Students: Nidal Hurani, Ghassan IbrahimSupervisor: Shai Rozenrauch

Industrial Project (234313)

Tube Lifetime Predictive Algorithm

COMPUTER SCIENCE DEPARTMENTTechnion - Israel Institute of Technology

July 8, 2012

Goals Finding tube lifetime predictive algorithm

based on parameters and results of the CT Radar system

The algorithm target is to predict with a precision of 75% the lifetime of the tubes

Algorithm implementation

ObstaclesRaw data was not reliableCompleting the missing data in order to use

it correctly Finding parameters and measures which

influence the most of the lifetime of the tube

Fit to a known statistical model which can describe the tube lifetime given these parameters

Dealing with huge data

MethodologyRun queries over the database (SQL) to

retrieve the relevant data setProcessing and transforming the data into a

training set which is used later in the predictive algorithm

Building a windows form application which can “talk “ with R

Fitting a decision tree using CART ( Classification and Regression Tree) for the giving training set

Predict a tube lifetime given a vector of estimated parameters or measures

Environments &TechnologiesMain programming language - C#IDE - Visual studio 2010Statistical tool JMP 7 - for finding possible

statistical models which can describe the problem

EXCEL (MS office)R (Statistical Language)RCOMMSSQLJMP 7

AchievementsA predictor with ±120 days error in general

76.8293% of the predictions with ±60 days error

User friendly program

ConclusionsThe more the training set reflect the tube

real behavior the more accurate the algorithm shall predict

Depends for example on the way of completing the data & also the amount of data needs to be complete

Having a comprehensive training set gives more accurate results

The algorithm somehow is “flexible” Whenever a new parameter is recognized as a huge

influencer