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Chemweno P.,Catholic University of Leuven | Pintelon L.,Catholic University of Leuven | Van Horenbeek A.,Catholic University of Leuven | Muchiri P.,Dedan Kimathi University of Technology
International Journal of Production Economics

Risk assessment performs a critical decision support role in maintenance decision making. This is through assisting maintenance practitioners systematically identify, analyze, evaluate and mitigate equipment failures. Often, such failures are mitigated through formulating effective maintenance strategies. In asset maintenance, well-known risk assessment techniques include the Failure Mode and Effect Analysis (FMEA), Fault Tree Analysis (FTA), and Bayesian Networks (BN). In recent years, considerable research attention has been directed towards improving existing techniques, often at the expense of a structured framework for selecting suitable risk assessment techniques. Often, several criteria influence the selection process. Moreover, the criteria are closely linked to specific organizational competencies that vary from one firm to another. In this study, a selection methodology for risk assessment techniques in the maintenance decision making domain is proposed. In the methodology, generic selection criteria for the FMEA, FTA and BN are derived based on the risk assessment process outlined in the ISO 31000:2009 standard. The criteria are prioritized using the Analytic Network Process (ANP), taking into account the judgment and opinion of academic and industrial domain experts. The results illustrate the usefulness of the proposed methodology towards assisting maintenance practitioners discern important competencies relevant to the specific technique and as such select the technique best suited for the organization. © 2015 Elsevier B.V. Source

Wa Maina C.,Dedan Kimathi University of Technology

Biodiversity monitoring is important in assessing the state of an ecosystem and determining if conservation actions are required. This is particularly important when conservation resources are scarce. However, traditional methods of biodiversity monitoring are labour intensive and cannot be applied in every ecosystem where there is need. In order to expand the application of biodiversity monitoring, there is need to automate this important task. In this work we present an application of audio diarization methods for biodiversity monitoring and show how these methods can be used to measure the abundance of indicator taxa in areas of interest. The use of audio recordings has the potential to reduce the time and effort spent in biodiversity monitoring. The experiments are performed on a freely available dataset of bird song recordings with the birds serving as indicator taxa in the ecosystem of interest. We are able to estimate the number of bird species in the recordings and this information can be used to estimate the species richness in an ecosystem. © 2015 IEEE. Source

Zamankhan P.,Dedan Kimathi University of Technology | Zamankhan P.,University of KwaZulu - Natal
Mathematical Problems in Engineering

The air-water mixture from an artificially aerated spillway flowing down to a canyon may cause serious erosion and damage to both the spillway surface and the environment. The location of an aerator, its geometry, and the aeration flow rate are important factors in the design of an environmentally friendly high-energy spillway. In this work, an analysis of the problem based on physical and computational fluid dynamics (CFD) modeling is presented. The numerical modeling used was a large eddy simulation technique (LES) combined with a discrete element method. Three-dimensional simulations of a spillway were performed on a graphics processing unit (GPU). The result of this analysis in the form of design suggestions may help diminishing the hazards associated with cavitation. © 2015 Piroz Zamankhan. Source

Maina C.W.,Dedan Kimathi University of Technology
2015 IST-Africa Conference, IST-Africa 2015

Kenya's rich biodiversity faces a number of threats including human encroachment, poaching and climate change. Since Kenya is a developing country, there is need to manage the sometimes competing interests of development, such as infrastructure development, and conservation. To achieve this, tools to effectively monitor the state of Kenya's various ecosystems are essential. In this paper we propose a biodiversity monitoring software tool that integrates acoustic indices of biodiversity, recognition of species of interest based on their vocalizations and acoustic census. This tool can be used by non-experts to determine the current state of their ecosystems by monitoring the state of bird species that serve as indicator taxa and whose abundance is related to the abundance of other terrestrial vertebrates including the 'big five'. The tool we propose exploits state-of-the art advances in signal processing and machine learning to perform biodiversity monitoring, bird species detection and census in a joint framework. Using publicly available data we demonstrate how current acoustic indices of biodiversity can be improved by incorporating machine learning based audio segmentation algorithms. We also show how open source toolkits can be used to build bird species recognition systems. Code to reproduce the experiments in this paper is available on Github at https://github.com/ciiram/BirdPy. © 2015 IIMC International Information Management Corporation Ltd. Source

Chemweno P.K.,Center for Industrial Management Traffic and Infrastructure | Pintelon L.,Center for Industrial Management Traffic and Infrastructure | Muchiri P.N.,Dedan Kimathi University of Technology
IFAC Proceedings Volumes (IFAC-PapersOnline)

In today's industries, optimal spare parts provisioning plays a critical role towards sustaining the asset's operational capabilities. In this context, spare parts pooling is increasingly mentioned as a plausible approach for optimizing spare parts management, more so for repairable systems. In this sense, several frameworks are proposed in literature, though largely analytical, thus limiting their capabilities with respect to modeling complex repairable systems. Moreover, the nature of interactions often account for aspects such as system reliability, imperfect component reconditioning, repair capacity and spare parts inventory that is multi-echelon in nature. To realistically model such complexities, simulation approaches are often explored. This paper presents a discrete event simulation modeling study. The simulation model mimics the impact of several aspects on unreliable repairable systems. The aspects include the repair capacity, component reconditioning process, and multi-echelon spare part provisioning strategy. Moreover, the influence of spare parts quality aspects is evaluated and demonstrated in the case study of critical system for a thermal power plant. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Source

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