scholarly journals A Statistical State Analysis of a Marine Gas Turbine

Actuators ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 54 ◽  
Author(s):  
Suzana Lampreia ◽  
Valter Vairinhos ◽  
Victor Lobo ◽  
José Requeijo
Keyword(s):  
Gas Turbine ◽  
Point Of View ◽  
Operating Conditions ◽  
Environmental Data ◽  
Statistical Point ◽  
Mean Time Between Failures ◽  
Time Between Failures ◽  
Intervention Plan ◽  
Mean Time

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.

Predicting Gas Turbine Reliability to Assess Risks for Purchased Power Agreements

1996 ◽  
Author(s):  
Wolfram Krockow
Keyword(s):  
Gas Turbine ◽  
Heavy Duty ◽  
Bottom Line ◽  
Mean Time Between Failures ◽  
Time Between Failures ◽  
The Monte Carlo Method ◽  
Parameter Variations ◽  
The Mean ◽  
Heavy Duty Gas Turbine ◽  
Mean Time

Availability and Reliability have become a major concern for operating companies; especially for those where unscheduled outages due to purchased power agreements may be highly penalized. On the other hand, high revenues by the sale of electricity can be achieved if the power generating set performs according to its demand. Economic calculations demonstrate that the bottom line between profit and loss lies within the high 90th% of availability. This paper summarizes the results of an analysis based on the regulations in France with its so-called EJP days (Effacement Jour Pointe). Any loss of highly penalized EJP days is quantified based on known RAM (Reliability, Availability, Maintainability) values of the equipment, as these are the Mean Time Between Failures MTBF’s and the Mean Times To Repair MTTR’s of the overall equipment as well as its subassemblies. In formulating the demand, the past 12 years of assigned EJP days by the Electricité de France, EdF, was analyzed to derive probability ratings of seasonal distributions, weekly distributions and day block distributions. The mathematics of this simulation model are based on well proven statistical procedures (i.e. the Monte Carlo Method). By performing parameter variations, the model can also quantitatively predict how much the Mean Time Between Failures of a heavy duty gas turbine must usually be better for this application when compared to an aeroderivative gas turbine. This is because it normally takes longer to repair or replace a heavy duty gas turbine versus an aeroderivative unit in case of a major unscheduled or forced outage.

Review of Technological Advancements and HSE-Based Safety Model for Deep-Water Human Occupied Vehicles

2014 ◽  
Vol 48 (3) ◽  
pp. 25-42 ◽  
Author(s):  
Narayanaswamy Vedachalam ◽  
Gidugu Ananada Ramadass ◽  
Malayath Aravindakshan Atmanand
Keyword(s):  
Deep Water ◽  
Capital Expenditure ◽  
Mean Time Between Failures ◽  
Safety Integrity Level ◽  
Geological Surveys ◽  
Time Between Failures ◽  
High Resolution Bathymetry ◽  
Safety Systems ◽  
Mean Time ◽  
Safety And Environment

AbstractThis paper reviews the latest advancements in subsea technologies associated with the safety of deep-water human occupied vehicles. Human occupied submersible operations are required for deep-water activities, such as high-resolution bathymetry, biological and geological surveys, search activities, salvage operations, and engineering support for underwater operations. As this involves direct human presence, the system has to be extremely safe and reliable. Based on applicable IEC 61508 Standards for health, safety, and environment (HSE), the safety integrity level requirements for the submersible safety systems are estimated. Safety analyses are done on 10 critical submersible safety systems with the assumption that the submersible is utilized for 10 deep-water missions per year. The results of the analyses are compared with the estimated target HSE requirements, and it is found that, with the present technological maturity and safety-centered design, it is possible to meet the required safety integrity levels. By proper maintenance, it is possible to keep the mean time between failures to more than 9 years. The results presented shall serve as a model for designers to arrive at the required trade-off between the capital expenditure, operating expenditure, and required safety levels.

Neural Network Based Modelling and GRA Coupled PCA Optimization of Hole Sinking Electro Discharge Micromachining

2014 ◽  
Vol 4 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Rajesh Kumar Porwal ◽  
Vinod Yadava ◽  
J. Ramkumar
Keyword(s):  
Neural Network ◽  
Removal Rate ◽  
Hybrid Approach ◽  
Back Propagation ◽  
Principal Component ◽  
Back Propagation Neural Network ◽  
Point Of View ◽  
Operating Conditions ◽  
Process Performance

Determination of material removal rate (MRR), tool wear rate (TWR) and hole taper (Ta) is a challenging task for manufacturing engineers from the productivity and accuracy point of view of the symmetrical and nonsymmetrical holes due to hole sinking electro discharge micro machining (HS-EDMM) process. Thus, mathematical models for quick prediction of these aspects are needed because experimental determinations of process performances are always tedious and time consuming. Not only prediction but determination of optimum parameter for optimization of process performance is also required. This paper attempts to apply a hybrid mathematical approach comprising of Back Propagation Neural Network (BPNN) for prediction and Grey Relational Analysis (GRA) coupled with Principal Component Analysis (PCA) for optimization with multiple responses of HS-EDMM of Invar-36. Experiments were conducted to generate dataset for training and testing of the network where input parameters consist of gap voltage, capacitance of capacitor and the resulting performance parameters MRR, TWR and Ta. The results indicate that the hybrid approach is capable to predict process output and optimize process performance with reasonable accuracy under varied operating conditions of HS-EDMM. The proposed approach would be extendable to other configurations of EDMM processes for different material.

A warranty based bilateral multi-issue negotiation approach

2015 ◽  
Vol 22 (7) ◽  
pp. 1247-1280 ◽  
Author(s):  
Prashant M. Ambad ◽  
Makarand S. Kulkarni
Keyword(s):  
Real Life ◽  
Spare Parts ◽  
Negotiation Process ◽  
Design Stage ◽  
Automated Negotiation ◽  
Content Type ◽  
Mean Time Between Failures ◽  
Time Between Failures ◽  
Target Values ◽  
Mean Time

Purpose – The purpose of this paper is to propose a warranty-based bilateral automated multi-issue negotiation approach. Design/methodology/approach – A methodology for bilateral automated negotiation process is developed considering the targets such as warranty attractiveness, warranty cost, mean time between failures, spare parts cost to the end user over the useful life of the life. The negotiation methodology is explained using different cases of negotiation. The optimization for each negotiation step is carried out using genetic algorithm with elitism strategy. Findings – The result after optimization indicates that the desired target values are achieved and manufacturer obtained desired profit margin. Practical implications – Application of automated negotiation model is illustrated using a real life case of an automobile engine manufacturer. The proposed approach helps the manufacturer of any product to develop a methodology for carrying out the negotiation process. The approach also results into taking warranty-related decisions at the design stage. Originality/value – This paper contributes in proposing a generalized methodology for warranty-based negotiation in which the negotiation is carried out between the manufacturer and the customer.

scholarly journals DEGRADATION ANALYSIS OF PROBABILISTIC PARALLEL CHOICE SYSTEMS

2014 ◽  
Vol 21 (03) ◽  
pp. 1450012
Author(s):  
AVINASH SAXENA ◽  
SHRISHA RAO
Keyword(s):  
Complete System ◽  
System Failure ◽  
Time To Failure ◽  
Probabilistic Choice ◽  
Mean Time Between Failures ◽  
System Parameters ◽  
Time Between Failures ◽  
Degradation Analysis ◽  
Mean Time ◽  
Selection Of

Degradation analysis is used to analyze the useful lifetimes of systems, their failure rates, and various other system parameters like mean time to failure (MTTF), mean time between failures (MTBF), and the system failure rate (SFR). In many systems, certain possible parallel paths of execution that have greater chances of success are preferred over others. Thus we introduce here the concept of probabilistic parallel choice. We use binary and n-ary probabilistic choice operators in describing the selections of parallel paths. These binary and n-ary probabilistic choice operators are considered so as to represent the complete system (described as a series-parallel system) in terms of the probabilities of selection of parallel paths and their relevant parameters. Our approach allows us to derive new and generalized formulae for system parameters like MTTF, MTBF, and SFR. We use a generalized exponential distribution, allowing distinct installation times for individual components, and use this model to derive expressions for such system parameters.

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