No abstract

Purpose The application of condition-based maintenance on selected equipment can allow online monitoring using fixed, half-fixed or portable sensors. The collected data not always allow a straightforward interpretation and many false alarms can happen. The paper aims to discuss these issues. Design/methodology/approach Statistical techniques can be used to perform early failure detection. With the application of Cumulative Sum (CUSUM) Modified Charts and the Exponentially Weighted Moving Average (EWMA) Charts, special causes of variation can be detected online and during the equipment functioning. Before applying these methods, it is important to check data for independence. When the independence condition is not verified, data should be modeled with an ARIMA (p, d, q) model. Parameters estimation is obtained using the Shewhart Traditional Charts. Findings With data monitoring and statistical methods, it is possible to detect any system or equipment failure trend, so that we can act at the right time to avoid catastrophic failures. Originality/value In this work, an electro pump condition is monitored. Through this process, an anomaly and four stages of aggravation are forced, and the CUSUM and EWMA modified control charts are applied to test an online equipment monitoring. When the detection occurs, the methodology will have rules to define the degree of intervention.

This paper describes the analysis, from a statistical point of view, of a maritime gas turbine, under various operating conditions, so as to determine its state. The data used concerns several functioning parameters of the turbines, such as temperatures and vibrations, environmental data, such as surrounding temperature, and past failures or quasi-failures of the equipment. The determination of the Mean Time Between Failures (MTBF) gives a rough estimate of the state of the turbine, but in this paper we show that it can be greatly improved with graphical and statistical analysis of data measured during operation. We apply the Laplace Test and calculate the gas turbine reliability using that data, to define the gas turbine failure tendency. Using these techniques, we can have a better estimate of the turbine’s state, and design a preventive observation, inspection and intervention plan.

There are various causes for vibrations on diesel engines. The engine vibrations depend not only on the present state of the engine, but also on the fuel quality, the environmental conditions (sea state in the case of shipborne engines), type of casing, other equipment in the vicinity, etc. The engines used for this study are installed aboard a ship, and the main aim is to use modified control charts to assess the condition of the engine and recommend corrective measures when necessary. An important issue to do this correctly is choosing the right places to measure vibration. The collected data is vibration at various engine power levels, measured at various points. The engine’s fault history is taken into consideration, but proved to be almost irrelevant. By using modified control charts, the engine vibrations can be estimated, and faults can be detected and classified so as to take corrective actions. In this study we followed a methodology that is slightly different from our previous work, and achieved good results.

This case study intends to carry out an analysis of the waste management of the Portuguese Navy ships, limiting the study to the residues referring in Annexes I, IV and V of Marpol 73/78 [ 4 ], where the pollution by hydrocarbons, sewage and all types of garbage is approached. Methods and forms are analyzed of how the storage and treatment of ship waste is carried out, checking the existing equipment, its operational status and whether there is an on-board waste management plan. However, it is not enough to assess the materials and procedures. The knowledge and cooperation of the military on board for the environment are also determinants. It was built and implemented a questionnaire to the garrison of some selected NRP ships after permission of the Commander of Portuguese Surface Fleet. We have applied an exploratory factorial analysis (EFA) so we could identify the major questions contributions to the latent variables that explain literacy about waste management in ships. An analysis of variance was applied so we could get significant independent variables that contribute to explain the selected factors.