Presentation Huggo Sena. - EMSHIPm120.emship.eu/Documents/MasterThesis/2012/Huggo Sena..pdf ·...

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2/16/12 1 Huggo Sena Ba/sta Analysis and prediction of welding deformations of ship panels in prefabrication process Master Student: Huggo Sena Batista Professor: PhD. Tadeusz Graczyk Nantes, France 15/February/2012 Huggo Sena Ba/sta Outlines Topics • Introduction • Initial Analysis • Modeling • Result • Conclusion 2

Transcript of Presentation Huggo Sena. - EMSHIPm120.emship.eu/Documents/MasterThesis/2012/Huggo Sena..pdf ·...

Page 1: Presentation Huggo Sena. - EMSHIPm120.emship.eu/Documents/MasterThesis/2012/Huggo Sena..pdf · Huggo Sena Batista Subject: EMSHIP Presentation Keywords: EMSHIP ZUT Created Date: 2/16/2012

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Huggo  Sena  Ba/sta  

Analysis  and  prediction  of  welding  deformations  of  ship  panels  in  

prefabrication  process  

Master  Student:  Huggo  Sena  Batista  

Professor:  PhD.  Tadeusz  Graczyk  

Nantes,  France    15/February/2012  

Huggo  Sena  Ba/sta  

Outlines  

Topics  •  Introduction  •  Initial  Analysis  •  Modeling  •  Result  •  Conclusion  

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Introduction  

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Huggo  Sena  Ba/sta  

Introduction  

◊ Shipbuilding  Industry    Different  process,  machinery  and  technology  

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 Reduction  of  problem  and  rework  after  process;  

Introduction  

◊ Shipbuilding  Industry    Improvements:  

New  technologies:  raw  material,  strength,  corrosion  etc.;  

 Reduction  of  the  warm-­‐up  (process);  

 New  welding  technologies;  

 Layout;  

 Reduction  of  the  welding  problems  

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Huggo  Sena  Ba/sta  

Introduction  

◊ Shipbuilding  Industry    Improvements:  

Welding-­‐induced  deformation   5  

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Huggo  Sena  Ba/sta  

Introduction  

◊ Problem    Welding-­‐induced  deformation  due  to  residual  stress  

Process   Heating-­‐cooling  cycles  

Welding  parameter  +  

 Initial  imperfection    +  

Pressure  (Gantry)  +  …  

Factors  

SAW  

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Huggo  Sena  Ba/sta  

Introduction  

◊ Problem    Welding-­‐induced  deformation  due  to  residual  stress  

Welding-­‐induced  deformation  

Plate  without  any  deformation  

Steel  Plates  

SAW  SAW  

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Huggo  Sena  Ba/sta  

Introduction  

◊ Proposed  solution  

Prediction  of  welding-­‐induced  deformation  

DoE  –  Numerical  equation  

Statistical  Analysis  

Current  situation  Analysis  

Results    

DoE  –  Planning  and  data  collection  

Modeling    

Initial  Analysis  

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Huggo  Sena  Ba/sta  

Initial  Analysis  

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Huggo  Sena  Ba/sta  

Initial  Analysis  

◊ Current  situation  analysis    Process  evaluation  

•  Edge  preparation  (butt  joint)  

•  Tack  welding  

•  Submerged  Arc  Welding  (SAW)  

•  Plate  transportation  

•  Turn-­‐over  unit  

•  Submerged  Arc  Welding  (SAW)  

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◊ Current  situation  analysis    Problem  –  welding-­‐induced  deformation  

•  After  1st  butt-­‐welding  

   →  Heat  Input                Welding  Current          +  Welding  Speed          +  Voltage          +  Efficiency  factor  (SAW)  

 →  Magnetics  

 →  Copper  Bar  

Initial  Analysis  

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◊ DoE  –  Planning  and  data  collection  

•  Design  of  Experiment  •  Factors,  level,  restrictions  etc  •  Data  collection  (measurement)  

Level  Heat  Input   Magnetic  

Pressure  Copper  Bar  Pressure    

[kJ/cm]   [bar]   [bar]  

Minimum   10.4   1.0   0.35  Central   10.9   1.5   0.40  

Maximum   11.8   2.0   0.45  27  different  welding  condition!  

Initial  Analysis  

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Huggo  Sena  Ba/sta  

◊ Current  situation  analysis  –  Summary  

Initial  Analysis  

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Modeling  

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Modeling  

◊ Statistical  analysis    Assumptions  –  Data  processing  

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Modeling  

◊ Statistical  analysis  

 •  Only  data  from  1st  side  butt  welding  (SAW)    •  Only  real  data  

 After  data  collection  →  Data  processing  (Assumption)  

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Modeling  

◊ Statistical  analysis    Data  processing  –  data  input  

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Modeling  

◊ Statistical  analysis    Data  processing  –  data  input  

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8  Trials  (DoE)  

Done  Outstanding  

19  Trials  =  50  measured  points  

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2   Data  input  (DoE)  Modeling  Verification  

•  17  trials  to  modeling  the  numerical  equation  •  2  trials  for  verification  

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Modeling  

◊ Statistical  analysis    Data  processing  –  outcomes    Characteristics  considered:  

     •  Terms  of  the  model      •P-­‐values  of  the  model      •  Residual      •  F-­‐value      •  Lack  of  fit  of  the  model      •  Standard  deviation  

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Modeling  

◊ Statistical  analysis    Data  processing  –  ANOVA  (Analyze  of  Variance)  

Item   Specification   ANOVA  

Terms  of  the  Model   -­‐   Q   CB   M   Q*CB   Q*M  P-­‐value  –  Terms   <0.05   0.91   0.54   0.26   0.04   0.0  P-­‐value  –  Model   <0.05   0.0  Residual  Mean  Square   -­‐   22.48  F  value  –  Model   -­‐   4.44  F  value  –  Terms   -­‐   0.01   0.38   1.31   4.28   15.26  Lack  of  Fit   >0.05   0.1  Standard  Deviation   -­‐   4.7  

 These  values  might  be  different,  depend  on  the  data  arrangement.    All  the  values  were  analyzed  based  on  statistical  fundaments.  

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Huggo  Sena  Ba/sta  

Modeling  

◊ DoE  Numerical  equation    Data  processing  –  Numerical  equation  

D=   +422.45083  

-­‐35.87045  ·∙  Q   ←Heat  Input  -­‐574.07631  ·∙  CB   ←Copper  bar  pressure  -­‐113.80114  ·∙  M   ←Magnetic  pressure  +52.41132  ·∙  Q  ·∙  CB  +10.01348  ·∙  Q  ·∙  M  

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Results  

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Huggo  Sena  Ba/sta  

Results  

◊ Prediction  of  welding-­‐induced  deformation    Using  the  equation  –  residual  calculation  

-­‐20  -­‐15  -­‐10  -­‐5  0  5  10  15  20  

19.33  

22.67  

17.67   32  

24  

31  

31.33  

22.33  

13.67  

23.67   18  

17  

23  

14.67  

21.33  

27.67  

13.33   21  

29.33   32  

19  

28.33  

Residu

al  [m

m]  

Actual  values  

Residual  (Actual  x  Predicted)  

Variation  =  ±  10  mm  (±  2.1  σ)  

+3  σ  

-­‐3  σ    

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Results  

◊ Prediction  of  welding-­‐induced  deformation    Using  the  equation  –  predicted  values  

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Huggo  Sena  Ba/sta  

Results  

◊ Prediction  of  welding-­‐induced  deformation    Using  the  equation  –  predicted  values  (theoretical)  

Deformation  [m

m]  

Heat  I

nput  

[kJ/cm

]  Magnetics  [bar]  

Copper  bar  [bar]:  0.45  

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Results  

◊ Prediction  of  welding-­‐induced  deformation    Using  the  equation  –  2  trials  for  verification  

-­‐20  -­‐15  -­‐10  -­‐5  0  5  10  15  20  

33.33  

16.00  

19.30  

17.67  

34.33  

30.00  

Residu

al  [m

m]  

Actual  values  

Residual  (Actual  x  Predicted)  

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+3  σ  

-­‐3  σ    Variation  =  ±  9  mm  (±  1.9  σ)  

Huggo  Sena  Ba/sta  

Conclusion  

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Conclusion  

◊ Welding-­‐induced  deformation  is  possible  to  predict  through  statistical  analysis;  

◊ Data  arrangement  analyses;  

◊ A  initial  analysis  of  the  process  to  define  the  main  factors;  

◊ Statistical  results  vs  sources  of  error;  

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Huggo  Sena  Ba/sta  

Analysis  and  prediction  of  welding  deformations  of  ship  panels  in  

prefabrication  process  

Master  Student:  Huggo  Sena  Batista  

Professor:  PhD.  Tadeusz  Graczyk  

Nantes,  France    15/February/2012  

Thank  you!  

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Meaning  

◊ Statistical  analysis  Item   Recom   Mean  

F  value  –  Model   >1   Relation  between  model  variance  with  the  residual  (error)  variance.    If  the  model  variance  is  bigger  than  the  error  variance,  F  value  >1  and  null  hypothesis  is  out.  F  value  –  Terms   >  1  

P-­‐value  –  Terms   <0.05     Small  probabilities  reject  the  null  hypothesis  (significant).  The  possibility  to  verify  F-­‐value  if  the  null  hypothesis  is  true.  P-­‐value  –  Model   <0.05  

Residual  Mean  Square   -­‐  Square  root  of  the  sum  of  the  residual  square.    It  verifies  if  the  model  is  close  or  not  of  the  real  values  

Lack  of  Fit   >0.05  This  is  the  variation  of  the  data  around  the  fitted  model.  Large  values  means  that  this  characteristics  is  not  significant  (NOT  significant  LOF  =  the  model  fits    the  data)  

Standard  Deviation   √RMS   Estimate  of  the  SD  associated  to  the  experiment  

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