# GMS 401 Lecture Notes - Statistical Process Control, Ferrari F2012, Incandescent Light Bulb

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12 Nov 2012
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1S.P.C. Statistical Process Control: GMS-401 F2012
In GMS-401 we study 2 types:
1. Inspection for variables —there is typically one dimension most
indicative of QUALITY or lack of Quality of an item being studied for compliance
to a Quality Standard. Here it is a dimension such as the contents of a jar of fruit
jam, the size of a pair of shoes etc. These are called X-bar and R charts. One
calculates X-bar-bar and R-bar averages and these are the centre lines of the SPC
run-charts that will be drawn. The charts MUST have these centre lines PLUS
upper and lower control AND range limits. The points on these graphs MUST be
joined so that a reader can follow the level of quality versus centre lines and control
limits over time and look for trends and potential out-of-control conditions.
The data will be in a set of readings typically taken at say one-hour intervals. The
number of readings taken each hour is the sample size–for example 4 jars of jam in
the exercise book. The sample size of 4 is used in calculating the control limits and
for determining the value of the statistical constants used in these calculations such
as A2, D3,D4.
The “number of samples” is 10 but the “sample size” is 4.
The 10 samples will be plotted on a graph but the number 10 in this case is NOT
used in the calculation of control limits when looking up the A2,D3, and D4 values.
In this type of SPC BOTH graphs must be drawn and examined. If a SINGLE
POINT on either graph exceeds the upper or lower control or range limits, the
process is said to be “out of control”. If NO points exceed the range or control
limits, the process is said to be “in control.
In addition the analyst will examine the graphs for patterns showing either expected
random behaviour or the tendency towards an
out-of-control condition. The QUALITY GURUS: Deming, Juran, Crosby,
Taguchi, Feigenbaum were the originators and proponents of SPC. Their themes
were:
1. A statistical sample can be taken and can provide great accuracy as to the quality
and acceptability of a batch of production. One need not examine EVERY unit of
production–it is too time consuming and too expensive AND would put a firm that
used this approach at a competitive disadvantage.
2. Perhaps we cannot have ZERO DEFECTS in production but we can certainly
minimize the defects (in many cases a total financial loss for the firm) but taking
statistical samples at appropriate intervals (depends on the volatility of the process–
how frequently will a factor affect quality–sharpness of tools etc.) and
EMPOWERING the production line employees with the ability to shut down the
production line if a trend towards OUT-OF-CONTROL is noted. We want
employees to stop the process BEFORE it is out-of-control and producing
substandard products that will not meet our customer’s needs–and they will
probably return them at our expense and stop buying from us. Look at the one-page
lime green sheet handed-out in class that discusses how to read and interpret a
control chart. There you can see the trends that we would expect production line
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## Document Summary

In gms-401 we study 2 types: inspection for variables there is typically one dimension most indicative of quality or lack of quality of an item being studied for compliance to a quality standard. Here it is a dimension such as the contents of a jar of fruit jam, the size of a pair of shoes etc. One calculates x-bar-bar and r-bar averages and these are the centre lines of the spc run-charts that will be drawn. The charts must have these centre lines plus upper and lower control and range limits. The points on these graphs must be joined so that a reader can follow the level of quality versus centre lines and control limits over time and look for trends and potential out-of-control conditions. The data will be in a set of readings typically taken at say one-hour intervals.

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