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Maintaining optimal measures of effectiveness by scenario requirements optimization
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Aerodynamics.
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Optimala effektivitetsm├ątt genom optimering av scenarion. (Swedish)
Abstract [en]

This thesis proposes a solution on how to manage support resources in such a way that optimized Measures of Effectiveness (MOE), such as Availability and Number of Backorders, are kept within a specified range without incurring the full scale re-optimizations in OPUS10 with every change in operative scenario. This has previously been experienced by FMV.

The hypothesis in this study is that the different risks inherent in the different scenarios are the causes of the changes in the MOE. Therefore by capturing the risks involved and treating those risks, it is possible to preempt the risks developing into problems. A solution to this end has been crafted based on the methodologies of Technical Measurement and Quality Function Deployment (QFD).

QFD methodology recommends going to the intended operational environment of the system, to capture the requirements. This study proposes using the norms of the Swedish Armed Forces (SWAF) as stipulated in the regulations regarding transports within the army," Transportreglemente", augmented with the methods of System Architecture to catch the stated and unstated user requirements.

The methods of Technical Measurement are then used to turn the requirements into Measures of Effectiveness, Key Performance Parameters (KPP), Measures of Performance (MOP) and Technical Performance Measures (TPM).

This study shows how to use the QFD House of Quality (HOQ) in the design of optimal support infrastructure, by prioritizing the MOP in order of criticality to support system performance. The MOP are then subjected to a sensitivity analysis ,before being used to design experiments which are tested to see which designs are satisfactory in relation to target performance within a tolerance band.

A design tradeoff of the design of different support infrastructure is performed in case of unsatisfactory performance or as new data is acquired as a result of an Estimation, Feasibility or Performance analysis.

Place, publisher, year, edition, pages
2014. , 100 p.
Series
TRITA-AVE, ISSN 1651-7660 ; 2014:60
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-163916OAI: oai:DiVA.org:kth-163916DiVA: diva2:802638
Examiners
Available from: 2015-04-13 Created: 2015-04-13 Last updated: 2015-04-13Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • Other locale
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Output format
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