RAM and LCC for Railways Industry: what is really important to achieve high performance?

The business article this month propose a discussion about which are the important reliability and safety engineering methods to be applied during railways asset life cycle in order to achieve high performance.

16-05-2017 (May 2017 - publication)

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RAM & LCC for railways industry: what´s really necessary to achieves high performance ?
This article describes the important application of each reliability and safety engineering methods throughout the railways asset life cycle in order to achieve and maintain high performance during operational phase.
RAM & LCC article - may 2017.pdf
Adobe Acrobat Document 2.3 MB


January 2018 (Business Case)


Why FMEA ?

The business article this month propose a discussion about why FMEA is important for the railways assets throughout it life cycle. The paper aims to explain the FMEA importance  and achievement, the different types of the FMEA and the advantages to be applied for the railways asset life cycle phases.


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Why FMEA ?
This technical paper will try to answer the question that many project managers and engineers in Railways industry used to ask during a project. Why we need to implement the FMEA analysis?
Despite of all effort necessary to carry out the FMEA analysis during the project in different phases, more than a project document delivery, the FMEA is an opportunity to improve the asset during the design phase and avoid many failures caused by error triggered during the design and manufacturing phases. In addition, the FMEA is an important input to other analysis, such as RCM and FRACAS as will be discussed in this paper.
FMEA Business case.pdf
Adobe Acrobat Document 1.1 MB

February 2018 (Business Case)


The journey from RCM analysis to asset Management applied for railway industry

this paper aims to clarify the aspect of RCM implemented during the design phase and how to integrate with the asset management during operation phase.


 

The RCM still plays an important hole in RAMS & LCC railway program during design and operation phase. The maintenance management process and implemented during the operation phase need to be part of the asset management program considering all aspects defined in ISO 55000 as well as the three key success factors such as equipment data, people and process.

 

 The RCM information during the design are inputting information for other important analysis during the design phase such as RAM analysis, LCC analysis and LORA. In addition, the RCM information is input to the assurance plan during the operation phase as part of an asset management program, which is facilitated with some integrated data system. Such system enables to implement the asset management as a process include performance monitoring, maintenance information (maintenance plan and work orders), FRACAS, time and task management, LCC management. The coming paper will demonstrate all aspects of the asset management for the railway industry.

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The journey from RCM analysis to asset M
Adobe Acrobat Document 857.5 KB

March 2018 (Business Case)


Reliability prediction based on lifetime data analysis methodology: The Signaling ETCS Trackside Balise case study

This paper explain the basis of the lifetime data analysis, it application throughout the railway asset life cycle, the main mathematic concepts and the study case.


 

The lifetime data analysis is the basis of reliability prediction as well as other index such as failure rate and unreliability. In order to predict such index for a specific period of time and plot the reliability and failure rate functions, it's necessary to apply different best fit methods in order to know firstly, which probability density function (pdf) fits better with the historical data. Secondly, the PDF parameter definition, which enable the reliability and failure rate function plot and index prediction.

 

The reliability concept means “probability of one equipment, product or service be successful until a specific time under defined operating conditions. In order to define the equipment reliability is necessary to collect historical failure data.

 

Therefore, the first step in the lifetime data analysis (LDA) study is to know how failures occur a long time and that's a critical issue for the reliability proper prediction in order to support decisions such as the best time of inspection and preventive maintenance, to check if the equipment is achieved reliability requirement and to supply reliability information to new projects.

 

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Reliability prediction based on lifetime
Adobe Acrobat Document 1'011.4 KB

April 2018 (Business Case Study)


“RAM analysis methodology is the basis for railway asset performance prediction: The Pantograph system case study”

The RAM analysis is a systematic system performance and bad actors effect prediction based on reliability and maintainability data, as well as preventive maintenance, spare parts and LCC data throughout the asset life cycle.


 

Abstract: This business paper aims to demonstrate the application of RAM analysis for railway industry as part of RAMS program implementation, which enable to predict the railways asset reliability, availability and maintainability in different levels, such as system, subsystem, equipment and component by taking into account the relation to each part failure to the impact to the highest system level. The basis for the RAM analysis, prediction is the LDA results based on historical data as discussed in business paper presented in March 2018 in the ECC website. Therefore, to predict the railways system performance, after the LDA results, it´s necessary to model the systems based on the RBD (Reliability Diagram Block) or FTA (Fault Tree Analysis). The final step is the Monte Carlo simulation concerning the system life cycle and operational profile. Finally, the RAM analysis results will provide more than systems, subsystem, equipment and component performance, but also the bad actors definition, in other words, the equipment/component which causes more impact on system operational availability. In order to exemplify the RAM analysis methodology, the case studies applied to critical equipment such as Bogie, Break and signalling will be presented at the end of this chapter.

 

 

Key Words: Lifetime Data Analysis (LDA), reliability, availability, maintainability, expected number of failures and life cycle cost.

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“RAM analysis methodology is the basis for railway asset performance prediction: The Pantograph system case study”
RAM analysis methodogy. The basis for ra
Adobe Acrobat Document 675.2 KB

May 2018 (Business Case Study)


ILS supportability assessment - The Preventive Maintenance Optimization analysis: The Pantograph case study


 

Abstract: This paper aims to demonstrate the application of ILS analysis for railway industry as part of RAMS program implementation, which enable to predict the effect of the logistic on the railways asset performance. The basis for the ILS are the main RAM methods such as LDA, RAM, FMEA and RCM results as discussed in previous chapters. Therefore, the spare parts level, the level of repair analysis, life cycle cost and supportability analysis will be the main topics of this paper. Finally, the case study concerning ILS concepts applied to critical equipment such as pantograph will be presented at the end of this paper.

 

 

 

Key Words: LSA, LRA, spare parts, Life cycle cost, supportability.

 

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ILS Optimization applied to railway indu
Adobe Acrobat Document 918.2 KB

June 2018


Functional Hazard Analysis and SIL limitations: Safety and reliability approach


coming soon