A Measurement Frequency Estimation Method for Failure Prognosis of an Automated Tire Condition Monitoring System

Meissner, Robert; Meyer, H.; Raddatz, Florian

doi:10.1109/icphm.2019.8819422

Cited by 2 publications

(3 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…During the entire process, DM uses a digitalized platform to collect, validate, analyze, and transfer the data and prognostics information. Such platforms to monitor condition data of an aircraft fleet are, for instance, Skywise of Airbus [24] and Airplane Health Management of Boeing [25].…”

Section: Data Management Team (Dm)mentioning

confidence: 99%

Analyzing Emerging Challenges for Data-Driven Predictive Aircraft Maintenance Using Agent-Based Modeling and Hazard Identification

et al. 2023

View full text Add to dashboard Cite

The increasing use of on-board sensor monitoring and data-driven algorithms has stimulated the recent shift to data-driven predictive maintenance for aircraft. This paper discusses emerging challenges for data-driven predictive aircraft maintenance. We identify new hazards associated with the introduction of data-driven technologies into aircraft maintenance using a structured brainstorming conducted with a panel of maintenance experts. This brainstorming is facilitated by a prior modeling of the aircraft maintenance process as an agent-based model. As a result, we identify 20 hazards associated with data-driven predictive aircraft maintenance. We validate these hazards in the context of maintenance-related aircraft incidents that occurred between 2008 and 2013. Based on our findings, the main challenges identified for data-driven predictive maintenance are: (i) improving the reliability of the condition monitoring systems and diagnostics/prognostics algorithms, (ii) ensuring timely and accurate communication between the agents, and (iii) building the stakeholders’ trust in the new data-driven technologies.

show abstract

Section: Data Management Team (Dm)mentioning

confidence: 99%

Analyzing Emerging Challenges for Data-Driven Predictive Aircraft Maintenance Using Agent-Based Modeling and Hazard Identification

et al. 2023

View full text Add to dashboard Cite

show abstract

“…We have previously developed a theoretical concept for a full automation of condition-monitoring tasks. (Meissner, Meyer, & Raddatz, 2019) As of this paper, we will just briefly discuss key aspects of a suitable infrastructure for an effective fault diagnosis, failure prognosis and subsequent maintenance planning optimization without going into much technical detail.…”

Section: Theoretical Layout For Automated Condition Monitoringmentioning

confidence: 99%

“…Therefore, the possibility of early abnormality detection and fault forecasting promise significant easing potential in aircraft operation. (Meissner, Meyer, & Raddatz, 2019)…”

Section: Use Case Scenariomentioning

confidence: 99%

Concept and Economic Evaluation of Prescriptive Maintenance Strategies for an Automated Condition Monitoring System

Meissner

Meyer

Wicke

2021

IJPHM

Self Cite

View full text Add to dashboard Cite

In order to reduce operating costs and increase the operational stability, the aviation industry is continuously introducing digital technologies to automate the state detection of their assets and derive maintenance decisions. Thus, many industry efforts and research activities have focused on an early state fault detection and the prediction of system failures. Since research has mainly been limited to the calculation of remaining useful lifetimes (RUL) and has neglected the impact on surrounding processes, changes on the objectives of the involved stakeholders, resulting from these technologies, have hardly been addressed in existing work. However, to comprehensibly evaluate the potential of a fault diagnosis and failure prognosis system, including its effects on adjacent maintenance processes, the condition monitoring system’s maturity level needs to be taken into account, expressed for example through the technology’s automation degree or the prognostic horizon (PH) for reliable failure projections. In this paper, we present key features of an automatic condition monitoring architecture for the example of a Tire Pressure Indication System (TPIS). Furthermore, we develop a prescriptive maintenance strategy by modeling the involved stakeholders of aircraft and line maintenance operations with their functional dependencies. Subsequently, we estimate the expected implications for a small aircraft fleet with the introduction of such a monitoring system with various levels of technological maturity. Additionally, we calculate the maintenance cost savings potential for different measurement strategies and compare these results to the current state-of-the-art maintenance approach. To estimate the effects of implementing an automated condition monitoring system, we use a discrete-event, agentbased simulation setup with an exemplary flight schedule and a simulated time span of 30 calendar days. The obtained results allow a comprehensive estimation of the maintenance related implications on airline operation and provide key aspects in the development of an airline’s prescriptive maintenance strategy.

show abstract

A Measurement Frequency Estimation Method for Failure Prognosis of an Automated Tire Condition Monitoring System

Cited by 2 publications

References 16 publications

Analyzing Emerging Challenges for Data-Driven Predictive Aircraft Maintenance Using Agent-Based Modeling and Hazard Identification

Analyzing Emerging Challenges for Data-Driven Predictive Aircraft Maintenance Using Agent-Based Modeling and Hazard Identification

Concept and Economic Evaluation of Prescriptive Maintenance Strategies for an Automated Condition Monitoring System

Contact Info

Product

Resources

About