[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-219772-105":3,"detail-sidebar-cat-1-en-105":80,"doc-detail-219772-en":126},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":73,"head_meta":75,"extra_data":77,"updated_unix":79},105,"en","hybrid-adaptive-model-for-optimising-railway-brake-blocks-replacement-strategy-failure-analysis","Hybrid Adaptive Model for Optimising Railway Brake Blocks Replacement Strategy - Failure Analysis","","The paper presents a novel hybrid adaptive model (HAM) that combines Gaussian mixture probabilistic machine learning, Weibull time-to-failure features, and value of information (VOI) to support complex engineering failure analysis. The goal is to determine an optimum components replacement intervention strategy for composite railway brake blocks, reducing failures and potential accidents. Using London Underground operational data, the approach balances safety and cost-effectiveness by predicting wear, estimating premature failure thresholds, and quantifying net losses under resource constraints.",{"@graph":14,"@context":72},[15,34,55],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/template/","Template",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/template/posters/","Posters",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/template/hybrid-adaptive-model-for-optimising-railway-brake-blocks-replacement-strategy-failure-analysis/219772/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/hybrid-adaptive-model-for-optimising-railway-brake-blocks-replacement-strategy-failure-analysis/219772.png","ImageObject",442,249,{"name":42,"@type":43},"Oliver","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/vnd.openxmlformats-officedocument.wordprocessingml.document","2026-10-05","2026-09-08",true,{"@type":52,"interactionType":53,"userInteractionCount":26},"InteractionCounter",{"@type":54},"ViewAction",{"@type":56,"mainEntity":57},"FAQPage",[58,64,68],{"name":59,"@type":60,"acceptedAnswer":61},"What is the purpose of the hybrid adaptive model (HAM) in this study?","Question",{"text":62,"@type":63},"To establish an optimum components replacement intervention strategy for composite railway brake blocks, reducing failures and possible accidents.","Answer",{"name":65,"@type":60,"acceptedAnswer":66},"How does the model predict brake block wear?",{"text":67,"@type":63},"It uses Gaussian mixture regression with a rational quadratic kernel, training on wear measurement data.",{"name":69,"@type":60,"acceptedAnswer":70},"How are replacement options evaluated for cost and decision-making?",{"text":71,"@type":63},"The VOI feature estimates net loss in cost terms for different replacement options, guiding selection under organizational resource constraints.","https://schema.org",{"og:url":32,"og:type":74,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":76,"canonical":32},"index,follow",{"doc_id":78,"site_id":7},219772,1791217915,{"code":4,"msg":81,"data":82},"success",[83,88,93,98,102,107,112,117,122],{"id":84,"doc_module":22,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},11,"Presentations",90,"presentations",{"id":89,"doc_module":22,"doc_module_name":25,"category_name":90,"show_sort_weight":91,"slug":92},12,"Resumes",80,"resumes",{"id":94,"doc_module":22,"doc_module_name":25,"category_name":95,"show_sort_weight":96,"slug":97},14,"Invoices",70,"invoices",{"id":99,"doc_module":22,"doc_module_name":25,"category_name":29,"show_sort_weight":100,"slug":101},15,60,"posters",{"id":103,"doc_module":22,"doc_module_name":25,"category_name":104,"show_sort_weight":105,"slug":106},16,"Social Media",50,"social-media",{"id":108,"doc_module":22,"doc_module_name":25,"category_name":109,"show_sort_weight":110,"slug":111},17,"Forms",40,"forms",{"id":113,"doc_module":22,"doc_module_name":25,"category_name":114,"show_sort_weight":115,"slug":116},18,"Letters",30,"letters",{"id":118,"doc_module":22,"doc_module_name":25,"category_name":119,"show_sort_weight":120,"slug":121},21,"Paper Templates",5,"papers-templates",{"id":123,"doc_module":22,"doc_module_name":25,"category_name":124,"show_sort_weight":4,"slug":125},158,"General","general-158",{"code":4,"msg":81,"data":127},{"doc_id":78,"user_id":128,"nickname":42,"user_avatar":129,"doc_module":22,"category_id":99,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":26,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":135,"language":136,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":137,"faqs":138,"seo_title":139,"seo_description":12,"update_tm":140,"read_time":141},8796095461610,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","Hybrid adaptive model to optimise components replacement strategy: A case study of railway brake blocks failure analysis\nFrederick Appoh(, Akilu Yunusa-Kaltungo, Jyoti Kumar Sinha\nDepartment of Mechanical, Aerospace and Civil Engineering, The University of Manchester, M13 9PL, UK.\nEmail addresses: \u0013 HYPERLINK \"about:blank\" \u0014frederick.appoh@postgrad.manchester.ac.uk\u0015 (F. Appoh); akilu.kaltungo@manchester.ac.uk (A. Yunusa-Kaltungo); \u0013 HYPERLINK \"about:blank\" \u0014jyoti.sinha@manchester.ac.uk\u0015 (J.K. Sinha)\nCorresponding author: (*)\nAbstract\nIn this paper, we propose a novel hybrid adaptive model (HAM) that integrates Gaussian mixture probabilistic machine learning (ML), Weibull time-to-failure feature, and value of information (VOI) techniques for complex engineering failure analysis. The objective is to establish an optimum components replacement intervention strategy for composite brake blocks of railway rolling stocks to better curtail failures and possible accidents. The HAM considers brake blocks as rudimentary systems for emergency brake application to prevent catastrophic rail accidents under nonlinear and dynamic environmental conditions. A Gaussian mixture regression technique with a rational quadratic kernel function is used to develop a predictive wear model that applies wear measurement as training data. The Weibull feature estimates the threshold maintenance replacement strategy pertaining to other premature failure modes before the brake blocks’ legal scrapping wear limit is reached. Finally, the VOI feature establishes the net loss in terms of cost for the proposed replacement options to guide optimum component replacement selection strategy under organisational resource constraints. Based on operational data obtained from several brake blocks of the London Underground Trains fleet, the proposed HAM failure analysis technique provided a better balance between safety and cost-effectiveness compared to other popular ML approaches.\nKeywords\nComplex failure analysis, rail accidents, Gaussian mixture regression, component replacement, railway brake blocks\n1.\tIntroduction\nThe use of rail transport has increased continuously across the globe owing to its good balance between transportation safety, cost-effectiveness, comfort, energy conservation (especially with electric or hybrid trains), and speed \u0013ADDIN CSL_CITATION {\"citationItems\":[{\"id\":\"ITEM-1\",\"itemData\":{\"DOI\":\"10.1016/J.RESS.2013.03.008\",\"ISSN\":\"0951-8320\",\"abstract\":\"The purpose of this study is to improve the efficiency, reliability and safety related to railroad maintenance tasks through an evaluation of the consequences of failures. The brake system was selected based on the failure data obtained from railroad vehicles in operation as one of the safety systems in railroad vehicles. The failure causes, failure effects, and the criticality of the failure mode were drawn for 62 failure modes of the braking system through the use of an FMECA for the 30 sub-devices having primary functions. The various maintenance tasks for the braking system were categorized into the 62 failure modes and failure consequences using the FMECA and the logic of maintenance decisions. Braking systems manufactured by the same manufacturer and operated by two different operators were studied in an effort to analyze preventive maintenance and to evaluate the adequacy of preventive maintenance tasks for the 62 failure modes. Based on results of the evaluation of these preventive maintenance tasks, new maintenance tasks were proposed, and concrete cost-cutting effects were determined from the calculation of the maintenance time and expected costs, using a preventive maintenance template developed specifically for railroad vehicles.\",\"author\":[{\"dropping-particle\":\"\",\"family\":\"Kim\",\"given\":\"Jaehoon\",\"non-dropping-particle\":\"\",\"parse-names\":false,\"suffix\":\"\"},{\"dropping-particle\":\"\",\"family\":\"Jeong\",\"given\":\"Hyun- Yong\",\"non-dropping-particle\":\"\",\"parse-names\":false,\"suffix\":\"\"}],\"container-tit","cbCaiiEsTqJ3W5xh","https://ap.wps.com/l/cbCaiiEsTqJ3W5xh","docx",1286016,37,"English","# Introduction\n## Hybrid adaptive model (HAM)\n## Predictive wear modeling\n## Weibull maintenance threshold strategy\n## Value of information (VOI) for cost loss\n## Case study and results\n## Keywords","[{\"question\":\"What is the purpose of the hybrid adaptive model (HAM) in this study?\",\"answer\":\"To establish an optimum components replacement intervention strategy for composite railway brake blocks, reducing failures and possible accidents.\"},{\"question\":\"How does the model predict brake block wear?\",\"answer\":\"It uses Gaussian mixture regression with a rational quadratic kernel, training on wear measurement data.\"},{\"question\":\"How are replacement options evaluated for cost and decision-making?\",\"answer\":\"The VOI feature estimates net loss in cost terms for different replacement options, guiding selection under organizational resource constraints.\"}]","Hybrid Adaptive Model for Optimising Railway Brake Blocks Replacement Strategy - Failure Analysis | DOCX",1788893948,13]