If it ain't broke, don't fix it: Optimizing the predictive aircraft maintenance schedule with Remaining Useful Life prognostics

Predictive aircraft maintenance is a maintenance strategy that aims to reduce the number of failures, the number of inspections, the number of maintenance tasks and the aircraft maintenance costs. Aircraft are equipped with health monitoring systems, where sensors continuously measure the condition of the aircraft components. In predictive...

Towards a digital twin architecture for the lighting industry

This paper introduces an ontology-based Digital Twin (DT) architecture for the lighting industry, integrating simulation models, data analytics, and visualization to represent luminaires. The ontology standardizes luminaire components, facilitating interoperability with design tools. The calculated ontology-level metrics suggest mid-level...

Introducing CNN-LSTM network adaptations to improve remaining useful life prediction of complex systems

Prognostics and Health Management (PHM) models aim to estimate remaining useful life (RUL) of complex systems, enabling lower maintenance costs and increased availability. A substantial body of work considers the development and testing of new models using the NASA C-MAPSS dataset as a benchmark. In recent work, the use of ensemble methods...

Multi-objective design of aircraft maintenance using Gaussian process learning and adaptive sampling

Aircraft maintenance design aims to identify strategies that render the aircraft reliable for flight in a cost-efficient manner. These are often conflicting objectives. Moreover, existing studies on maintenance design often limit themselves to only one type of maintenance strategy, overlooking other potentially dominating designs. We propose...

Predictive Aircraft Maintenance: Modeling and Analysis Using Stochastic Petri Nets

Predictive aircraft maintenance is a complex process, which requires the modeling of the stochastic degradation of aircraft systems, as well as the dynamic interactions between the stakeholders involved. In this paper, we show that the stochastically and dynamically colored Petri nets (SDCPNs) are able to formalize the predictive aircraft...

Classification prognostics approaches in aviation

Traditionally, prognostics approaches to predictive maintenance have focused on estimating the remaining useful life of the equipment. However, from an industrial point of view, the goal is often not to predict the residual life but to determine the need for a maintenance action at a given time window. This approach allows us to frame the...

A Systematic Review of Artificial Intelligence Public Datasets for Railway Applications

The aim of this paper is to review existing publicly available and open artificial intelligence (AI) oriented datasets in different domains and subdomains of the railway sector. The contribution of this paper is an overview of AI-oriented railway data published under Creative Commons (CC) or any other copyright type that entails public...

Improving Subsurface Asset Failure Predictions for Utility Operators: A Unique Case Study on Cable and Pipe Failures Resulting from Excavation Work

Utility operators must rely on predictive analyses regarding the availability of their subsurface assets, which highly depend on damage by increasing amounts of excavation work. However, straightforward use of standard statistical techniques, such as logistic regression or Bayesian logistic regression, does not allow for accurate predictions...

Using in situ density and strength measurements for sediment maintenance in ports and waterways

Purpose: Fluid mud layers can be substantial in waterways and they can jeopardise navigation when the ship’s keel comes in its vicinity. The nautical bottom has therefore to be properly characterised. Mud density and yield stress are used as criteria to characterise the nautical bottom. For a decade, measuring these parameters in situ has...

Opportunities and challenges in IoT-enabled circular business model implementation – A case study

While the enabling capabilities of the Internet of Things (IoT) in the Circular Economy (CE) have been highlighted in a number of publications, knowledge about how to leverage IoT in actual implementation of circular strategies is still lacking. This paper aims to elucidate reasons for the apparent mismatch between the ‘theoretical...

Predictive maintenance for aircraft components using proportional hazard models

Unscheduled maintenance can contribute significantly to an airline's cost outlay. Reliability analysis can help to identify and plan for maintenance events. Reliability analysis in industry is often limited to statistically based approaches that incorporate failure times as the primary stochastic variable, with additional strict assumptions...