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Statistical Quality Control Control Charts for Variables 4 (20) You are a new ma

ID: 3049091 • Letter: S

Question

Statistical Quality Control Control Charts for Variables 4 (20) You are a new manufacturing engineer in a Pharmaceutical industry. The operators give you some collected data over the last manufactured lots. The results are presented below. -2800 s2 = 180 -1 a. (10) Calculate the appropriate control limits b. (5) How would the control limits vary if the measure of dispersion for the data is split by half c. (5) The manager is challenging your selection of control chart based on what she remembers of the Central Limit Theorem. Justify and sustain your position

Explanation / Answer

Back-up Theory

Let there be n measurements on a quality characteristic taken at k equally-spaced intervals. Let xij represent the jth measurement at the ith interval, i = 1, 2, …., k and j = 1, 2, …., k.

The Xbar part of Xbar-s Chart has:

Central line: CL = Xdouble bar

Lower Control Limit: LCL = Xdouble bar – A3sbar

Upper Control Limit: UCL = Xdouble bar + A3sbar;

The s part of Xbar-s Chart has:

Central line: CL = sbar

Lower Control Limit: LCL = B3sbar

Upper Control Limit: UCL = B4sbar, where

Xdouble bar = (1/k)(i = 1, k)xibar, xibar = (1/n)(i = 1, n)xij

sbar = (1/k)(i = 1, k)si, si2 = {1/(n – 1)}(i = 1, n)(xij - xibar)2

A3, B3, B4 are constants which can be directly obtained from standard Control Chart Constants Table.

Preparatory Work

From the given data we find:

n = 5, k = 20, Xdouble bar = 2800/100 = 28 and Sbar = (180/20) = 3

Part (a)

All relevant computations are given below:

k

20

n

5

A3

1.427

B3

0

B4

2.089

Xdouble bar

28

sbar

3

Xbar Chart

CL

28

LCL

23.719

UCL

32.281

sChart

CL

3

LCL

0

UCL

6.267

DONE

Part (b)

When the measure of dispersion, i.e., sbar, is halved, the new sbar = 1.5, the revised control lomits would be:

Xbar Chart

CL

28

LCL

25.8595

UCL

30.1405

sChart

CL

1.5

LCL

0

UCL

3.1335

DONE

Part (c)

Since sample size is 5 and the number of samples is 20, the numbers are large enough for the Central Limit Theorem to be valid. Hence, by CLT, the sample averages can be taken to be Normally distributed and hence all calculations hold good. ANSWER

k

20

n

5

A3

1.427

B3

0

B4

2.089

Xdouble bar

28

sbar

3

Xbar Chart

CL

28

LCL

23.719

UCL

32.281

sChart

CL

3

LCL

0

UCL

6.267