An autonomous system for maintenance scheduling data-rich complex infrastructure: Fusing the railways’ condition, planning and cost

Durazo-Cardenas, Isidro Sergio; Starr, Andrew; Turner, Christopher; Tiwari, Ashutosh; Kirkwood, Leigh; Bevilacqua, Maurizio; Tsourdos, Antonios; Shehab, Essam; Baguley, Paul; Xu, Yuchun; Emmanouilidis, Christos

doi:10.1016/j.trc.2018.02.010

Cited by 50 publications

(32 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Their goals focus on keeping the system running as well as reducing excessive maintenance. Preventative maintenance evolutions and tasks are typically planned by the maintainers in systems to help reduce downtimes 33 . These downtimes cannot only slow down system performance for the customers, but they can also incur costs depending on how extensive the required maintenance may be 34 .…”

Section: Methodsmentioning

confidence: 99%

A stakeholder framework for evaluating the ‐ilities of autonomous behaviors in complex adaptive systems

Douglas

Mazzuchi

Sarkani

2020

Systems Engineering

View full text Add to dashboard Cite

Complex adaptive systems (CAS) exhibit emergent behaviors caused by the nonlinear actions between individual components within the system and their environment. These emergent behaviors are difficult to predict and measure making it very challenging to initially design from the start. Developing CASs, such as an autonomous swarming unmanned system, is a relevant key task today for solving hard problems with limited resources in a demanding economy. Swarming unmanned systems are valued by their unique capabilities, but how do stakeholders ensure their needs are considered during development? Certain stakeholders have interests that go beyond the initial delivery of the system, yet developers seem to focus efforts on designing autonomous behaviors to satisfy immediate mission needs. To close this gap, we propose a stakeholder focused framework for evaluating CASs over a full system life cycle for swarming unmanned systems. A goal‐oriented requirements engineering modeling methodology, Knowledge Acquisition in AutOmated Specification, is used to map requirements between stakeholder goals and autonomous behaviors. Behaviors are analyzed in an agent‐based simulation using NetLogo for quantifying stakeholder‐driven performance qualities (‐ilities). A case study was performed for a swarm of unmanned surface vessels called wave gliders to evaluate performance over the entire system life cycle.

show abstract

Section: Methodsmentioning

confidence: 99%

A stakeholder framework for evaluating the ‐ilities of autonomous behaviors in complex adaptive systems

Douglas

Mazzuchi

Sarkani

2020

Systems Engineering

View full text Add to dashboard Cite

show abstract

“…The application of the URRAN methodology, which is considered in CVPX-2016, is an attempt to consider the risk level of a failure probability (λ) of technical means during their operation [7,8].…”

Section: Methodsmentioning

confidence: 99%

The determination of the repairs of railway track considering the reliability and risk level

Grin

Kovalenko

2020

E3S Web Conf.

View full text Add to dashboard Cite

The method of predictive calculations of the state of the rails as the main element of assessing the state of the track when planning major repairs of the track is given. With a standard service life of 600 to 700 million tons gross, it is necessary to predict the number of defective rails on the track when increasing the service life to 1100 million tons gross (considering local rail replacement during intermediate repairs). The polygon for assigning repairs is determined by the number of “Windows” that can be provided per week on the section. The projected increase in the work of the track causes the need to increase life cycle cost depreciation charges for the formation of the repair Fund for capital repairs by 30-35%.

show abstract

“…This can help improve the outcomes of complex maintenance decisions [163]. The benefits of migrating to new tools, particularly in a data-rich environment can be large [164].…”

Section: E Big Data Analytics Tool Selection and Challengesmentioning

confidence: 99%

Requirements for Big Data Adoption for Railway Asset Management

2020

View full text Add to dashboard Cite

Nowadays, huge amounts of data have been captured along with the day-today operation of assets including railway systems. Hence, we have come to the era of big data. The utilization of big data technologies for asset condition information management is becoming indispensable for improving asset management decision making. The vital information such as precursor information collected on failure modes and knowledge that may be available for analysis is hidden within the large extent of data. There are analysis tools incorporated with techniques such as multiple regression analysis and machine learning that are facilitated by the availability of big data. Therefore, the utilization of big data technologies for asset condition information management is becoming indispensable for improving asset management decision making. This paper provides a review of the requirements and challenges for big data analytics applications to railway asset management. The review focuses on railway asset data collection, data management, data applications with the implementation of Blockchain technology as well as big data analytics technologies. The need for, and the importance of big data analytics in railway asset management; and the requirement for the asset condition data collection in the railway industry are highlighted. Research challenges in railway asset management via application of big data analytics are identified and the future research directions are presented. INDEX TERMS Big data analytics, asset management, railway, data management, blockchain.

show abstract

An autonomous system for maintenance scheduling data-rich complex infrastructure: Fusing the railways’ condition, planning and cost

Cited by 50 publications

References 48 publications

A stakeholder framework for evaluating the ‐ilities of autonomous behaviors in complex adaptive systems

A stakeholder framework for evaluating the ‐ilities of autonomous behaviors in complex adaptive systems

The determination of the repairs of railway track considering the reliability and risk level

Requirements for Big Data Adoption for Railway Asset Management

Contact Info

Product

Resources

About