Browsing by Author "Lampreia, Suzana Paula Gomes Fernando da Silva"
Now showing 1 - 5 of 5
Results Per Page
Sort Options
- Control Charts Limits Flexibility Based on the Equipment ConditionsPublication . Lampreia, Suzana Paula Gomes Fernando da Silva; Vairinhos, Valter Martins; Lobo, Victor J. A. S.; Parreira, Rui; Requeijo, José GomesCondition Based Maintenance became an important development in industrial and transport equipment maintenance efforts. Many statistical methodologies have been applied in this area. These methodologies are usually applied off-line: after the data is collected. We propose an online, real-time condition monitoring system based on a modified control chart, applied to engine parameters. These charts should be flexible enough and its control limits should reflect the equipment state, the manufacturer specifications and onboard meteorological conditions. In this study we will develop a methodology to specify flexible chart control limits. The experimental equipment is a combined diesel or gas propulsion system. Two phases will be assumed. In phase 1 the equipment and historical data are analyzed, studying historical data, which leads to the definition of equipment parameters. In phase 2, new data is obtained by simulation, and the Exponentially Weighted Moving Average charts are applied considering flexible limits.
- Diesel Engine Condition Monitoring Due to Different Operation AreasPublication . Lampreia, Suzana Paula Gomes Fernando da Silva; Lobo, Victor J. A. S.; Requeijo, José GomesWhen a ship design is developed, its engines are installed accordingly the owner requisites and the environment conditions in the designated operation area. Usually they are not adapted to sail all over the world. This implies that in some cases the power output cannot be the same for the safety of the engine, If a engine was conceived to operate on 16ºC of ocean sea, when it navigates on a 36ºC ocean, the engine power must be limited in order to not provoke major damage. Due to the fact, in this study two diesel engines will be monitor with online data collection and statistical treatment. The statistic treatment will be with the univariate control charts. With the engines operating on a range of ocean temperatures form 16ºC to 36ºC, the power limitatiom and the systems must be flexible due the use of the engines and consequently the use of ships over sea.
- Implementation of MEWMA Control Chart in Equipment Condition MonitoringPublication . Lampreia, Suzana Paula Gomes Fernando da Silva; Vairinhos, Valter Martins; Requeijo, José Gomes; Dias, J. M.The progressive degradation of presently operating electro-mechanical systems is a certain future fact. To minimize losses, maintenance costs and eventual replacements, condition monitoring should be applied to critical equipment (Condition Based Maintenance – CBM). The state of equipment can be predicted at any moment using statistical methods to analyze condition monitoring data. In this paper, collected data are vibration values, obtained at p points (p = 4 for instance) of an experimental equipment, forming p variables. When independence condition does not hold, it is suggested modeling data with Auto-Regressive Integrated Moving Average (ARIMA) models, and using the residues of the estimated model for Phase I. In Phase I, the estimation of parameters is achieved using the Hotelling T control chart; only after applying the defined ARIMA model, the p variables are treated. In Phase II, equipment state is artificially degraded through induced failures and failure prediction obtained using special multivariate control charts for data statistical treatment. Assuming data independence and normality, Multivariate Exponentially Weighted Moving Average Modified (MEWMAM) control charts are applied in Phase II to data collected from an electric pump, controlling the behavior of data using this procedure. In Phase II, for non-independent data the prediction errors from the adjusted model are used instead of original data. To show that the suggested methodology can be applied to propulsion systems, simulated data from a gas turbine are used. Using these methodologies it is possible to run online condition monitoring, and act in time, to minimize maintenance costs and maximize equipment performance.
- Opportunistic Maintenance Based on CUSUM Control ChartsPublication . Lampreia, Suzana Paula Gomes Fernando da Silva; Vairinhos, Valter Martins; Lobo, Victor J. A. S.; Parreira, Rui; Requeijo, José GomesThe use of a Ship Maintenance Management System is fundamental for the good performance of equipments and the entire platform. Over the systematic maintenance, the opportunistic maintenance is a concept that aims to minimize outages and costs preventing undesirable failures. To implement this kind of maintenance statistical methodologies must be used. The Cumulative Sum charts have a very good performance applied to processes control in quality control. We proposed the use of Modified Cumulative Sum control charts to equipment maintenance.The data under study are observations of cooling water and oil temperatures from a diesel generator. In the first phase, we will apply traditional control charts, and, in the second phase, the Cumulative charts with a certain Average Run Length will be used. Then we will compare the results and extract conclusions, presenting measures for improvement.
- Ships on Condition Data Driven Maintenance ManagementPublication . Lampreia, Suzana Paula Gomes Fernando da Silva; Lobo, Victor J. A. S.; Requeijo, José Gomes; Vairinhos, Valter MartinsOn condition maintenance management is gaining general acceptance both in ships as in other domains. This is a natural result given evolution of low cost sensors, statistical methodology, telecommunications, software and superabundance of observational data. In this paper we analyze the effects of digital revolution on the usual maintenance policies and anticipate its consequences on ships maintenance management. Specifically, we try to show that on condition maintenance is, intrinsically, a data driven maintenance policy and the natural solution that results from the convergence of those economic and technological realities. The existence of low cost, high quality sensors, means that sensor networks can be and are being installed in new and existing machinery projects. this means that high quality monitoring data is or can be continuously generated (thousand variables), at acceptble costs, covering all aspects considered relevant from the point of view of risks (consequences of failures), costs, nature and operational importance of equipment. This means the generation, transmission and in decisions and policies. the development of statistical methodology capable of transforming, in real time, those data mountains in useful knowledge is, nowadays, accomplished routinely using almost free software or, at least, easily accessible resources. The real problems are, frequently, realted with human resources and knowledge management, The paper identifies with real data examples some of the main consequences and issues associated to this new reality and its effects on main maintenance policies and mangement organizations.