Robust vibration-based faults diagnosis machine learning model for rotating machines to enhance plant reliability

Plant availability and reliability can be improved through a robust condition monitoring and fault diagnosis model to predict the current status (healthy or faulty) of any machines and critical assets. The model can then predict the exact fault for the faulty asset so that remedial maintenance can be carried out in a planned plant outage. Nowadays, the artificial intelligence (AI)-based machine learning (ML) model seems to be current trend to meet these requirements. Hence, the paper is also proposing such vibration-based faults diagnosis ML model through an experimental rotating rig. Here, the 2-Steps approach is used with the ML model to easy the industrial operation and maintenance process. The Step-1 provides the information about the asset health status such as healthy or faulty. The Step-2 then identifies the exact nature of fault to aid the decision making for the fault rectification and maintenance activities to avoid the risk of failure and enhance the reliability

Strategy of maintenance system in industrial company

This paper introduces the main conclusions of the doctoral thesis “Strategy of maintenance system in industrial company”, which focuses on improving of economic efficiency of the maintenance system by selecting the appropriate maintenance strategy for production machines. In the paper I characterise outputs of the survey, which focuses on characterization of maintenance management level, maintenance cost control and allocation level and range of modern maintenance management tools (Computerized Maintenance Management Systems = CMMS) utilization in industrial enterprises in Czech Republic. This article also deals with proposed methodology for selecting the appropriate maintenance strategy and with the brief characteristic of the model MAM (Maintenance Analytical Module), which was developed as a decision support tool for maintenance managers

Maintenance strategy focused on the specific consumption of diesel generators in sub-saharan countries: Case of National Electricity Company of Burkina Faso

Sub-Saharan countries would mainly use thermal power plant whose Specific Consumption (SC) was relatively higher than the reference values provided by the manufacturers, which would contribute to the increase in electricity production costs. The aim of this study would be to propose a maintenance strategy which would aim to keep the SC according to the age of the generator at acceptable proportions according to the reference values provided by the manufacturers. The Ishikawa and Pareto diagrams were used to identify and analyze the causes of the variation in the SC of two large plants of the National Electricity Company of Burkina Faso. The results showed four major causes representing about 20% of the common causes which are 80% of the increase in SC in the thermal power plant of Kossodo and Komsilga, it would be : the poor quality of the fuels, lack of spare parts, inadequate maintenance practice, and poor fuel supply policy

Maintenance strategy focused on the specific consumption of diesel generators in sub-saharan countries: Case of National Electricity Company of Burkina Faso

Sub-Saharan countries would mainly use thermal power plant whose Specific Consumption (SC) was relatively higher than the reference values provided by the manufacturers, which would contribute to the increase in electricity production costs. The aim of this study would be to propose a maintenance strategy which would aim to keep the SC according to the age of the generator at acceptable proportions according to the reference values provided by the manufacturers. The Ishikawa and Pareto diagrams were used to identify and analyze the causes of the variation in the SC of two large plants of the National Electricity Company of Burkina Faso. The results showed four major causes representing about 20% of the common causes which are 80% of the increase in SC in the thermal power plant of Kossodo and Komsilga, it would be : the poor quality of the fuels, lack of spare parts, inadequate maintenance practice, and poor fuel supply policy

Electromechanical modelling of a new class of nanocomposite cement-based sensors for structural health monitoring

This work focuses on the analysis of a new nanocomposite cement-based sensor (carbon nanotube cement-based sensor), for applications in vibration-based structural health monitoring of civil engineering structures. The sensor is constituted of a cement paste doped with multi-walled carbon nanotubes, so that mechanical deformations produce a measurable change of the electrical resistance. Prior work of some of the authors has addressed the fabrication process, dynamic behaviour and implementation to full-scale structural components. Here, we investigate the effectiveness of a linear lumped-circuit electromechanical model, in which dynamic sensing is associated with a strain-dependent modulation of the internal resistance. Salient circuit parameters are identified from a series of experiments where the distance between the electrodes is parametrically varied. Experimental results indicate that the lumped-circuit model is capable of accurately predicting the step response to a voltage input and its steady-state response to a harmonic uniaxial deformation. Importantly, the model is successful in anticipating the presence of a superharmonic component in sensor’s output

Reliability analysis for automobile engines: conditional inference trees

The reliability model with covariates for machinery parts has been extensively studied by the proportional hazards model (PHM) and its variants. However, it is not straightforward to provide business recommendations based on the results of the PHM. We use a novel method, namely the Conditional Inference Tree, to conduct the reliability analysis for the automobile engines data, provided by a UK fleet company. We find that the reliability of automobile engines is significantly related to the vehicle age, early failure, and repair history. Our tree-structured model can be easily interpreted, and tangible business recommendations are provided for the fleet management and maintenance

Reliability estimation based on operational data of manufacturing systems

Maintenance management has a direct influence on equipment reliability and safety. However, a large portion of traditional maintenance models and reliability analysis methods usually assumes that only perfect maintenance is performed on the system and the system will restore to as good as new regardless of the kind of preventive maintenance work-order that is performed. This is not practical in reality and may result in an inaccurate parametric estimation. The research objective of this paper is to develop a maximum likelihood estimation method to obtain more accurately estimated parameters based on the operational data of manufacturing systems, taking into consideration the difference between perfect and imperfect maintenance work-orders. Weibull distribution is specifically studied for this purpose. A practical case study based on industrial operational data from an automotive assembly line is performed to illustrate the implementation and efficiency of the proposed reliability estimation method. Copyright © 2008 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/61212/1/959_ftp.pd

Perancangan Kebijakan Perawatan dan Penentuan Persediaan Spare Part di Sub Sistem Evaporasi Pabrik Urea Kaltim-3 PT Pupuk Kalimantan Timur

Pabrik Kaltim-3 PT Pupuk Kalimantan Timur memberikan kontribusi 17,84 % untuk produksi amoniak dan 19,13 % untuk produksi urea dari total produksi di PKT. Salah satu proses di Pabrik Urea Kaltim-3, yaitu evaporasi merupakan proses dimana larutan urea dinaikkan konsentrasinya (dikentalkan) dari konsentrasi 75% menjadi 99,8%. Untuk  mencegah kegagalan fungsi, maka diperlukan aktivitas perawatan. Aktivitas perawatan yang dilakukan di PKT masih menunjukkan adanya over dan under maintenance. Oleh karena itu akan dilakukan perancangan kegiatan perawatan dengan metode Reliability Centered Maintenance II (RCM II) yang menghasilkan fungsi, kegagalan fungsi, serta Failure Mode and Effect Analysis (FMEA). Berdasarkan informasi pada FMEA tersebut, kemudian dihasilkan kebijakan perawatan dan pelaksana teknis, serta data historis kerusakan yang digunakan untuk menghitung interval waktu perawatan. Selain itu juga dilakukan perhitungan persediaan spare part dengan memperhatikan lead time pemesanan komponen. Dengan menentukan kebijakan perawatan  dan persediaan spare part yang tepat, maka biaya yang dikeluarkan dapat diminimalisir

System Reliability Evaluation Based on Convex Combination Considering Operation and Maintenance Strategy

The approaches to the system reliability evaluation with respect to the cases, where the components are independent or the components have interactive relationships within the system, were proposed in this paper. Starting from the higher requirements on system operational safety and economy, the reliability focused optimal models of multiobjective maintenance strategies were built. For safety-critical systems, the pessimistic maintenance strategies are usually taken, and, in these cases, the system reliability evaluation has also to be tackled pessimistically. For safety-uncritical systems, the optimistic maintenance strategies were usually taken, and, in these circumstances, the system reliability evaluation had also to be tackled optimistically, respectively. Besides, the reasonable maintenance strategies and their corresponding reliability evaluation can be obtained through the convex combination of the above two cases. With a high-speed train system as the example background, the proposed method is verified by combining the actual failure data with the maintenance data. Results demonstrate that the proposed study can provide a new system reliability calculation method and solution to select and optimize the multiobjective operational strategies with the considerations of system safety and economical requirements. The theoretical basis is also provided for scientifically estimating the reliability of a high-speed train system and formulating reasonable maintenance strategies

Diseño de un plan de mantenimiento preventivo basado en la metodología RCM para la chancadora de cono MP 1000 de la unidad minera Las Bambas, provincia Cotabambas, Apurímac

Una falla de los componentes y subcomponentes de un equipo en funcionamiento causa dos problemas principales; que es el daño de los componentes y subcomponentes, y la falta de producción debido a que la planta está fuera de servicio. Además, las fallas imprevistas de los componentes aumentan la incontrolabilidad del sistema, lo que empeora la producción. El mantenimiento centrado en la confiabilidad (RCM), es un proceso para desarrollar programas de mantenimiento preventivo. El método RCM proporciona una estrategia utilizando la experiencia operativa de una manera más sistemática, se desarrolla un sistema de soporte de decisiones analizando el Modo de Falla, Efecto y Análisis de Criticidad (AMEF). En esta investigación el objetivo es diseñar un plan de mantenimiento preventivo utilizando la metodología RCM, para la Chancadora de cono MP 1000 de la unidad Minera las BAMBAS, el mismo que se realizó en base al método del análisis de criticidad de los diferentes componentes que constituyen la planta de chancado, con lo que se pretende mejorar su confiabilidad y disponilidad. La planta está ubicada en la Unidad Minera las Bambas que se ubica entre los distritos de Challhuahuacho, provincia de Cotabambas, en la Región Apurímac, a una altitud que varía entre los 3.800 y 4.600 m.s.n.m., a aproximadamente 75 km al suroeste de la ciudad de Cusco