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QFD with statistical ranking – a hydropower turbine case study
ID
Rihar, Lidija
(
Author
),
ID
Jenko, Marjan
(
Author
)
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Abstract
Influences of hydropower plant water turbine operational parameters on turbine operational economics, reliability and lifetime are ranged with a new type of QFD method that includes parameter distribution densities and probabilities. In our method, each dominant i.e., main parameter coexists with associated side parameters. Their contribution to effects, usually attributed to the main parameter only, is modelled by a) probability density of the side parameter contribution to the main parameter effects, and by b) side parameters’ Bernoulli distribution since association of side parameter to the dominant parameter effects is in the realm of probability and not all side parameter effects are associated with the main parameter effects at all times. Analysis results are probability densities of dominant parameters influence measure on the turbine operating attributes. A simulation tool was built to establish relations amongst influential parameters and turbine’s economics, reliability and lifetime. We obtained technical data associated with turbine operation attributes from turbine senior designers having led successful projects within last 30 years. Simulation results have been validated with existing turbine-projects maintenance data.
Language:
English
Keywords:
hydropower turbine maintenance
,
parameter probability density
,
predictive analysis
,
QFD
,
QFD SR
,
sensitivity analysis
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FS - Faculty of Mechanical Engineering
Publication status:
Published
Publication version:
Version of Record
Year:
2024
Number of pages:
Str. 239-250
Numbering:
Vol. 23, no. 2
PID:
20.500.12556/RUL-160338
UDC:
658.58:621.224
ISSN on article:
1726-4529
DOI:
10.2507/IJSIMM23-2-681
COBISS.SI-ID:
205307139
Publication date in RUL:
26.08.2024
Views:
199
Downloads:
11
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Record is a part of a journal
Title:
International journal of simulation modelling
Shortened title:
Int. j. simul. model.
Publisher:
DAAAM International Vienna
ISSN:
1726-4529
COBISS.SI-ID:
8008982
Licences
License:
CC BY-NC 4.0, Creative Commons Attribution-NonCommercial 4.0 International
Link:
http://creativecommons.org/licenses/by-nc/4.0/
Description:
A creative commons license that bans commercial use, but the users don’t have to license their derivative works on the same terms.
Secondary language
Language:
Slovenian
Keywords:
vzdrževanje turbin
,
hidroelektrarne
,
gostota verjetnosti parametrov
,
analiza napovedi
,
QFD
,
analiza občutljivosti
Projects
Funder:
ARRS - Slovenian Research Agency
Project number:
P2-0270
Name:
Proizvodni sistemi, laserske tehnologije in spajanje materialov
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