The thesisproject concerns the development of a methodology to connect data, from theAirbus department in Stade, with each other and find relationships between themwhich lead to a prioritising tool with which justifiable decisions can bededuced in order to plan which Measurement System Analysis (MSA) to conductnext, focusing on cost effectiveness.  Therefore, the main content will revolvearound studying and analysing relevant literature and connecting this with theactual data, as present at Airbus, to arrive at a functional tool.  As such, the main aim and objectivesconcentrate around developing a thorough understanding of the relevant data anddiscovering how they relate with one another and with costs. Aim would be tofind a causal relationship, which is then subsequently also verified andvalidated.      The main findings areexpected to give the relationships between the data, e.g. that a certainimprovement of X% in MSA leads to Y% better Cpk (Process Capability Index. Adjustmentof Cp for the effect of non-centred distribution) and as such Z% reduction inCost of Non Quality (CNQ) per process.      As Airbus is in a toughcompetition with Boeing and other aircraft manufacturers, finding ways to bemore cost effective is very useful. Especially now with the populationof the earth rapidly growing and the use of aircraft for travel becoming morereadily available/affordable for everyone, the amount of aircraft that need tobe in the worlds fleet is expanding even more. As such, the rate ofconstruction of aircraft is rising tremendously and improvements in recurringcosts are ever more valuable. Even though the work is dedicated to Airbusprocesses, the methodology as developed for the prioritisation tool should begeneralisable to also be applicable for other situations and as such give aworthwhile contribution to the body of knowledge: How these data relate witheach other and how this knowledge/information can be turned into practicalimprovements.