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[object Object],[object Object],[object Object],[object Object]
is to influence and to  control the quality at the time of manufacturing .   Statistical  Process Control (SPC) focuses on controlling the manufacturing process to  prevent defects rather than detect them. Purpose and Application of SPC
BENEFITS OF SPC ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Sources of variation which are built into the process and will be caused by such problems as Types of variation Inherent variation (chance cause) : These are the source of random variation , the extent of which can be measured and monitored. The level of variation will continue unless something special occurs. ,[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Special cause variation (assignable cause)
 
[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],Statistics
Average (  )  or Mean : It simply means sum of all the individual observed data divided by the no. of observations. X 1  + X 2  + X 3  + - - - - + Xn   n n = no. of Observations. Example  : Observations = 20, 24, 26, 28, 43, 18 n = 6  20+24+26+28+43+18 =  =  6 =  26.5 X  X  X
Range (R) : Range is measure of the variation in a set of data. It is calculated by subtracting the lowest value in the data set from the highest value in that same set.  R =  X max – X min X max = 43, X min = 18 R = 43 – 18 = 25 Observations = 20, 24, 26, 28, 43, 18
Assuming Normal distribution as the pattern of variation for measured characteristics, we know that Average + 3   / - 3   comprises almost all (99.73%) of the observations. Hence 6 sigma is used as a measure of process capability. Lack of statistical control results in a variability larger than 6 sigma. Thus 6 Sigma is valid for statistically stable process and sigma is estimated as       =  / d 2   R
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],spread spread X   = X
Indices Tolerance  Process Capability  = Cp = Potential Capability The Capability Index is defined as the ratio of the Specification spread or Tolerance to the Process Variation = USL - LSL  6  / d 2   R
[object Object],[object Object],[object Object],[object Object],[object Object]
Cpk = Achieved Capability 3   Min of Or  - LSL 3   Cpk = USL – X  X  Where,    =  /  d 2  and the actual average is  R  X
CONSTANT  X  X  median R S
[object Object],[object Object],[object Object]
Inferences based on Cpk : 3 .  Cpk = 1.00 represents a just capable process and the process can give good results only if it is perfectly centered. Even a small deviation from the mid of specification will result in non conformance. Here 100% of the tolerance is used. Not a very desirable solution.   4.  Cpk < 1.00 means that the process not capable of meeting the specified tolerance. In this case, rework and rejection will be inevitable.
 

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Spc

  • 1.
  • 2. is to influence and to control the quality at the time of manufacturing . Statistical Process Control (SPC) focuses on controlling the manufacturing process to prevent defects rather than detect them. Purpose and Application of SPC
  • 3.
  • 4.
  • 5.
  • 6.  
  • 7.
  • 8.
  • 9. Average ( ) or Mean : It simply means sum of all the individual observed data divided by the no. of observations. X 1 + X 2 + X 3 + - - - - + Xn n n = no. of Observations. Example : Observations = 20, 24, 26, 28, 43, 18 n = 6 20+24+26+28+43+18 = = 6 = 26.5 X X X
  • 10. Range (R) : Range is measure of the variation in a set of data. It is calculated by subtracting the lowest value in the data set from the highest value in that same set. R = X max – X min X max = 43, X min = 18 R = 43 – 18 = 25 Observations = 20, 24, 26, 28, 43, 18
  • 11. Assuming Normal distribution as the pattern of variation for measured characteristics, we know that Average + 3  / - 3  comprises almost all (99.73%) of the observations. Hence 6 sigma is used as a measure of process capability. Lack of statistical control results in a variability larger than 6 sigma. Thus 6 Sigma is valid for statistically stable process and sigma is estimated as  = / d 2 R
  • 12.
  • 13. Indices Tolerance Process Capability = Cp = Potential Capability The Capability Index is defined as the ratio of the Specification spread or Tolerance to the Process Variation = USL - LSL 6 / d 2 R
  • 14.
  • 15. Cpk = Achieved Capability 3  Min of Or - LSL 3  Cpk = USL – X X Where,  = / d 2 and the actual average is R X
  • 16. CONSTANT X X median R S
  • 17.
  • 18. Inferences based on Cpk : 3 . Cpk = 1.00 represents a just capable process and the process can give good results only if it is perfectly centered. Even a small deviation from the mid of specification will result in non conformance. Here 100% of the tolerance is used. Not a very desirable solution. 4. Cpk < 1.00 means that the process not capable of meeting the specified tolerance. In this case, rework and rejection will be inevitable.
  • 19.