumentation from Andhra University (1994). He is an enterprising leader & planner with a strong record of contributions in streamlining operations, invigorating businesses, heightening productivity, systems & procedures. 
 
Sureshbabu has achievement-driven professional experience in spearheading entire unit/ plant operations to maintain continuity and match organisational goals through supervising Operations, Quality Control, Production Goals, Automation, Maintenance, Process Improvements, Safety Guidelines, Manpower Development, New Policy/Procedure Guidelines, Resource Allocation and Cost Optimisations. He is leading and managing all plant operations with effective utilisation of all resources and implementing industry best practices such as TPM, Six Sigma, Lean Management & others Business Excellence initiatives that contribute to improve productivity and efficiency. He has exhibited leadership in closely collaborating with numerous Japanese Consultants for implementing TPM to enhance overall plant effectiveness.
  

(The views expressed in interviews are personal, not necessarily of the organisations represented)