Approach to systematic improvements of dependability within railway asset management

Approach to systematic improvements of dependability within railway asset management | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Case Report Approach to systematic improvements of dependability within railway asset management Rikard Granström, Peter Söderholm This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4557557/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Oct, 2024 Read the published version in International Journal of System Assurance Engineering and Management → Version 1 posted 5 You are reading this latest preprint version Abstract This paper describes results from a research and development (R&D) project at Trafikverket (Swedish transport administration). The purpose of the study was to systemize dependability improvements of Trafikverket’s Control Command and Signalling (CCS) assets. A case study was conducted on level crossings that represent a critical part of the CCS system. The results of the study show that the systemic approach contributes to asset management as it contributes to short-term dependability and productivity improvements as well as to medium term specifications for system modifications and long-term specifications for next generation of level crossings. The approach is based on a combination of methodologies and tools described in dependability standards, e.g., Failure Modes, Effects & Criticality Analysis (FMECA). However, the approach also considers aspects from Design of Experiments (DoE) to support field tests aligned with other tasks in the railway infrastructure. Besides contributing to improvements, the approach complies with regulations and mandatory standards. Examples of these are Common Safety Method for Risk Evaluation and Assessment (CSM-RA, EU 402/2013) and EN 50126 - RAMS (Reliability, Availability, Maintainability & Safety) for railway applications. In addition, the approach complies with regulatory requirements related to enterprise risk management and internal control, i.e., effectiveness, productivity, compliance and documentation. The approach also supports asset management in accordance with the ISO 55000-series. Railway dependability Asset management Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction Besides changes in a technical system’s reliability and maintainability, one central part of continuous dependability improvement is the continuous improvement of the on-going maintenance programme as prescribed by Reliability-Centred Maintenance (RCM) [ 1 ]. However, any change to the maintenance program that might affect railway safety must follow CSM-RA. In addition, any safety-related requirement should be evaluated with regard to availability and life cycle cost (LCC) before it can be accepted. Hence, any improvements of safety or dependability should be integrated with each other, as described by EN 50126 (RAMS) [ 2 ]. There are many safety critical functions within the railway infrastructure. One of these functions are the possibility to safely pass the railway track at level crossings. Hence, level crossing users and related accidents are one risk category that has to be managed in accordance with regulations such as Common Safety Targets (CST). Besides safety, level crossings also impact the availability of infrastructure for train passages and road traffic, but also asset management and LCC. Hence, continuous dependability and productivity improvements related to level crossings can contribute positively to effective railway asset management. Maintenance programmes governing the maintenance of Trafikverket’s infrastructure assets have from the outset been constructed based upon expert judgments from which rules and regulations for maintenance have been derived. During the years, new rules have been added, sometimes due to incidents or accidents, some of which have had fatal consequences. Hence, some rules are “written in blood”. As experts retire or go to other occupations, the rules remain, while the knowhow and logic to why rules are existing slowly diminishes. This creates a situation where maintenance programmes become static as by ossification. Without a systematic description of the logic from which maintenance programs are derived, it is difficult for the asset manager to implement changes, alter the maintenance programs, and at the same time assess consequences of proposed changes. New maintenance technologies and methodologies emerge, but are rarely adopted and implemented to support a more effective and efficient asset management. This paper is based on a study conducted at Banverket (Swedish railway administration), predecessor to Trafikverket (Swedish transport administration). The study set out to explore how dependability improvements of level crossing assets could be obtained, by applying standardised dependability methodologies. The study is a relevant description of a methodology that can be applied to create necessary prerequisites for any organisation wanting to improve dependability as well as contributing to improvements of LCC within safety-critical systems. As an exemplary case, the study it is also a relevant description of efforts required to implement changes in maintenance programs and maintenance concepts within railway. 2. Theoretical background The theoretical framework of this work is based on best agreed upon applications, as described by common dependability and railway specific standards. Examples of central standards are IEC 60300-3-11 (Reliability-Centred Maintenance, RCM) [ 1 ], IEC 60300-3-14 (Maintenance and maintenance support) [ 3 ], IEC 60812 (FMEA/FMECA) [ 4 ], and EN 50126 (RAMS) [ 2 ]. In addition, theories related to Design of Experiments (DoE) are used to plan verification and validation of changes in current maintenance programs. 3. Methodology The study was conducted over a period of approximately five years. Initiatives from researchers and the infrastructure manager Banverket led to a methodology, which can be described in three evolutionary stages. The first step of the study was initiated by a research proposal to use FMEA and FTA to systemize the dependability of the level crossing system. Findings from this initial study rendered into recommendations for operational changes of the existing maintenance programme and maintenance concept as well as recommendations for tactical changes for functional modifications of the level crossing assets [ 5 ]. Even some strategical recommendations for the next generation of level crossings were made. The second step of the study was initiated by Banverket to assess the effectiveness of proposed operational changes to the maintenance programme and the maintenance concept. Therefore, a decision was made to do an analysis to estimate the impact of proposed changes in terms of cost and dependability and to find a track section at which recommendations for maintenance programme and maintenance concept could be deployed for demonstration and verification [ 6 ]. The third step was a verification testing in field, which focused on the implementation of recommendations at track section 524 between Hallsberg and Frövi stations [ 7 ]. An extended maintenance programme was executed by the maintenance entrepreneur Infranord. In addition, field observations were made to assess the feasibility of recommended maintenance execution and to study the time it takes to execute maintenance in track. 4. Data collection The empirical material used in this work is based on Trafikverket’s asset management of level crossings. Besides maintenance programs, data is collected from the inspection system (Bessy), the fault reporting, analysis and corrective action system (0Felia), the asset register system (BIS) and Banverket’s material catalogue. Data and knowledge gathering for the FMEA and the FTA were to a large extent gathered through a cross functional team, which according to RCM logic is required for conducting the analysis. Members of the team included, process leader, signalling experts, maintenance technicians, inspection experts and people responsible for rules and regulations (maintenance programme). Field observations during maintenance execution were also used to collect data relevant to productivity improvements of existing maintenance concept. 5. Discussion and results The results from the study are presented in relation to the three steps of the applied approach to provide useful insights from the performed study. 5.1. Step 1 – FMECA and FTA To construct a FMEA for the level crossing system was not a straight-forward exercise. The first obstacle to overcome was to define the actual system of interest, i.e., which inherent items that are part of the level crossing system. No existing drawing of the system could be obtained. Therefore, field visits together with maintenance technicians and archival analysis of Banverket’s material catalogue were used to assemble know how and items that are inherent to the level crossing system. Another challenge was to determine the system boundaries, and thereby which inherent items to be considered in the analysis. The aim of the study was to improve system dependability. Hence, it was necessary to identify which items that are critical for the dependability of the level crossing system. The system of interest should be the constitution of inherent items that provide the dependability of required function. Hence, initial work was devoted to analysis of what is the required function of the level crossing system. Reasoning led to the conclusion that the required function of a level crossing system is to provide reliable go/no-go signals to both rail and road traffic. Therefore, the system of interest and the items included in the study were selected upon the basis that they are critical for the required function (go/no-go for rail and road traffic). In order to obtain a useful system structure for analysis, items had to be grouped into sub-functions that are critical for obtaining the required system function. Identified sub functions were, internal power supply, crossing gate mechanism, control logic, track circuit and optical and audible signalling, se Fig. 1 . Inherent items that are critical for obtaining sub-functions were grouped into their respective category. See Fig. 2 , example of some items critical for the crossing gate mechanism function. Field visits were conducted together with maintenance personnel during the initial phases of the study. These visits were valuable for understanding the physics of the degradation of the system (cause and effect) and for gaining knowledge of how maintenance is executed. Discrepancies were identified between what was stated as requirements in the maintenance programme and what was performed in real life. This understanding was especially useful for later work with the FMEA-sheets. One example of the degradation process can be related to the crossing gate arm. In Sweden, level crossing gate arms are made of wood with a protective coating of paint. The crossing gate mechanism is supposed to work as a seesaw (teeter) in almost perfect balance. However, if the coating is compromised, the wood will absorb moisture. Hence, the crossing gate will become heavier, which affects the balance of the seesaw. This will in turn lead to excessive degradation and failure of mechanical components within the crossing gate mechanism. See Fig. 3 . Another example of a failure process can be seen in Fig. 4 . Here, grease is injected into the grease nipples on the outside of the crossing gate mechanism, in accordance with the maintenance programme. However, excessive grease propagates to the inside of the mechanism and drips down onto the roller switch (which indicates the position of the gate arm) causing it to lose its function, usually in an intermittent manner. An obvious cause of No Fault Found events (NFF). While consulting outdated maintenance programmes it was discovered that there used to be a instruction requiring excess grease to be removed when applying new grease. This instruction could however not be found in current maintenance programs. One of the challenges when working with complex systems where many different inherent items can experience multiple failure modes is to get a bird eye system view of the problem. One solution to this problem was to perform a rudimentary form of Fault Tree Analysis (FTA), illustrated in Fig. 5 . By using different colours, different aspects of function, failure mode and maintenance programme can be illustrated. The orange colour illustrates the unwanted top event of a faulty crossing gate mechanism function. The yellow colour illustrates the degraded functional states of sub-components. The blue colour marks the failure modes and the grey colour indicate areas where the current maintenance programme or its application can be insufficient. The FMEA was constructed following recommendations from IEC 60812 (Analysis techniques for system reliability – Procedure for failure mode and effects analysis, FMEA) [ 4 ]. At outset, the study followed the standard structure of the FMEA sheets, where the physical item was the baseline for the analysis. However, this led to a rather tedious exercise since a number of items experience the same type of failure modes, causing each failure mode to be described in the same way on multiple occasions for different items. This causes the FMEA-sheet to become somewhat incoherent and the group working with the analysis lost focus on multiple occasions. Hence, the recommendation for future studies is to focus on functions instead of physical items. In this case, the study should emanate from the required system function (e.g. level crossing), or appropriate sub system function, e.g., the crossing gate mechanism’s required function. Next step is to assess the failure modes which can cause loss of required function. Thereafter, the items whose functions are critical for maintaining required function. See Table 1. Table 1 part 1, 2 and 3 of FMEA-sheet. This approach is a functional FMEA and is in its structure much more like the representations created in the fault trees. This is also from a maintenance point of view a more rational structure since the purpose of maintenance is to maintain or restore required system functions and not the condition of physical items. In addition, the FMEA (Table 1) proved to be much valuable to reconstruct the logic behind the documented maintenance programme. The first part of the FMEA describes unit, function and failure mode. The second part of the FMEA describes the failure modes’ failure cause, local and final effect as well as the detection method (e.g., inspections), and compensating provisions against failure (e.g., actual maintenance task to be executed). The third part of the FMEA contains recommendations for alternative detection methods and recommended measures. Parts one and two of the FMEA-sheet describe the present situation. Part three of the FMEA-sheet describes improvements that can be achieved compared to the present situation. The beauty of this structure is also that it directly indicates which failure mode a recommended measure addresses, while the structure allows us to see which type of effects, we could expect in relation to implementing, e.g., recommended changes. Overall, it gives a much useful initial structure for Design of Experiments (DoE). The combination of FTA and FMECA allows to recreate the logic behind the maintenance programmes. It also provides a baseline for experiments, which can be conducted in an orderly fashion since it already from the outset is possible to isolate the consequences of proposed changes. The FMEA is also valuable for collecting recommendations for future system modifications. The conducted study rendered in a long list of recommendations. Some of the operational recommendations were: Better instructions for battery maintenance, remove oxide from terminals, use special grease. Develop decision support for when to exchange batteries. Instructions for applying grease, and cleaning of excess grease. Better instructions for when to paint gate arms. Include inspection of cross gate mechanism heating. Make sure that failures of structural items are corrected (doors, seals, mosquito-nets, rubber strips). If required, cleaning of roller switches from access grease to prevent intermittent failures. Some of the tactical and strategical recommendations are: Use other material than wood in gate arms. Materials which do not absorb water and which can withstand snow and ice build-up. Exchange track circuits to axle counters. Change signalling light from bulbs to LED. Better instructions for snow removal. Redesign of engine mounting, where present mount (standing engine) causes grease to run through the inside of the engine, causing grease to attach to motor brush and commutator, leading to intermittent failures. 5.2. Step 2 – planning of field experiment To execute any change of a railway maintenance programme in Sweden, as in most national railway administrations, is a major task. It involves updates of rules and regulations, preparation of information systems to accommodate the changes, e.g., new inspections and new maintenance tasks. It involves developing new courses and to educate technicians on a nationwide scale. Since maintenance is executed by entrepreneurs, the changes also have to be accommodated within new and existing maintenance contracts throughout the nation. Therefore, it is necessary to validate changes in small scale before executing nationwide plans. From the recommended changes to the maintenance programme suggested by the FMEA, an analysis was made to estimate the impact of proposed changes in terms of cost and dependability. The analysis also included the task to find a track section at which recommendations for maintenance programme and maintenance concept could be deployed for demonstration and verification. Track section 524 was identified as a useful candidate for verification testing. This track section had a high number of faults per level crossing. Configuration wise the track section represented an average constitution of level crossings in Sweden. Based on fault data this track section was in a degraded state and in need of improved maintenance. The number of level crossings (20) for the study was judged satisfactory. Expected results from the test: Improved dependability and reduced cost for preventive and corrective maintenance. Cost-benefit of performed measures, which could serve as decision support for further dependability improvements for level crossing assets. A demonstrator for how changed maintenance programmes and maintenance concepts could be deployed nationwide, also for other systems than level crossings. The cost-benefit analysis was constituted in three main parts: Initial increase of preventive maintenance effort and related cost to restore the dependability of the level crossing system. Increased cost for deployment of new recommended maintenance programme. Cost-benefit comparison between increased preventive maintenance cost (pt.1 and pt.2) compared with reduced cost for corrective maintenance. An estimation was done that corrective maintenance measures could be reduced by some 50% due to increase of system dependability. In theory, if the initial calculations were to hold up, the pay-off time for initial cost increase from pt.1 and pt.2 would be somewhere between 2–3 years. After which the dependability level could be maintained at a lower cost than required by previous maintenance programme. From this part of the study recommendations were also made for practical preparation of the actual experiment, some of which are: Detail the maintenance concept for critical items. One example being the crossing gate mechanism motor, which due to excessive application of grease can experience intermittent failures when grease comes into to the motor and clogs the brush and commutator. Training programme for the entrepreneurs in accordance to the new maintenance programme. Develop routine to keep track of costs within the experiment. Open books, to keep track of real costs. Continuous assessment meetings with the entrepreneur to keep them focused on the task at hand. There is always a risk that they return to old habits. The maintenance programs should contribute to extended life length of items. However, the reporting structure of failure or faults does not support an adequate description of items’ life lengths. Therefore, it was recommended to conduct interviews with technicians to get their assessment of the matter. Conduct interviews with infrastructure manager and signalling experts to document their experiences, which are useful for further development of maintenance programs and for the deployment on a larger scale 5.3. Step 3 – execution of verification field test Verification testing started with an inspection fit for the purpose of assessing the amounts of material that had to be pre-ordered before the physical work could be conducted. Two days were required to complete the inspection, i.e., 10 level crossings per day. Table 2 Signalling related faults and NFF 2008–2021 Results of the experiment were in accordance with expectations. Hence, the number of faults were reduced by a magnitude of 50%. The physical work was conducted in June 2012, Table 2 shows the development of signalling related faults for the years 2008–2021. Table 2 Signalling related faults and NFF 2008-2021 Interesting to observe is also that the number of no fault found (NFF) events were reduced in comparison to previous statistics. It should be mentioned, that the test was only carried out 2012 to somewhere in 2014. A technician involved in the test, who is still working on the same track section have confirmed that maintenance execution from 2015 onwards has in most aspects returned to how maintenance was carried out before the test. This might explain why the number of faults has increased from 2015 onwards. As for the NFF events, the crossing gate mechanism motor has been a source of intermittent failures in all level crossings. There was a hypothesis that the cause of the intermittent failures were the cause of excess grease contaminating items internal to the motor. Before executing the verification test, the project set out to test this hypothesis by examining a couple of the motors to assess whether grease was in fact contaminating items internal to the motor. A couple of motors were therefore disassembled for this purpose, see Fig. 6. The picture in the middle clearly shows a contaminated commutator. The left picture shows commutator after cleaning operation. From a cost perspective, this finding was especially interesting. The current practice is to replace the motor in field if it has any major problem. The cost for one new motor in 2012 was 1,550€. If the motor had been refurbished at a factory, the cost was somewhere around 1,200€. A time study conducted before the field test showed that it took about 30 minutes to refurbish an engine in field conditions, with an estimated refurbishment cost of about 50€. Hence, the cost saving potential is somewhere around 25–30 times. This could have an enormous impact on the total asset management cost of level crossings if implemented nationwide. A test was set up within the verification test to examine whether refurbishment of engines was, from a reliability point of view a viable alternative to exchanging motors. Therefore, a lot of motors were replaced in the beginning of the verification test. Motors were exchanged in three categories, new, refurbished in factory, and refurbished in field. In addition, instructions for applying a correct amount of grease to the motors was included in the maintenance concept. Table 3 shows the number of reported faults on track section 514 where a motor is replaced for the test series. Interesting to observe is that none of the motors replaced due to fault is a motor refurbished in the field. Therefore, it can be concluded that refurbishing motors in the field is, from a reliability and cost point of view, a much more viable task than the other two alternatives. In practice a more logical production logistics would be to bring motors refurbished at a entrepreneur workshop out in the field and replace the contaminated motors to bring them back to the workshop for refurbishment. Table 3. Number of faults requiring exchange of motor Tightening of terminals (Fig. 7 ) is also something that should be included in the maintenance programme. On multiple occasions, it was discovered that connectivity was not satisfactory. This is a likely cause of intermittent failures and NFF events. However this is something that does not have to be conducted every year, therefore similar measures should be planned as reoccurring periodic restorations e.g. every third year. Another interesting field observation was that the paint recommended for protective coating of the gate arms was not working as intended. It did not provide an adequate protection cover. However, when efforts were made to paint the gate arms with a second layer (15 minutes after the first coating) of the same paint the results were fantastic, almost like a shrink tubing had been placed on to the arm, see Fig. 8 . As for future maintenance concepts of gate arms, they should state that two coats of paint should be applied. Other recommendations for the maintenance programme was also derived from the test, while changing gate arms. As the base paint (from factory) was deemed inadequate to withstand moisture, the recommendation was to paint the whole gate arm when installing new materials. And especially add paint to the end of the gate arm, which almost always has to be sawed into right length, leaving the end unprotected and exposed to rain, se middle picture in Fig. 8 . Gate arms are almost all the time facing the rain since they are only lowered at train passage. Hence, without protective coating at the tip, water will sipper into the wood of the gate arm A time study was also conducted to assess the production rate for maintenance of level crossing. During the planning of the experiment phase, an assumption was made that two persons would require one day to perform maintenance of one level crossing in accordance with the new instructions. During the experiment, it was obvious that two level crossings could be managed if the execution was well planned and all required materials were prepared and brought to field. For future maintenance concepts, it is useful that the same personnel get to do the physical work since they get better at it for each day. 6. Conclusions The work presented in this paper shows that it is possible to fulfil requirements of value creation within asset management and enterprise risk management and internal control (i.e., compliance, effectiveness, productivity and documentation) when working with continuous dependability improvement. The applied combination of methodologies focusing on process, function and system (primarily FMECA, FTA and DoE) fulfil requirements related to compliance (primarily railway safety and RAM) and documentation. In addition, the effectiveness is improved by increased availability performance simultaneously as the productivity is improved by cutting costs. However, in spite of this, there have not been any general implementation of the project results, e.g., by changes in Trafikverket’s maintenance programmes. This unsatisfactory situation is not unique for this project or for Trafikverket, but it is actually becoming more frequently recurring. Hence, there are dedicated research areas studying the pacing problem, i.e., the phenomenon where the regulators are struggling to keep pace with the fast technological development and avoid ossification. As indicated above, roles responsible for and working with dependability improvements should participate in every part of the maintenance process. This to ensure that changed tasks in maintenance programmes are supported and executed in the right way at all process phases. It is important that correct information is collected throughout the experiment. Preferable, the same systems should be used for planning and data collection during the experimentation study as during normal operation. One reason is that different tasks in the railway infrastructure should be coordinated, e.g., regarding possession times. Another reason is that data should be used to measure any change in dependability and cost. It was possible to get dependability data with good enough quality by combining sources such as the inspection system (Bessy), the fault reporting and corrective action system (0Felia), and the asset register (BIS). Hence, it was also possible to estimate the obtained dependability improvements. However, cost data with sufficient quality was more challenging to obtain. Hence, it was not possible to estimate the actual cost savings in a good way. The major obstacle for receiving good quality cost data is that Trafikverket only has aggregated or contract-related cost data. However, the maintenance entrepreneur has more specific and real cost data related to individual maintenance tasks in the railway infrastructure. However, even when data is available it may not be relevant for dependability improvements related to the maintenance programmes. Hence, the use of FMECA can support the identification of relevant information to collect in field to monitor specific functions and their failure modes. In addition, the FMECA can be used to evaluate possible condition monitoring applications to support condition-based maintenance (CBM) of different failure modes. When working with changes that requires field tests in the railway infrastructure, it is crucial to always start with the design of the experiment. This involves to identify what to control, what to measure, how to measure and determine how to perform the evaluation. It is not sufficient to expect that these things sort itself out at the end or that someone else will take responsibility at the end. These things have to be determined already in the experimental design stage, and pre-test is a good way to test assumptions made in the design. Without proper preparation of experimental design, it is not uncommon that data is collected which at the end is shown to be insufficient for evaluation purposes. The planning of the experiment should consider the overarching purpose. In this case, it is to receive information to make a correct decision about improvements of the existing maintenance programme. Hence, it is a deductive approach that starts with the decision, then identifies necessary information as support, and finally what data to collect and analyse. The FMEA and FTA are valuable to get a useful system description for experimental design purposes. Hence, the FMECA and FTA can be used to document expert knowledge and judgement or statistical correlations that are the foundation of the maintenance program. The experiments can contribute with establishing causal relationships by verifying and validating expert judgements and statistical correlation analyses. After the test was executed, Banverket performed an own inspection to control that all included level crossings had been maintained by the entrepreneurs according to the new instructions. This control revealed that some maintenance tasks had been omitted by the entrepreneur. However, after the control inspection by Trafikverket and resulting communication activities, the entrepreneur executed the remaining work. In summary, trust is good, but control is better (necessary) to enable a follow up of the effects of proposed changes. Hence, the ones responsible for the test have to stay involved in all aspects of it, especially regarding maintenance execution in field. It is not possible to assume that the operative maintenance personnel in field automatically understands what and how tasks should be executed, or that they are motivated. Hands-on education in the field is the best way to get an understanding and acceptance, i.e., show physically how the tasks are to be carried out. The ones designing the test will also learn and get insight about the application area and its limitations by participating in day-to-day maintenance activities in the field. The later follow-up of the long-term effects of proposed changes, reveals that it is challenging to follow a planned experiment that requires an extended test time to estimate achieved affect. Hence, it requires perseverance to conduct a planned experiment that extends over several years. Especially when persons related to decisions and tasks included in the experiment includes changes at both the infrastructure manager and at the maintenance entrepreneur. Normally, most people are excited to test something new, but perseverance is required to conduct a study for a number of years An interesting finding of the study is related to the maintenance of level crossing motors. By repairing the motor in field instead of replacing it, gives a potential cost saving of 25–30 times. When considering this on a national level for all relevant level crossings, the savings becomes significant. Hence, the FMECA and FTA supported a simple level of repair analysis that identified a dependability improvement with great cost saving and no negative impact on the availability for functions required by rail and road traffic. However, for lines with very high density traffic, replacement of the motor may still be preferred compared with field repair due to availability requirements. In these cases, a combination can be applied by using a field restored motor for replacement of the faulty motor and thereafter repair the replaced motor in field. By this approach, only field level maintenance is involved and other levels of repairs are excluded. This should reduce NFF events and associated costs, as well as other Life support costs (LSC), e.g., related to logistics. Declarations Compliance with Ethical Standards The research presented in this paper are conducted and reported in line with signed agreements by participating actors to ensure compliance with regulations that are mandatory for authorities in Sweden as a member of the EU. Acknowledgments We acknowledge the financial and intellectual support received from Trafikverket, especially the R&D project “ASSET” (TRV 2022/29194). Functionality provided by “Reality Lab Digital Railway” (TRV 2017/67785, and Vinnova, 2017–02139) is also highly appreciated. A version of this paper has previously been presented at the Industrial AI Congress 2023 (IAI2023) in Luleå [8]. References IEC (2010) 60300-3-11 - Dependability management Application guide - Reliability centred maintenance. International Electrotechnical Commission, Geneva Switzerland IEC (2017) 50126 - Railway Applications - The Specification and Demonstration of Reliability, Availability, Maintainability and Safety (RAMS). International Electrotechnical Commission, Geneva Switzerland IEC (2008) 60300-3-14 - Dependability management - Application guide - Maintenance and maintenance support. International Electrotechnical Comission, Geneva Switzerland IEC (2006) 60300-3-11 - Analysis techniques for system reliability – Procedure for failure mode and effects analysis (FMEA). International Electrotechnical Comission, Geneva Switzerland Granström R (2009) DoU utredning av Banverkets vägskyddsanläggningar. Technical report. Trafikverket, Luleå Granström R (2011) Underhållsbehovsanalys – Beslutsstöd för driftsäkerhetshöjning vägskyddsanläggningar. Technical report. Trafikverket, Luleå Granström R (2012) Halvårsutvärdering förstärkt underhåll vägskyddsanläggningar BDL 524. Technical report. Trafikverket, Luleå Granström R, Söderholm P (2023) Systematic dependability improvements within railway asset management. Proceedings of Industrial AI Congress (IAI2023), Luleå, Sweden 2023 Cite Share Download PDF Status: Published Journal Publication published 01 Oct, 2024 Read the published version in International Journal of System Assurance Engineering and Management → Version 1 posted Editorial decision: Minor revisions 08 Jul, 2024 Reviewers agreed at journal 13 Jun, 2024 Reviewers invited by journal 13 Jun, 2024 Editor invited by journal 12 Jun, 2024 First submitted to journal 11 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4557557","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Case Report","associatedPublications":[],"authors":[{"id":313970687,"identity":"114424d3-a73d-4385-aa45-67c6596222f2","order_by":0,"name":"Rikard Granström","email":"","orcid":"","institution":"Trafikverket","correspondingAuthor":false,"prefix":"","firstName":"Rikard","middleName":"","lastName":"Granström","suffix":""},{"id":313970688,"identity":"bc1ea155-d4af-45a0-baf5-b758764eb2d7","order_by":1,"name":"Peter Söderholm","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-6479-9101","institution":"Trafikverket","correspondingAuthor":true,"prefix":"","firstName":"Peter","middleName":"","lastName":"Söderholm","suffix":""}],"badges":[],"createdAt":"2024-06-10 10:57:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4557557/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4557557/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s13198-024-02523-4","type":"published","date":"2024-10-01T15:56:53+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59968257,"identity":"30200e9a-c846-479a-8a31-75b61accccfb","added_by":"auto","created_at":"2024-07-10 02:34:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":190559,"visible":true,"origin":"","legend":"\u003cp\u003eSub functions of required system function.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4557557/v1/a12ae5ffc5c3ea3952265d78.png"},{"id":59969479,"identity":"bdd7b6f6-a91b-4b77-be6b-d0f0336e4cca","added_by":"auto","created_at":"2024-07-10 02:50:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":109753,"visible":true,"origin":"","legend":"\u003cp\u003eSome items critical for the crossing gate sub function.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4557557/v1/597c1ddf7d068988878a6fb3.png"},{"id":59969266,"identity":"c48320a5-c547-4634-a7af-49863f60b3d2","added_by":"auto","created_at":"2024-07-10 02:42:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":152324,"visible":true,"origin":"","legend":"\u003cp\u003eLevel crossing gate arm.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4557557/v1/27f412b561d19434f68f82f9.png"},{"id":59968259,"identity":"58a154d5-94d6-45c9-9a16-59a2c15f0462","added_by":"auto","created_at":"2024-07-10 02:34:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":312374,"visible":true,"origin":"","legend":"\u003cp\u003eGrease in roller switch.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4557557/v1/9b0ade287666fc65d7888aa0.png"},{"id":59969267,"identity":"93d92bd3-9bc1-429a-949b-49fc9a907ebd","added_by":"auto","created_at":"2024-07-10 02:42:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":99057,"visible":true,"origin":"","legend":"\u003cp\u003eRudimentary documentation of fault tree analysis (FTA).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4557557/v1/5ccf9eecf3f82819bc932fdc.png"},{"id":59968263,"identity":"62edb195-6de3-4c1e-8a7f-5af9aae914fb","added_by":"auto","created_at":"2024-07-10 02:34:28","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":360466,"visible":true,"origin":"","legend":"\u003cp\u003eMotor after and before refurbishment, right picture engine marked for test.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4557557/v1/c4835661c295d6b40895683c.png"},{"id":59968265,"identity":"c0eedd10-2e2a-4fd6-82dd-ac6317be0b03","added_by":"auto","created_at":"2024-07-10 02:34:28","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":557247,"visible":true,"origin":"","legend":"\u003cp\u003eTightening of terminals\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4557557/v1/5f687d9d59b618547b49d2ba.png"},{"id":59969269,"identity":"d9ea9ccb-e4b7-4602-bf1e-6954c89d6787","added_by":"auto","created_at":"2024-07-10 02:42:28","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":277122,"visible":true,"origin":"","legend":"\u003cp\u003eProtective coating of gate arm.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-4557557/v1/c0dd62c89be6ea6a3d78de6a.png"},{"id":66097817,"identity":"e21d4034-cc3b-4fce-8565-2d77139fb022","added_by":"auto","created_at":"2024-10-07 16:15:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4149637,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4557557/v1/a3dd1ed1-9290-41f6-ac60-50c2df9f7ccf.pdf"}],"financialInterests":"","formattedTitle":"Approach to systematic improvements of dependability within railway asset management","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eBesides changes in a technical system\u0026rsquo;s reliability and maintainability, one central part of continuous dependability improvement is the continuous improvement of the on-going maintenance programme as prescribed by Reliability-Centred Maintenance (RCM) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, any change to the maintenance program that might affect railway safety must follow CSM-RA. In addition, any safety-related requirement should be evaluated with regard to availability and life cycle cost (LCC) before it can be accepted. Hence, any improvements of safety or dependability should be integrated with each other, as described by EN 50126 (RAMS) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are many safety critical functions within the railway infrastructure. One of these functions are the possibility to safely pass the railway track at level crossings. Hence, level crossing users and related accidents are one risk category that has to be managed in accordance with regulations such as Common Safety Targets (CST). Besides safety, level crossings also impact the availability of infrastructure for train passages and road traffic, but also asset management and LCC. Hence, continuous dependability and productivity improvements related to level crossings can contribute positively to effective railway asset management. Maintenance programmes governing the maintenance of Trafikverket\u0026rsquo;s infrastructure assets have from the outset been constructed based upon expert judgments from which rules and regulations for maintenance have been derived. During the years, new rules have been added, sometimes due to incidents or accidents, some of which have had fatal consequences. Hence, some rules are \u0026ldquo;written in blood\u0026rdquo;. As experts retire or go to other occupations, the rules remain, while the knowhow and logic to why rules are existing slowly diminishes. This creates a situation where maintenance programmes become static as by ossification. Without a systematic description of the logic from which maintenance programs are derived, it is difficult for the asset manager to implement changes, alter the maintenance programs, and at the same time assess consequences of proposed changes. New maintenance technologies and methodologies emerge, but are rarely adopted and implemented to support a more effective and efficient asset management.\u003c/p\u003e \u003cp\u003eThis paper is based on a study conducted at Banverket (Swedish railway administration), predecessor to Trafikverket (Swedish transport administration). The study set out to explore how dependability improvements of level crossing assets could be obtained, by applying standardised dependability methodologies.\u003c/p\u003e \u003cp\u003eThe study is a relevant description of a methodology that can be applied to create necessary prerequisites for any organisation wanting to improve dependability as well as contributing to improvements of LCC within safety-critical systems. As an exemplary case, the study it is also a relevant description of efforts required to implement changes in maintenance programs and maintenance concepts within railway.\u003c/p\u003e"},{"header":"2. Theoretical background","content":"\u003cp\u003eThe theoretical framework of this work is based on best agreed upon applications, as described by common dependability and railway specific standards. Examples of central standards are IEC 60300-3-11 (Reliability-Centred Maintenance, RCM) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], IEC 60300-3-14 (Maintenance and maintenance support) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], IEC 60812 (FMEA/FMECA) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and EN 50126 (RAMS) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In addition, theories related to Design of Experiments (DoE) are used to plan verification and validation of changes in current maintenance programs.\u003c/p\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eThe study was conducted over a period of approximately five years. Initiatives from researchers and the infrastructure manager Banverket led to a methodology, which can be described in three evolutionary stages.\u003c/p\u003e \u003cp\u003eThe first step of the study was initiated by a research proposal to use FMEA and FTA to systemize the dependability of the level crossing system. Findings from this initial study rendered into recommendations for operational changes of the existing maintenance programme and maintenance concept as well as recommendations for tactical changes for functional modifications of the level crossing assets [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Even some strategical recommendations for the next generation of level crossings were made.\u003c/p\u003e \u003cp\u003eThe second step of the study was initiated by Banverket to assess the effectiveness of proposed operational changes to the maintenance programme and the maintenance concept. Therefore, a decision was made to do an analysis to estimate the impact of proposed changes in terms of cost and dependability and to find a track section at which recommendations for maintenance programme and maintenance concept could be deployed for demonstration and verification [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe third step was a verification testing in field, which focused on the implementation of recommendations at track section 524 between Hallsberg and Fr\u0026ouml;vi stations [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. An extended maintenance programme was executed by the maintenance entrepreneur Infranord. In addition, field observations were made to assess the feasibility of recommended maintenance execution and to study the time it takes to execute maintenance in track.\u003c/p\u003e"},{"header":"4. Data collection","content":"\u003cp\u003eThe empirical material used in this work is based on Trafikverket\u0026rsquo;s asset management of level crossings. Besides maintenance programs, data is collected from the inspection system (Bessy), the fault reporting, analysis and corrective action system (0Felia), the asset register system (BIS) and Banverket\u0026rsquo;s material catalogue. Data and knowledge gathering for the FMEA and the FTA were to a large extent gathered through a cross functional team, which according to RCM logic is required for conducting the analysis. Members of the team included, process leader, signalling experts, maintenance technicians, inspection experts and people responsible for rules and regulations (maintenance programme). Field observations during maintenance execution were also used to collect data relevant to productivity improvements of existing maintenance concept.\u003c/p\u003e"},{"header":"5. Discussion and results","content":"\u003cp\u003eThe results from the study are presented in relation to the three steps of the applied approach to provide useful insights from the performed study.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e5.1. Step 1 \u0026ndash; FMECA and FTA\u003c/h2\u003e \u003cp\u003eTo construct a FMEA for the level crossing system was not a straight-forward exercise. The first obstacle to overcome was to define the actual system of interest, i.e., which inherent items that are part of the level crossing system. No existing drawing of the system could be obtained. Therefore, field visits together with maintenance technicians and archival analysis of Banverket\u0026rsquo;s material catalogue were used to assemble know how and items that are inherent to the level crossing system. Another challenge was to determine the system boundaries, and thereby which inherent items to be considered in the analysis. The aim of the study was to improve system dependability. Hence, it was necessary to identify which items that are critical for the dependability of the level crossing system. The system of interest should be the constitution of inherent items that provide the dependability of required function. Hence, initial work was devoted to analysis of what is the required function of the level crossing system. Reasoning led to the conclusion that the required function of a level crossing system is to provide reliable go/no-go signals to both rail and road traffic. Therefore, the system of interest and the items included in the study were selected upon the basis that they are critical for the required function (go/no-go for rail and road traffic).\u003c/p\u003e \u003cp\u003eIn order to obtain a useful system structure for analysis, items had to be grouped into sub-functions that are critical for obtaining the required system function. Identified sub functions were, internal power supply, crossing gate mechanism, control logic, track circuit and optical and audible signalling, se Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eInherent items that are critical for obtaining sub-functions were grouped into their respective category. See Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, example of some items critical for the crossing gate mechanism function.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eField visits were conducted together with maintenance personnel during the initial phases of the study. These visits were valuable for understanding the physics of the degradation of the system (cause and effect) and for gaining knowledge of how maintenance is executed. Discrepancies were identified between what was stated as requirements in the maintenance programme and what was performed in real life. This understanding was especially useful for later work with the FMEA-sheets.\u003c/p\u003e \u003cp\u003eOne example of the degradation process can be related to the crossing gate arm. In Sweden, level crossing gate arms are made of wood with a protective coating of paint. The crossing gate mechanism is supposed to work as a seesaw (teeter) in almost perfect balance. However, if the coating is compromised, the wood will absorb moisture. Hence, the crossing gate will become heavier, which affects the balance of the seesaw. This will in turn lead to excessive degradation and failure of mechanical components within the crossing gate mechanism. See Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAnother example of a failure process can be seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Here, grease is injected into the grease nipples on the outside of the crossing gate mechanism, in accordance with the maintenance programme. However, excessive grease propagates to the inside of the mechanism and drips down onto the roller switch (which indicates the position of the gate arm) causing it to lose its function, usually in an intermittent manner. An obvious cause of No Fault Found events (NFF). While consulting outdated maintenance programmes it was discovered that there used to be a instruction requiring excess grease to be removed when applying new grease. This instruction could however not be found in current maintenance programs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOne of the challenges when working with complex systems where many different inherent items can experience multiple failure modes is to get a bird eye system view of the problem. One solution to this problem was to perform a rudimentary form of Fault Tree Analysis (FTA), illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. By using different colours, different aspects of function, failure mode and maintenance programme can be illustrated. The orange colour illustrates the unwanted top event of a faulty crossing gate mechanism function. The yellow colour illustrates the degraded functional states of sub-components. The blue colour marks the failure modes and the grey colour indicate areas where the current maintenance programme or its application can be insufficient.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe FMEA was constructed following recommendations from IEC 60812 (Analysis techniques for system reliability \u0026ndash; Procedure for failure mode and effects analysis, FMEA) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. At outset, the study followed the standard structure of the FMEA sheets, where the physical item was the baseline for the analysis. However, this led to a rather tedious exercise since a number of items experience the same type of failure modes, causing each failure mode to be described in the same way on multiple occasions for different items. This causes the FMEA-sheet to become somewhat incoherent and the group working with the analysis lost focus on multiple occasions. Hence, the recommendation for future studies is to focus on functions instead of physical items. In this case, the study should emanate from the required system function (e.g. level crossing), or appropriate sub system function, e.g., the crossing gate mechanism\u0026rsquo;s required function. Next step is to assess the failure modes which can cause loss of required function. Thereafter, the items whose functions are critical for maintaining required function. See Table\u0026nbsp;1.\u003c/p\u003e \u003cp\u003e Table 1 part 1, 2 and 3 of FMEA-sheet.\u003c/p\u003e \u003cp\u003e\u003cimg 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\" width=\"554\" height=\"561\"\u003e\u003c/p\u003e\u003cp\u003eThis approach is a functional FMEA and is in its structure much more like the representations created in the fault trees. This is also from a maintenance point of view a more rational structure since the purpose of maintenance is to maintain or restore required system functions and not the condition of physical items.\u003c/p\u003e \u003cp\u003eIn addition, the FMEA (Table\u0026nbsp;1) proved to be much valuable to reconstruct the logic behind the documented maintenance programme.\u003c/p\u003e \u003cp\u003eThe first part of the FMEA describes unit, function and failure mode. The second part of the FMEA describes the failure modes\u0026rsquo; failure cause, local and final effect as well as the detection method (e.g., inspections), and compensating provisions against failure (e.g., actual maintenance task to be executed). The third part of the FMEA contains recommendations for alternative detection methods and recommended measures.\u003c/p\u003e \u003cp\u003eParts one and two of the FMEA-sheet describe the present situation. Part three of the FMEA-sheet describes improvements that can be achieved compared to the present situation. The beauty of this structure is also that it directly indicates which failure mode a recommended measure addresses, while the structure allows us to see which type of effects, we could expect in relation to implementing, e.g., recommended changes. Overall, it gives a much useful initial structure for Design of Experiments (DoE). The combination of FTA and FMECA allows to recreate the logic behind the maintenance programmes. It also provides a baseline for experiments, which can be conducted in an orderly fashion since it already from the outset is possible to isolate the consequences of proposed changes. The FMEA is also valuable for collecting recommendations for future system modifications.\u003c/p\u003e \u003cp\u003eThe conducted study rendered in a long list of recommendations. Some of the operational recommendations were:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eBetter instructions for battery maintenance, remove oxide from terminals, use special grease.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDevelop decision support for when to exchange batteries.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInstructions for applying grease, and cleaning of excess grease.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eBetter instructions for when to paint gate arms.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInclude inspection of cross gate mechanism heating.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eMake sure that failures of structural items are corrected (doors, seals, mosquito-nets, rubber strips).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIf required, cleaning of roller switches from access grease to prevent intermittent failures.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eSome of the tactical and strategical recommendations are:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eUse other material than wood in gate arms. Materials which do not absorb water and which can withstand snow and ice build-up.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eExchange track circuits to axle counters.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eChange signalling light from bulbs to LED.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eBetter instructions for snow removal.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eRedesign of engine mounting, where present mount (standing engine) causes grease to run through the inside of the engine, causing grease to attach to motor brush and commutator, leading to intermittent failures.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e5.2. Step 2 \u0026ndash; planning of field experiment\u003c/h2\u003e \u003cp\u003eTo execute any change of a railway maintenance programme in Sweden, as in most national railway administrations, is a major task. It involves updates of rules and regulations, preparation of information systems to accommodate the changes, e.g., new inspections and new maintenance tasks. It involves developing new courses and to educate technicians on a nationwide scale. Since maintenance is executed by entrepreneurs, the changes also have to be accommodated within new and existing maintenance contracts throughout the nation. Therefore, it is necessary to validate changes in small scale before executing nationwide plans.\u003c/p\u003e \u003cp\u003eFrom the recommended changes to the maintenance programme suggested by the FMEA, an analysis was made to estimate the impact of proposed changes in terms of cost and dependability. The analysis also included the task to find a track section at which recommendations for maintenance programme and maintenance concept could be deployed for demonstration and verification.\u003c/p\u003e \u003cp\u003eTrack section 524 was identified as a useful candidate for verification testing. This track section had a high number of faults per level crossing. Configuration wise the track section represented an average constitution of level crossings in Sweden. Based on fault data this track section was in a degraded state and in need of improved maintenance. The number of level crossings (20) for the study was judged satisfactory. Expected results from the test:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eImproved dependability and reduced cost for preventive and corrective maintenance.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eCost-benefit of performed measures, which could serve as decision support for further dependability improvements for level crossing assets.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eA demonstrator for how changed maintenance programmes and maintenance concepts could be deployed nationwide, also for other systems than level crossings.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe cost-benefit analysis was constituted in three main parts:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eInitial increase of preventive maintenance effort and related cost to restore the dependability of the level crossing system.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIncreased cost for deployment of new recommended maintenance programme.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eCost-benefit comparison between increased preventive maintenance cost (pt.1 and pt.2) compared with reduced cost for corrective maintenance. An estimation was done that corrective maintenance measures could be reduced by some 50% due to increase of system dependability.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eIn theory, if the initial calculations were to hold up, the pay-off time for initial cost increase from pt.1 and pt.2 would be somewhere between 2\u0026ndash;3 years. After which the dependability level could be maintained at a lower cost than required by previous maintenance programme.\u003c/p\u003e \u003cp\u003eFrom this part of the study recommendations were also made for practical preparation of the actual experiment, some of which are:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eDetail the maintenance concept for critical items. One example being the crossing gate mechanism motor, which due to excessive application of grease can experience intermittent failures when grease comes into to the motor and clogs the brush and commutator.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTraining programme for the entrepreneurs in accordance to the new maintenance programme.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDevelop routine to keep track of costs within the experiment.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eOpen books, to keep track of real costs.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eContinuous assessment meetings with the entrepreneur to keep them focused on the task at hand. There is always a risk that they return to old habits.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe maintenance programs should contribute to extended life length of items. However, the reporting structure of failure or faults does not support an adequate description of items\u0026rsquo; life lengths. Therefore, it was recommended to conduct interviews with technicians to get their assessment of the matter.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eConduct interviews with infrastructure manager and signalling experts to document their experiences, which are useful for further development of maintenance programs and for the deployment on a larger scale\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e5.3. Step 3 \u0026ndash; execution of verification field test\u003c/h2\u003e \u003cp\u003eVerification testing started with an inspection fit for the purpose of assessing the amounts of material that had to be pre-ordered before the physical work could be conducted. Two days were required to complete the inspection, i.e., 10 level crossings per day.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;2 Signalling related faults and NFF 2008\u0026ndash;2021\u003c/p\u003e \u003cp\u003e Results of the experiment were in accordance with expectations. Hence, the number of faults were reduced by a magnitude of 50%. The physical work was conducted in June 2012, Table\u0026nbsp;2 shows the development of signalling related faults for the years 2008\u0026ndash;2021.\u003c/p\u003e \u003cp\u003eTable 2 Signalling related faults and NFF 2008-2021\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e\u003cp\u003eInteresting to observe is also that the number of no fault found (NFF) events were reduced in comparison to previous statistics.\u003c/p\u003e \u003cp\u003eIt should be mentioned, that the test was only carried out 2012 to somewhere in 2014. A technician involved in the test, who is still working on the same track section have confirmed that maintenance execution from 2015 onwards has in most aspects returned to how maintenance was carried out before the test. This might explain why the number of faults has increased from 2015 onwards.\u003c/p\u003e \u003cp\u003eAs for the NFF events, the crossing gate mechanism motor has been a source of intermittent failures in all level crossings. There was a hypothesis that the cause of the intermittent failures were the cause of excess grease contaminating items internal to the motor. Before executing the verification test, the project set out to test this hypothesis by examining a couple of the motors to assess whether grease was in fact contaminating items internal to the motor.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA couple of motors were therefore disassembled for this purpose, see Fig.\u0026nbsp;6. The picture in the middle clearly shows a contaminated commutator. The left picture shows commutator after cleaning operation. From a cost perspective, this finding was especially interesting.\u003c/p\u003e \u003cp\u003eThe current practice is to replace the motor in field if it has any major problem. The cost for one new motor in 2012 was 1,550\u0026euro;. If the motor had been refurbished at a factory, the cost was somewhere around 1,200\u0026euro;. A time study conducted before the field test showed that it took about 30 minutes to refurbish an engine in field conditions, with an estimated refurbishment cost of about 50\u0026euro;. Hence, the cost saving potential is somewhere around 25\u0026ndash;30 times. This could have an enormous impact on the total asset management cost of level crossings if implemented nationwide.\u003c/p\u003e \u003cp\u003eA test was set up within the verification test to examine whether refurbishment of engines was, from a reliability point of view a viable alternative to exchanging motors. Therefore, a lot of motors were replaced in the beginning of the verification test. Motors were exchanged in three categories, new, refurbished in factory, and refurbished in field. In addition, instructions for applying a correct amount of grease to the motors was included in the maintenance concept.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;3 shows the number of reported faults on track section 514 where a motor is replaced for the test series. Interesting to observe is that none of the motors replaced due to fault is a motor refurbished in the field. Therefore, it can be concluded that refurbishing motors in the field is, from a reliability and cost point of view, a much more viable task than the other two alternatives. In practice a more logical production logistics would be to bring motors refurbished at a entrepreneur workshop out in the field and replace the contaminated motors to bring them back to the workshop for refurbishment.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;3. Number of faults requiring exchange of motor\u003c/p\u003e \u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e\u003cp\u003eTightening of terminals (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003e) is also something that should be included in the maintenance programme. On multiple occasions, it was discovered that connectivity was not satisfactory. This is a likely cause of intermittent failures and NFF events. However this is something that does not have to be conducted every year, therefore similar measures should be planned as reoccurring periodic restorations e.g. every third year.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAnother interesting field observation was that the paint recommended for protective coating of the gate arms was not working as intended. It did not provide an adequate protection cover. However, when efforts were made to paint the gate arms with a second layer (15 minutes after the first coating) of the same paint the results were fantastic, almost like a shrink tubing had been placed on to the arm, see Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003e. As for future maintenance concepts of gate arms, they should state that two coats of paint should be applied.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOther recommendations for the maintenance programme was also derived from the test, while changing gate arms. As the base paint (from factory) was deemed inadequate to withstand moisture, the recommendation was to paint the whole gate arm when installing new materials. And especially add paint to the end of the gate arm, which almost always has to be sawed into right length, leaving the end unprotected and exposed to rain, se middle picture in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003e. Gate arms are almost all the time facing the rain since they are only lowered at train passage. Hence, without protective coating at the tip, water will sipper into the wood of the gate arm\u003c/p\u003e \u003cp\u003eA time study was also conducted to assess the production rate for maintenance of level crossing. During the planning of the experiment phase, an assumption was made that two persons would require one day to perform maintenance of one level crossing in accordance with the new instructions. During the experiment, it was obvious that two level crossings could be managed if the execution was well planned and all required materials were prepared and brought to field. For future maintenance concepts, it is useful that the same personnel get to do the physical work since they get better at it for each day.\u003c/p\u003e \u003c/div\u003e"},{"header":"6. Conclusions","content":"\u003cp\u003eThe work presented in this paper shows that it is possible to fulfil requirements of value creation within asset management and enterprise risk management and internal control (i.e., compliance, effectiveness, productivity and documentation) when working with continuous dependability improvement. The applied combination of methodologies focusing on process, function and system (primarily FMECA, FTA and DoE) fulfil requirements related to compliance (primarily railway safety and RAM) and documentation. In addition, the effectiveness is improved by increased availability performance simultaneously as the productivity is improved by cutting costs. However, in spite of this, there have not been any general implementation of the project results, e.g., by changes in Trafikverket\u0026rsquo;s maintenance programmes. This unsatisfactory situation is not unique for this project or for Trafikverket, but it is actually becoming more frequently recurring. Hence, there are dedicated research areas studying the pacing problem, i.e., the phenomenon where the regulators are struggling to keep pace with the fast technological development and avoid ossification.\u003c/p\u003e \u003cp\u003eAs indicated above, roles responsible for and working with dependability improvements should participate in every part of the maintenance process. This to ensure that changed tasks in maintenance programmes are supported and executed in the right way at all process phases. It is important that correct information is collected throughout the experiment. Preferable, the same systems should be used for planning and data collection during the experimentation study as during normal operation. One reason is that different tasks in the railway infrastructure should be coordinated, e.g., regarding possession times. Another reason is that data should be used to measure any change in dependability and cost.\u003c/p\u003e \u003cp\u003eIt was possible to get dependability data with good enough quality by combining sources such as the inspection system (Bessy), the fault reporting and corrective action system (0Felia), and the asset register (BIS). Hence, it was also possible to estimate the obtained dependability improvements. However, cost data with sufficient quality was more challenging to obtain. Hence, it was not possible to estimate the actual cost savings in a good way. The major obstacle for receiving good quality cost data is that Trafikverket only has aggregated or contract-related cost data. However, the maintenance entrepreneur has more specific and real cost data related to individual maintenance tasks in the railway infrastructure. However, even when data is available it may not be relevant for dependability improvements related to the maintenance programmes. Hence, the use of FMECA can support the identification of relevant information to collect in field to monitor specific functions and their failure modes. In addition, the FMECA can be used to evaluate possible condition monitoring applications to support condition-based maintenance (CBM) of different failure modes.\u003c/p\u003e \u003cp\u003eWhen working with changes that requires field tests in the railway infrastructure, it is crucial to always start with the design of the experiment. This involves to identify what to control, what to measure, how to measure and determine how to perform the evaluation. It is not sufficient to expect that these things sort itself out at the end or that someone else will take responsibility at the end. These things have to be determined already in the experimental design stage, and pre-test is a good way to test assumptions made in the design. Without proper preparation of experimental design, it is not uncommon that data is collected which at the end is shown to be insufficient for evaluation purposes. The planning of the experiment should consider the overarching purpose. In this case, it is to receive information to make a correct decision about improvements of the existing maintenance programme. Hence, it is a deductive approach that starts with the decision, then identifies necessary information as support, and finally what data to collect and analyse. The FMEA and FTA are valuable to get a useful system description for experimental design purposes. Hence, the FMECA and FTA can be used to document expert knowledge and judgement or statistical correlations that are the foundation of the maintenance program. The experiments can contribute with establishing causal relationships by verifying and validating expert judgements and statistical correlation analyses.\u003c/p\u003e \u003cp\u003eAfter the test was executed, Banverket performed an own inspection to control that all included level crossings had been maintained by the entrepreneurs according to the new instructions. This control revealed that some maintenance tasks had been omitted by the entrepreneur. However, after the control inspection by Trafikverket and resulting communication activities, the entrepreneur executed the remaining work. In summary, trust is good, but control is better (necessary) to enable a follow up of the effects of proposed changes. Hence, the ones responsible for the test have to stay involved in all aspects of it, especially regarding maintenance execution in field. It is not possible to assume that the operative maintenance personnel in field automatically understands what and how tasks should be executed, or that they are motivated. Hands-on education in the field is the best way to get an understanding and acceptance, i.e., show physically how the tasks are to be carried out. The ones designing the test will also learn and get insight about the application area and its limitations by participating in day-to-day maintenance activities in the field.\u003c/p\u003e \u003cp\u003eThe later follow-up of the long-term effects of proposed changes, reveals that it is challenging to follow a planned experiment that requires an extended test time to estimate achieved affect. Hence, it requires perseverance to conduct a planned experiment that extends over several years. Especially when persons related to decisions and tasks included in the experiment includes changes at both the infrastructure manager and at the maintenance entrepreneur. Normally, most people are excited to test something new, but perseverance is required to conduct a study for a number of years\u003c/p\u003e \u003cp\u003eAn interesting finding of the study is related to the maintenance of level crossing motors. By repairing the motor in field instead of replacing it, gives a potential cost saving of 25\u0026ndash;30 times. When considering this on a national level for all relevant level crossings, the savings becomes significant. Hence, the FMECA and FTA supported a simple level of repair analysis that identified a dependability improvement with great cost saving and no negative impact on the availability for functions required by rail and road traffic. However, for lines with very high density traffic, replacement of the motor may still be preferred compared with field repair due to availability requirements. In these cases, a combination can be applied by using a field restored motor for replacement of the faulty motor and thereafter repair the replaced motor in field. By this approach, only field level maintenance is involved and other levels of repairs are excluded. This should reduce NFF events and associated costs, as well as other Life support costs (LSC), e.g., related to logistics.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompliance with Ethical Standards\u003c/h2\u003e \u003cp\u003eThe research presented in this paper are conducted and reported in line with signed agreements by participating actors to ensure compliance with regulations that are mandatory for authorities in Sweden as a member of the EU.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eWe acknowledge the financial and intellectual support received from Trafikverket, especially the R\u0026amp;D project \u0026ldquo;ASSET\u0026rdquo; (TRV 2022/29194). Functionality provided by \u0026ldquo;Reality Lab Digital Railway\u0026rdquo; (TRV 2017/67785, and Vinnova, 2017\u0026ndash;02139) is also highly appreciated.\u003c/p\u003e\u003cp\u003eA version of this paper has previously been presented at the Industrial AI Congress 2023 (IAI2023) in Lule\u0026aring; [8].\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eIEC (2010) 60300-3-11 - Dependability management Application guide - Reliability centred maintenance. International Electrotechnical Commission, Geneva Switzerland\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIEC (2017) 50126 - Railway Applications - The Specification and Demonstration of Reliability, Availability, Maintainability and Safety (RAMS). International Electrotechnical Commission, Geneva Switzerland\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIEC (2008) 60300-3-14 - Dependability management - Application guide - Maintenance and maintenance support. International Electrotechnical Comission, Geneva Switzerland\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIEC (2006) 60300-3-11 - Analysis techniques for system reliability \u0026ndash; Procedure for failure mode and effects analysis (FMEA). International Electrotechnical Comission, Geneva Switzerland\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGranstr\u0026ouml;m R (2009) DoU utredning av Banverkets v\u0026auml;gskyddsanl\u0026auml;ggningar. Technical report. Trafikverket, Lule\u0026amp;#229\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGranstr\u0026ouml;m R (2011) Underh\u0026aring;llsbehovsanalys \u0026ndash; Beslutsst\u0026ouml;d f\u0026ouml;r drifts\u0026auml;kerhetsh\u0026ouml;jning v\u0026auml;gskyddsanl\u0026auml;ggningar. Technical report. Trafikverket, Lule\u0026amp;#229\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGranstr\u0026ouml;m R (2012) Halv\u0026aring;rsutv\u0026auml;rdering f\u0026ouml;rst\u0026auml;rkt underh\u0026aring;ll v\u0026auml;gskyddsanl\u0026auml;ggningar BDL 524. Technical report. Trafikverket, Lule\u0026amp;#229\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGranstr\u0026ouml;m R, S\u0026ouml;derholm P (2023) Systematic dependability improvements within railway asset management. Proceedings of Industrial AI Congress (IAI2023), Lule\u0026aring;, Sweden 2023\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-system-assurance-engineering-and-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijsa","sideBox":"Learn more about [International Journal of System Assurance Engineering and Management](http://link.springer.com/journal/13198)","snPcode":"13198","submissionUrl":"https://www.editorialmanager.com/ijsa/default2.aspx","title":"International Journal of System Assurance Engineering and Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Railway, dependability, Asset management","lastPublishedDoi":"10.21203/rs.3.rs-4557557/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4557557/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper describes results from a research and development (R\u0026amp;D) project at Trafikverket (Swedish transport administration). The purpose of the study was to systemize dependability improvements of Trafikverket\u0026rsquo;s Control Command and Signalling (CCS) assets. A case study was conducted on level crossings that represent a critical part of the CCS system. The results of the study show that the systemic approach contributes to asset management as it contributes to short-term dependability and productivity improvements as well as to medium term specifications for system modifications and long-term specifications for next generation of level crossings. The approach is based on a combination of methodologies and tools described in dependability standards, e.g., Failure Modes, Effects \u0026amp; Criticality Analysis (FMECA). However, the approach also considers aspects from Design of Experiments (DoE) to support field tests aligned with other tasks in the railway infrastructure. Besides contributing to improvements, the approach complies with regulations and mandatory standards. Examples of these are Common Safety Method for Risk Evaluation and Assessment (CSM-RA, EU 402/2013) and EN 50126 - RAMS (Reliability, Availability, Maintainability \u0026amp; Safety) for railway applications. In addition, the approach complies with regulatory requirements related to enterprise risk management and internal control, i.e., effectiveness, productivity, compliance and documentation. The approach also supports asset management in accordance with the ISO 55000-series.\u003c/p\u003e","manuscriptTitle":"Approach to systematic improvements of dependability within railway asset management","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-10 02:34:23","doi":"10.21203/rs.3.rs-4557557/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revisions","date":"2024-07-09T01:59:07+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-06-13T14:16:11+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-13T09:44:42+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"International Journal of System Assurance Engineering and Management","date":"2024-06-12T15:37:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of System Assurance Engineering and Management","date":"2024-06-12T02:14:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-system-assurance-engineering-and-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijsa","sideBox":"Learn more about [International Journal of System Assurance Engineering and Management](http://link.springer.com/journal/13198)","snPcode":"13198","submissionUrl":"https://www.editorialmanager.com/ijsa/default2.aspx","title":"International Journal of System Assurance Engineering and Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"78dd7cf2-e3e9-43a9-907e-da11fdd5d8bf","owner":[],"postedDate":"July 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-10-07T16:12:54+00:00","versionOfRecord":{"articleIdentity":"rs-4557557","link":"https://doi.org/10.1007/s13198-024-02523-4","journal":{"identity":"international-journal-of-system-assurance-engineering-and-management","isVorOnly":false,"title":"International Journal of System Assurance Engineering and Management"},"publishedOn":"2024-10-01 15:56:53","publishedOnDateReadable":"October 1st, 2024"},"versionCreatedAt":"2024-07-10 02:34:23","video":"","vorDoi":"10.1007/s13198-024-02523-4","vorDoiUrl":"https://doi.org/10.1007/s13198-024-02523-4","workflowStages":[]},"version":"v1","identity":"rs-4557557","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4557557","identity":"rs-4557557","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}