MRO – AN INFO SYSTEM APPROACH

BY LT GEN (DR) ANIL KAPOOR AVSM, VSM (Retired)

Introduction

1.   The new technology world order is defined by 4Ds – Data, Digitization, Digitalization and Disruption. This has propelled into a tenacious spiral of digital transformation, which in the continuum of time is revolutionising our lives at an unprecedented pace. In the disrupted world, data is the new oil and technology the new oil rig to configure an info system changing the business practices.  Given the emerging technologies landscape, there is a huge opportunity to indulge in creative problem solvers and  exploit the power of technology and innovation.

2.       Maintenance, Repair and Overhaul (MRO) has existed as a necessity for enhancing reliability and availability of equipment with periodic and preventive maintenance (PPM) being a best practice, specially in the Armed Forces. Maintenance and major repair interventions have been carried out as a standard operating procedure and a drill at various echelons from the user garage to major workshops based on n pre-defined time bound preventive interventions. The underlying thought process has been that most of the equipment in peace time is not exploited and hence, units have to be prepared for any operational eventuality, which calls for PPM.  The moot questions are – Is Periodic Preventive Maintenance an optimum MRO practice?  Is breakdown repair an optimum MRO practice ? These questions, in effect, are the maintenance professionals paradox. This paper will attempt to analyse and unravel  the paradox.

3.  An Analogy.  A equipment major intervention program reads – This tank will undergo a medium reset after 15 years  (vintage) or 5000 kms (exploitation) and an overhaul at 25 years or 10000 kms, whichever is earlier. The user is conscious and so is the maintenance echelon to carry out the life  enhancement intervention.  Now, envision an excerpt in the soldier medical intervention program – An Officer would undergo a heart bypass at 40 years of age or in the rank of a Brigadier and an open heart surgery at 50 years or in the rank of Maj Gen whichever is earlier.  But this bizarre – so say all of us.

There is a good reason – humans can express and hence, medical interventions are condition based and symptomatic. The equipment is mute and hence, undergoes over maintenance based on policies which can be questioned – why should an equipment which has turned 15 years with 2000 kms be given the same treatment as the one 15 years with 5000 kms?  Practice indicates that in some cases, the OEM supplied components or spare parts which may not have completed their useful life replaced by locally purchased stores actually create a weakness in the system which becomes start of a continuum of future faults and failures adversely affecting reliability.  There is a case for condition based monitoring and maintenance.

MRO – The Journey

4.  Generation of Equipment.  The Armed Forces have at least three generations of equipment – Gen X (1965 -80), Y (1981-94) which are near obsolete, Gen Z (1996-2010) and Gen Alpha (2011-25). Condition based monitoring and maintenance (CBMM) is the need of the hour.  The technology stack comprising IoT, smart sensors, decentralised control systems (DCS), supervised control and data acquisition systems (SCADA), AR, VR, wearables, big data analytics, AI, 5G etc based ICT systems are part of the Gen Z and Alpha systems. It is the Gen X, Y and Z equipment which need to be CBMM compliant.  CBMM is the NextGen Predictive Maintenance.

5. The Industrial Revolution.   The First Industrial Revolution used water and steam power to mechanize production. The Second used electric power to create mass production. The Third used electronics and information technology to automate production. Now the Fourth Industrial Revolution is building on the digital revolution that has been occurring since Y2K. It is characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. These revolutions have been instep with the technological evolution. Industry 4.0 & 5.0 are but a manifestation of this spiral driven by four Ds, where precision and accuracy in manufacturing and bulk production is today the driving force. We are packaging a lot of technology in too little a space like they say multiple techs into micros making equipment a flotilla of technologies and maintenance and repair a challenging proposition.

6. The Technology Evolution. The technology evolution has been the game changer in the equipment management through generations of equipment. The Moore’s Law which defined the level of system engineering complexity of electronics integrated circuits has been superseded by the ICT revolution and disruptive technologies over the generations of equipment. Of course, inherent in all these, Gen X onwards, escalations has been resultant more stable systems with better technologies, reduced system engineering complexities, higher reliability and the fact that all mechanical, hydraulic or hybrid systems have embedded electronics for higher operational & system level visibility.  A quick contextual walk through is given below:

(a) Gen X. The valve based systems created bulky hardware systems with relays to create a seek and respond analog system for operations and trouble shooting as it was called for Gen X. The big thud on the drawer trays of circuits would help fix faults due to loose connections in the huge P series radars.  The  carburettors controlling the fuel air mixture of petrol based and air locks of diesel based vehicles was the quintessential skill set to attempt engine problems, as an example, and Vespa scooter would start in case you tilted the scooter 30 degrees from the normal or so and life was simple and interesting, in case skills were perfected.

(b) Gen Y. This was followed by Gen Y with integrated circuits based servo systems which created a open and closed loop digital control systems. There were the interface circuit cards connecting the IO 8255 ICs of the microprocessor mother boards. These systems supported efficient system operations and facilitated maintenance/ repair through built in test equipment (BITE) and test point voltage analysis for fault isolation.

(c) Gen Z. Digital transformation with computer based embedded systems comprising MEMS, VLSI, sensor technology, wired and wireless communication technologies, onboard computers, system application software have resulted into intelligent systems based on automated information systems which aid quick diagnostics, thereby bringing down the down time in Gen Z.

(d) Gen Alpha & Beyond. The technology stack augmented by IoT, AI, cloud computing, cyber, big data analytics have become a part of every system today. There is convergence of ICT, sensors miniaturised embedded hardware, application software and cyber defence as an operational technology is gaining traction. Platform as a service (PaaS), infrastructure as a service (IaaS), software as a service (SaaS), cloud -native desktop as a service (DaaS), ERP solutions both bespoke and customised through enterprise as a service (EaaS) etc have configured an info system of systems which operate within the equipment, link the equipment to equipment and connect the edge to a central info system.

(f) The Medical Analogy.  A medical analogy will reinforce the case for CBMM. A medical examination in the Department of Ophthalmology traditionally for Glaucoma was one of the most challenging and a time consuming hugely  involved process. Worse case by the time glaucoma was confirmed, lot of time had elapsed making treatment difficult. Hence, medication was started in some cases without Glaucoma with its attendant adverse effects. Today, Spectral domain-optical coherence tomography SD-OCT) and OCT angiography is a fast track technology interface to monitor in real time, identify early strains and timely precise treatment is facilitated.

7.  Data Science Based MRO.  The CBBM is a modern, real time  data driven approach to ensure weapon readiness based on KPI analytics. Data is collected from the array of sensors every millisecond , more or less, based on the sensor characteristics. As an example, a commercial SUV today has over 200 data points to monitor, record, process, store the data, selectively display, as per user requirement, transmit data appropriately to central OEM service centres to manage the complete vehicle system based on real time data. Big data analytics is a hugely deployed technology in data management for decision support and info systems. These sensors can be designed and developed based on predefined KPIs for real time systemic functional transparency and scaled up. These sensor Data Base Management Systems (DBMS) help in better visibility and take informed decisions in real time, help the user build confidence in the equipment, avoid over maintenance or otherwise, reduce downtimes, ensure high readiness and reliability, build maintenance and repair schedules based on reliability data. These systems give insights, assess equipment health, reduce failure rates, extend useful life, the control to the end user, given visibility to the maintenance agencies / OEMs, amplified MRO agility and flexibility, facilitated CBMM on a just in time (JIT) model thereby eliminating the just in case PPM. The KPIs of fault frequency analytics and RAMD can been built in to configure an MRO info management and decision support system. In an overall analysis, CBMM builds user confidence, facilitates planning and optimizing maintenance plans, enhances performance, ensures the systems remain fully mission capable by timely interventions at reduced opex and revenue expenditures.

Real Time DBMS for MRO – Managing Legacy & Way Forward

8.    MRO is a challenge characterised by volatility, uncertainty, complexity and ambiguity (VUCA) and a major VUCA challenge. This is further accentuated by technology obsolescence which disturbs the equilibrium of supply chains of legacy system spares and assemblies and hence, sustenance support. The legacy equipment are being managed through periodic, preventive and breakdown maintenance be they armoured fighting vehicles, armament, aircrafts, ships and submarines with the attendant down times and high maintenance costs. A study on Feedback of Repair, Workshop Activity and Reliability Data (FORWARD) was launched. A lot of data was collected from other means but it was experienced that almost 90% of the collected data was never analysed because of the sheer volume of data, dark data  and lack of resources.  There is a case to identify sensor based add on systems to enhance systemic visibility and  facilitating real time DBMS for MRO decision support system for legacy equipment. The intent is to transcend from a probabilistic model of maintenance to a deterministic SMART predictive maintenance model through condition based monitoring and maintenance system.

9. Pre Requisites for CBBM.  Improving legacy equipment reliability requires sensors, instrumentation (to capture near real-time equipment performance info) with monitoring systems (to derive data trends), system of recording, display and storing. Torsion Vibration sensors, magnetic sensors, pressure and temperature sensors among host of others are available to get real time data for highly critical rotating equipment and assets. The advent of Instrumented Internet of Things (IIoT) is now helping these  MRO operations to collect reliability data, analyze and diagnose equipment problems in near real time. Breakthroughs in technology are helping allowing operations to collect data from thousands of assets in minutes and configure a MRO info based decision support system. The legacy equipment in the Armed Forces and others would need a well planned technology strategy for CBMM. The following system engineering requirements are imperative to configure CBMM:

•  Identifying the KPIs to be addressed.
•  Identifying sensor(s)  and instrumentation for each KPI.
•  Micro electro-mechanical systems (MEMS), and the related micromechatronics and microsystems constitute the technology of microscopic devices, particularly those with moving parts. They merge at the nanoscale into nanoelectromechanical systems and nanotechnology and are building blocks for CBMM.
• Wired and wireless communication systems within and external to the equipment.
•  IoT enabled graphical dashboards.
• Hand held and appropriate info system hardware.
• Application software for analytics.
• Central control and reporting maintenance command post.

10.  Tryst with CBMM.   An experiment was done on condition based monitoring systems for AFVs.

• Problem Statement.  A large number of engines appear for major interventions including overhaul.
• Action Taken. It was, indeed, this thought that led to identify the drivers of this frequent failures and address them through best practices on maintenance or reliability enhancement. And this resulted in putting a number of sensors a large number of systems and subjecting the engine to dynamometer tests. A Torsional Vibration Sensor system was deployed for engine system analysis to get cylinder-specific health indicators of their engines such as compression, fuel injection, and bearing condition, health of journal bearings, sleeve bearings, rotor shaft. Trend monitoring via IOT-enabled graphical dashboards facilitated view and analysis of engine condition, bearing health conditions in real time, and pinpoint reasons for emerging faults in the bearings such as inadequate load bearing, improper lubrication, broken rotor bar, air gap eccentricity or misaligned shaft. electromagnetic stresses on the shaft and shaft clearance. A lot of data got picked up. And finally, a torsional vibration sensor system (TVSS) was deployed to assess the life of an engine. 12 engines were subjected to TVSS, eight engines which had just arrived from the Field Army for an overhaul and four post overhaul. Out of these eight, four were genuine and it actually had a major sub system failures but the balance four only needed gaskets and FIP overhaul to get the engine back to its parameters.  Four overhauled engines were quality checked for meaningful quality feedback. The man in the loop was empowered through technology to impart autonomy in decision making. A snapshot of dashboard is given below:

11.  Lessons Learnt & Pay Offs Envisaged.  Given the above business context, there is need to transition from the present practice of planned PPM to CBMM in all plants and equipment. The data based MRO info system fact sheet leading to CBMM and pay offs are as given below:

• Only 18% of failures can be avoided by following a PPM schedule.
• Technology is available to address the balance vital 82% failures.
• Timely corrective action reduces extent of repairs increasing uptime and operational efficiency of plants and equipment.
• Monitoring the real time health of equipment facilitates deployment advantage.
• Extension of running hours enhances productivity by eliminating breakdowns.
• Enhanced reliability.
• Minor repairs on the field possible – A stitch in time saves nine!
• Trending and estimation of residual life is a great advantage in estimation of RAMD.
• Cost savings of up to 50% on spares and manpower.
• Simplified logistics.

Conclusion

11.  CBMM is an idea the time of which has come. In fact, we stand on the brink of a technological revolution that will fundamentally alter not only business processes but also business practices. The scale, scope, and complexity of this digital disruption / transformation will be unprecedented as never experienced. With AI, IOT, MEMS, sensor and communication technologies, the transition to predictive precise maintenance is the new normal. CBMM is disrupting MRO practices in almost every industry globally. The breadth and depth of the technological value addition towards condition monitoring herald the transformation of entire systems of design, development,  production, life cycle sustainment and  system engineering management.

12 Aug 22

Anil Kapoor

Lt Gen (Dr) Anil Kapoor, AVSM, VSM served as Director General Electronics and Mechanical Engineers and Director General Info Systems. A Chartered Engineer, he was awarded the Eminent Engineer Award 2020 by Institution of Engineers. He is a Professor of Practice at IIT Tirupati and also a board member in their Innovation Hub. He writes and speaks on emerging technologies like C7 ISR and AI in many publications and platforms.