Predictive Maintenance Modelling for Through-Life Engineering Services

Predictive maintenance needs to forecast the numbers of rejections at any overhaul point before any failure occurs in order to accurately and proactively take adequate maintenance action. In healthcare, prediction has been applied to foretell when and how to administer medication to improve the health condition of the patient. The same is true for maintenance where the application of prognostics can help make better decisions. In this paper, an overview of prognostic maintenance strategies is presented. The proposed data-driven prognostics approach employs a statistical technique of (i) the parameter estimation methods of the time-to-failure data to predict the relevant statistical model parameters and (ii) prognostics modelling incorporating the reliability Weibull Cumulative Distribution Function to predict part rejection, replacement, and reuse. The analysis of the modelling uses synthetic data validated by industry domain experts. The outcome of the prediction can further proffer solution to designers, manufacturers and operators of industrial product-service systems. The novelty in this paper is the development of the through-life performance approach. The approach ascertains when the system needs to undergo maintenance, repair and overhaul before failure occurs

A Simulation Based Approach to Model Design Influence on the Fatigue Life of a Vented Brake Disc

The brake disc is considered a safety critical components in vehicles, hence the growing concern on its service life performance. Brake disc performance is measured by several criteria of which prominent amongst these criteria is fatigue life and disc thermal deflection. This study considers the influence of geometric design features of a vented brake disc on its fatigue life at particular sections of the brake disc which are considered critical and its deflection due to thermal inputs. A parametric study is carried out with CAE/FEA using Taguchi design of experiment. The study identified the geometric design features that significantly influence the studied performance measures. Sensitivity plots were also obtained to show the manner these design factors affect the fatigue life at these points as well as the disc thermal deflection. Two design features, the inboard plate thickness and the length of the effective offset are observed to contribute majorly to the fatigue life of the brake disc as well as its thermal deflection. Hence, design effort should be concentrated on these features for optimal fatigue life design at these points of interest in this study

'In-situ' inspection technologies: Trends in degradation assessment and associated technologies

The advent of advanced, innovative and complex engineered systems has established new technologies that are far more superior and perform well even in harsh environments. It is well established that such next generation systems need to be maintained regularly to prevent any catastrophic failure as a result of regular wear and tear. Non-destructive and structural monitoring technologies have been supporting maintenance activities for over a century and industries still continue to rely on such technologies for effective degradation assessment. Maintenance ‘in-situ’ has been adopted for decades where the health of system or component needs to be inspected in its natural environment, especially those safety critical systems that need in-field inspection to determine its health. This paper presents selective case studies adopted in the area of damage assessment that qualify for both field and ‘in-situ’ inspection. The future directions in the applicability of traditional and advanced inspection techniques to inspect multiple materials and in the area of inaccessible area degradation assessment have also been presented as part of this study

A study of pulsed thermography for life assessment of thin EB-PVD TBCs undergoing oxidation ageing

This paper presents an assessment of ageing for thin Thermal Barrier Coatings (TBC) using active thermography. As TBCs undergo ageing during their service life, sintering changes the porosity, elements migrate from the substrate, and micro-cracks build up in the structure of the material, exhibiting a change in thermal conductivity and diffusion properties. As the material ages and these properties change over time, it is possible to exploit trends in this change for characterisation of coating ageing, which would provide a diagnostics tool to estimate remaining useful life. In this study, through-depth diffusivity measurement has been applied to thin EB-PVD coatings which are artificially aged via oxidation furnace cycles. In order to address the difficulties of capturing a fast thermal event in a thin coating, a novel parametric study approach has been carried out to optimise data capture and analysis, maximising available frames for the model fitting step. Through-depth diffusivities have been measured during ageing for six samples, yielding a repeatable trend in thermal diffusivity measurements, with three features, which can be exploited for ageing characterisation of thin EB-PVD TBCs, and used as an alarm of imminent failure

A coefficient clustering analysis for damage assessment of composites based on pulsed thermographic inspection

This paper introduces a coefficient clustering analysis method to detect and quantitatively measure damage occurring in composite materials using pulsed thermographic inspection. This method is based on fitting a low order polynomial model for temperature decay curves, which (a) provides an enhanced visual confirmation and size measurement of the damage, (b) provides the reference point for sound material for further damage depth measurement, (c) and reduces the burden in computational time. The performance of the proposed method is evaluated through a practical case study with carbon fibre reinforced polymer (CFRP) laminates which were subjected to a drop impact test with varying energy levels. A novel method for reducing an entire thermogram sequence into a single image is introduced, which provides an enhanced visualisation of the damage area

New Threats for Old Manufacturing Problems: Secure IoT-Enabled Monitoring of Legacy Production Machinery

The digitization of manufacturing through the introduction of Industrie 4.0 technologies creates additional business opportunities and technical challenges. The integration of such technologies on legacy production machinery can upgrade them to become part of the digital and smart manufacturing environment. A typical example is that of industrial monitoring and maintenance, which can benefit from internet of things (IoT) solutions. This paper presents the development of an-IoT-enabled monitoring solution for machine tools as part of a remote maintenance approach. While the technical challenges pertaining to the development and integration of such solutions in a manufacturing environment have been the subject of relevant research in the literature, the corresponding new security challenges arising from the introduction of such technologies have not received equal attention. Failure to adequately handle such issues is a key barrier to the adoption of such solutions by industry. This paper aims to assess and classify the security aspects of integrating IoT technology with monitoring systems in manufacturing environments and propose a systematic view of relevant vulnerabilities and threats by taking an IoT architecture point of view. Our analysis has led to proposing a novel modular approach for secure IoT-enabled monitoring for legacy production machinery. The introduced approach is implemented on a case study of machine tool monitoring, highlighting key findings and issues for further research

Statistical Methods for Convergence Detection of Multi-Objective Evolutionary Algorithms

In this paper, two approaches for estimating the generation in which a multi-objective evolutionary algorithm (MOEA) shows statistically significant signs of convergence are introduced. A set-based perspective is taken where convergence is measured by performance indicators. The proposed techniques fulfill the requirements of proper statistical assessment on the one hand and efficient optimisation for real-world problems on the other hand. The first approach accounts for the stochastic nature of the MOEA by repeating the optimisation runs for increasing generation numbers and analysing the performance indicators using statistical tools. This technique results in a very robust offline procedure. Moreover, an online convergence detection method is introduced as well. This method automatically stops the MOEA when either the variance of the performance indicators falls below a specified threshold or a stagnation of their overall trend is detected. Both methods are analysed and compared for two MOEA and on different classes of benchmark functions. It is shown that the methods successfully operate on all stated problems needing less function evaluations while preserving good approximation duality at the same time.Article / Letter to editorLeiden Inst. Advanced Computer Science

Effects of negative air ions on oxygen uptake kinetics, recovery and performance in exercise: a randomized, double-blinded study

Copyright © ISB 2013Limited research has suggested that acute exposure to negatively charged ions may enhance cardio-respiratory function, aerobic metabolism and recovery following exercise. To test the physiological effects of negatively charged air ions, 14 trained males (age: 32 ± 7 years; {Mathematical expression}: 57 ± 7 mL min-1 kg-1) were exposed for 20 min to either a high-concentration of air ions (ION: 220 ± 30 × 103 ions cm-3) or normal room conditions (PLA: 0.1 ± 0.06 × 103 ions cm-3) in an ionization chamber in a double-blinded, randomized order, prior to performing: (1) a bout of severe-intensity cycling exercise for determining the time constant of the phase II {Mathematical expression} response (τ) and the magnitude of the {Mathematical expression} slow component (SC); and (2) a 30-s Wingate test that was preceded by three 30-s Wingate tests to measure plasma [adrenaline] (ADR), [nor-adrenaline] (N-ADR) and blood [lactate] (BLac) over 20 min during recovery in the ionization chamber. There was no difference between ION and PLA for the phase II {Mathematical expression}τ (32 ± 14 s vs. 32 ± 14 s; P = 0.7) or {Mathematical expression} SC (404 ± 214 mL vs 482 ± 217 mL; P = 0.17). No differences between ION and PLA were observed at any time-point for ADR, N-ADR and BLac as well as on peak and mean power output during the Wingate tests (all P > 0.05). A high-concentration of negatively charged air ions had no effect on aerobic metabolism during severe-intensity exercise or on performance or the recovery of the adrenergic and metabolic responses after repeated-sprint exercise in trained athletes. © 2013 ISB

The challenges and opportunities of artificial intelligence in implementing trustworthy robotics and autonomous systems

Effective Robots and Autonomous Systems (RAS) must be trustworthy. Trust is essential in designing autonomous and semi-autonomous technologies, because “No trust, no use”. RAS should provide high quality of services, with the four key properties that make it trust, i.e. they must be (i) robust for any health issues, (ii) safe for any matters in their surrounding environments, (iii) secure for any threats from cyber spaces, and (iv) trusted for human-machine interaction. We have thoroughly analysed the challenges in implementing the trustworthy RAS in respects of the four properties, and addressed the power of AI in improving the trustworthiness of RAS. While we put our eyes on the benefits that AI brings to human, we should realise the potential risks that could be caused by AI. The new concept of human-centred AI will be the core in implementing the trustworthy RAS. This review could provide a brief reference for the research on AI for trustworthy RAS