Transforming Railroad Asset Management: Going Smart with Predictive Maintenance

Transcription

1 Trasformig Railroad Asset Maagemet: Goig Smart with Predictive Maiteace Abstract As oe of the most asset-itesive idustries i the world, the rail idustry ivests early 20% of its reveue i asset maiteace to esure safe operatios. What s more, sigi cat challeges such as spiralig maiteace costs, arrow maiteace widows, o availability of talet for remote coditio moitorig, ad heighteed customer expectatios, plague the idustry. Railroad compaies are therefore movig from the traditioal scheduled maiteace strategies to asset coditio based predictive maiteace to ehace utilizatio, reduce costs ad safeguard the durability of their railway etworks. Predictive maiteace ivolves the deploymet of sesor-based diagostic moitorig i real-time for assets ad sub-systems that provide eough time to act - based o the recorded coditio parameters. The paper discusses how railroad compaies ca use ext-ge digital techologies such as remote sesors, edge computig, IoT platforms ad Big Data aalytics to formulate predictive maiteace strategies. It also highlights the impact of such strategies i drivig sigi cat improvemets i reliability, asset availability, cost ef ciecy, ad customer satisfactio.

2 Why the Rail Idustry is Movig to a Predictive Maiteace Paradigm I this idustry, equipmet failures ca result i fatal cosequeces; uplaed outages ad ureliable operatios ca severely impact reveues as well as customer satisfactio ad safety. Time-based traditioal maiteace strategies fail to capture the exact state of a asset, ad lead to uecessary maiteace ad high operatig costs. Little woder predictive maiteace is a hot butto issue i the rail idustry today. The approach allows users to cotiuously moitor assets, proactively idetify probable defects, ad iitiate ecessary maiteace work before a asset fails, ehacig system availability ad reducig maiteace costs. Sesors placed alog railway tracks or mouted oboard rollig stock help railway compaies remotely capture critical parameters associated with rollig stock as well as xed ifrastructure - i real time. Alog with asset related data, other data like weather ad geographical coditios ca also be captured to eable superior asset maagemet. The data captured across the etwork of sesors is fed ito predictive model, eablig proactive maiteace operatios to elimiate uplaed dowtime of assets. The bee ts do ot ed there. Accurate forecastig of spare parts requiremet through predictive aalytics helps cut dow o their procuremet ad shippig costs. Accurate isights ito mapower requiremets also help drive precise maiteace crew schedulig. Predictive maiteace solutios also play a critical part i supplier cotract egotiatios. They provide relevat data such as warraty iformatio, supplier details, traceability ad demad forecastig, to help railway compaies egotiate the best price, icludig terms ad coditios for the ew cotract. Four Key Igrediets of a Successful Predictive Maiteace Strategy So how ca railroad compaies develop a successful predictive maiteace strategy? Focusig o the followig four areas is critical: Idetify data eeds: Most curret systems i rail orgaizatios are icapable of meetig the data requiremets eeded for predictive maiteace. Oe of the rst steps is to obtai the data required for the solutio

3 developmet process usig a top dow approach. Clearly de ig the busiess objectives allows solutio developers to drill dow ad pipoit the required data. De e the right system requiremets: This is the most crucial step i developig a predictive maiteace solutio. It is importat to de e scope of the solutio, ad idetify busiess critical eeds ad parameters for predictio. A wrog system ca lead to usuccessful outcomes ad limit user co dece. Bled data aalytics with domai expertise: While data scietists help develop predictive algorithms, rail domai expertise is essetial to guide data scietists i buildig the right algorithm aliged with speci c busiess eeds. Create a eviromet for value-additio: The scope of a predictive maagemet solutio goes beyod predictig failures to predictig several busiess scearios, deployig suitable prescriptive actios ad improvig maiteace related performace idicators. These iclude suggestig the ext maiteace activity, just-i-time ivetory plaig for replacemet of parts, idetifyig systems that eed a upgrade i their desig due to their cotiued poor performace, ad so o. The Role of Digital Techologies i developig Smart Maiteace Strategies It's clear that adoptig relevat emergig techologies such as sesors help achieve ew levels of success ad ef ciecy across the rail idustry usig predictive maiteace strategies. But with the sesor data volumes growig pheomeally over time, data maagemet ad aalysis eeds are growig. To tur this eormous data ito actioable isights, major railroad compaies are turig to cloud-based IoT ad Big Data techologies. Big Data aalytics ca help coect the dots across the etire rail etwork such as rails, bridges, statios, ad so o. It eables compaies to develop predictive algorithms from heterogeeous data sources, realtime commuicatios, ad scalable data structures. The result: rapid isights from disparate sources of iformatio to help improve asset availability ad service levels, reduce service delays due to uplaed outages, ad implemet smarter maiteace strategies.

4 Uderstadig the Roadblocks Despite the promise of predictive maiteace strategies, may rail orgaizatios cotiue to delay ivestig i them. The reaso: it is dif cult to shift from traditioal, scheduled maiteace to a predictive model i oe leap. Nature of maiteace practices, resources, as well as geographic ad weather coditios vary from regio to regio, as a result of which trais ad etworks are desiged ad developed to meet speci c requiremets a major barrier to the adoptio of predictive maiteace. Additioal challeges iclude: Developig co dece i the predictios: Rail compaies that are i the iitial stages of IoT implemetatio are facig the challege of false alarms. To mitigate this, alog with accurate predictive algorithms, it is ecessary to icorporate oise correctio methods. Meetig regulatory compliace demads: Safety is paramout to railway trasportatio, leadig to regulatory costraits o the asset maiteace ad certi catio procedures. Developig the required tool kit ad desired skill set: Predictive maiteace requires the deploymet of latest techologies, makig it dif cult to create large scale skill sets i ew techologies withi the orgaizatio. Similarly, it is also importat to develop the ecessary skills to uderstad the predictios ad historical data ad correlate the facts to drive accurate asset status, what-if aalysis, ad improved decisios. Need for large capital outlays: Railways typically deal with a large asset base that operates i harsh operatioal coditios. Migratig large scale operatios from traditioal to predictive maiteace demads huge ivestmets i terms of time, moey, ad techology alog with meticulous plaig. Deployig Next-ge IoT Platform-based Predictive Maiteace A software that ca predict failures ad trigger maiteace work ows ad itervetios eeds extesive access to high quality data from multiple sources such as diagostic vas, way side sesors ad so o (see Figure 1). To produce rapid ROI

5 while trasformig the maiteace procedures completely, the solutio must be truly exible, scalable ad itegrated to meet dyamic requiremets. Busiess Rule Egie O-trai moitorig devices Data collectio Rail Operatios Cetre (ROC) Wayside sesors Geometric cars Droes Field Ispectio ad more Coditio Moitorig Sesors/Devices Capturig asset health Data filtratio ad ormalizatio Data itegratio ad maagemet Predictive ad prescriptive aalytics Data Maagemet & Aalytics Alarms Warig Itegratio with Eterprise applicatio Eterprise Resource Plaig (ERP) Icidet Maagemet System (IMS) Coditio Based Maiteace Eterprise Applicatios Impact Aalysis ad Real-time Decisio Makig Maiteace Depot Asset Maagers IT Operatios Data Architecture & Modellig Data Maagemet Eterprise Data Goverace Busiess Itelligece Dashboards Data Warehouse Actioable Isights Reports Figure 1: High-level View of IoT-based Predictive Maiteace Solutio We believe a IoT-based platform with the followig capabilities is best-suited to moitor ad aalyze asset health data for railroad compaies: Data capture ad maagemet: The platform should host a diverse rage of sesors to capture asset data from various coditio moitorig devices- irrespective of the data format, data source, or the type of sesor. This raw data ca be processed at the edge ad stored i databases or le systems depedig o the type. Aalytics ad busiess itelligece: The platform should use the available sesor data alog with other relevat data to develop meaigful isights usig various aalytics tools such as machie learig algorithms for aomaly detectio, ad real-time warigs, predictive asset health assessmet, stream aalytics ad so o. With dashboards based o historic asset coditio data ad predictive aalysis of sesor data, the platform will eable busiess itelligece ad drive superior decisio-makig. Itegratio with eterprise applicatios: The platform should seamlessly itegrate with eterprise asset maagemet (EAM), data warehouse, ad other eterprise

6 IT systems usig stadard middleware platforms to create a ui ed view ad trigger evets ad work ows for subsequet activities. Cloud-eabled: The platform should be deployed o the cloud to allow for scale ad adjustmets based o chagig busiess requiremets. Rethikig Rail Asset Maagemet Today' rail customers demad awless, reliable, ad safe services. For railroad compaies, caterig to these growig expectatios requires the deploymet of ext-ge digital techologies to rede e ad re-imagiig several orgaizatioal processes i additio to upskillig their workforce. The time is ripe for data aalysts, computer professioals, ad rail domai experts to work collaboratively to drive predictive moitorig strategies through digital techologies such as IoT, Big Data techologies, ad sophisticated predictive aalytics algorithms.

7 About The Authors Dr. Kadukuri Raju Dr. Kadukuri Raju is a Trasportatio Rail Domai Cosultat with TCS' Travel, Trasportatio, ad Hospitality busiess uit. He has bee associated with TCS for more tha 18 years, hadlig various resposibilities durig this period. Raju's areas of expertise iclude railroads, logistics, ad itelliget trasportatio systems, ad he has published several research papers o various idustry platforms. He holds a Master's degree i Trasportatio Egieerig from the Natioal Istitute of Techology (NIT), Waragal, Idia, ad a Ph.D. i Trasportatio Systems Egieerig from the Idia Istitute of Techology Bombay, Idia. Shivam Gupta Shivam Gupta is a Busiess Aalyst with TCS' Travel, Trasportatio, ad Hospitality busiess uit, with focus o Railways. He has bee associated with TCS for more tha 4 years. Gupta holds a Bachelor's degree i Mechaical Egieerig from Jamia Millia Islamia, Delhi, Idia, ad a MBA from the Goa Istitute of Maagemet, Goa, Idia. Cotact Visit the Travel, Trasportatio & Hospitality page o tth.marketig@tcs.com Subscribe to TCS White Papers TCS.com RSS: Feedburer: About Tata Cosultacy Services Ltd (TCS) Tata Cosultacy Services is a IT services, cosultig ad busiess solutios orgaizatio that delivers real results to global busiess, esurig a level of certaity o other firm ca match. TCS offers a cosultig-led, itegrated portfolio of IT ad IT-eabled, ifrastructure, egieerig ad assurace services. This is TM delivered through its uique Global Network Delivery Model, recogized as the bechmark of excellece i software developmet. A part of the Tata Group, Idia s largest idustrial coglomerate, TCS has a global footprit ad is listed o the Natioal Stock Exchage ad Bombay Stock Exchage i Idia. For more iformatio, visit us at All cotet / iformatio preset here is the exclusive property of Tata Cosultacy Services Limited (TCS). The cotet / iformatio cotaied here is correct at the time of publishig. No material from here may be copied, modified, reproduced, republished, uploaded, trasmitted, posted or distributed i ay form without prior writte permissio from TCS. Uauthorized use of the cotet / iformatio appearig here may violate copyright, trademark ad other applicable laws, ad could result i crimial or civil pealties. Copyright 2018 Tata Cosultacy Services Limited TCS Desig Services I M I 06 I 18