Slide 2 Process Control Charts Slide 3 VOCABULARY IMPORTANT
TERMS: Nominal: Data at expected value Discrete: Data with only a
finite number of values Indiscrete: Data of Acceptable vs.
Unacceptable Variable: Property being measured Under Control:
Variables fall in a nominal range Data Points: Measurements taken
Datum: A fixed reference point for measurements Slide 4 Used to
test if the process is in control Used to see if significant
changes have occurred in the process over time Indiscrete or
Continuous Data Chart or X- R Chart Measurement at time intervals
Measurements compare the control over time Example units of
measurement to Use: Length (mm) Volume (cc) Weight (gm.) Power
(kwh) Time (sec, min, hr.) Pressure (psi) Voltage (v) Discrete Data
Charts or PN-P Charts Inspection on lot or batch of parts; Notation
of the number of good and defective parts Variable representation:
The number of parts inspected in the lot = n Fraction of defective
in lot = p Number of defectives = pn Process Control Charts Slide 5
In the manufacturing process, car engine valve stems are being
machined with a nominal diameter of 13 mm. Samples are taken at the
following times of day: 6:00, 10:00, 14:00, 18:00 and 22:00, for 25
consecutive days. The diameter measurements (data) from these
samples are presented in the table on the next slide. Classroom
Example - R CHART CONSTRUCTION Indiscrete Chart Slide 6 5 Slide 7
Steps to formulating the chart: Step 1: Collect the data Step 2:
Sort the data into subgroups, such as lots, order number, or days
Step 3: Identify the values for the variables n and k, where n =
the size of the sub group (i.e., five times) k = the number of sub
groups (i.e., 25 days) Slide 8 Steps to formulating the chart: Step
4: Calculate the mean for each group that will be represented by
Slide 9 Steps to formulating the chart: Step 5: Calculate the range
for each subgroup represented by R Slide 10 Upper & Lower
Control Limits 9 Learning how to plot two separate charts: o X
Control Chart o R Control Chart The Upper Control Limit and the
Lower Control Limit set the tolerance level for the control of the
manufacture of a product. Slide 11 Steps to Calculating the Upper
& Lower Control Limits Slide 12 Continuation of Calculating the
Upper & Lower Control Limits Slide 13 Manufacturing Statistics
A 2 is from the table based on the size of the subgroup (i.e., Five
reading times) D 4 & D 3 is from the table based on the size of
the subgroup (i.e., Five reading times) Slide 14 x bar R X double
bar R barCLxUCLxLCLxCLrUCLrLCLr = Slide 15 Step 8:Plot Chart Plot
Chart Slide 16 Chart Variations Slide 17 Future Prediction Slide 18
An inspector of car wheel rims, working at the end of a
manufacturing line, near the end of each shift must inspect the lot
of wheel rims made during that shift. On good days when the welder
is running properly, over 400 wheel rims are made per batch. On
poor days, as low as 50 to 60 wheel rims are made per batch. The
inspector marks on the check sheet for each batch the total number
of wheels inspected and the number of defects returned for rework
for each lot. Classroom Example P-Control Chart Construction Slide
19 18 Slide 20 Steps to Calculating P-Control Chart Step 1. Collect
data Step 2. Divide the data into sub groups (i.e., usually days or
lot). Each sub group size should be larger than 50 units, where n =
the number in each subgroup pn = the number of defects in each sub
group Slide 21 Calculating Fraction of Defectives Step 3. Calculate
the fraction of defective parts using the following formula: Where
p = fraction (decimal) of the number of defectives pn = number of
defects in each subgroup n = number in each subgroup NOTE: To
convert result to percentage(%), multiply the result by 100 Slide
22 Calculating Average Fraction of Defectives Step 4. Calculate the
Average Fraction of Defectives using the following formula: Slide
23 Calculating Control Limits Step 5. Calculating the Control Limit
for each Subgroup: Slide 24 23 Slide 25 Step 6:Draw P Control Chart
Plot Chart Slide 26 Classroom Example On an assembly line of
windshield wiper motors, the inspector selects randomly 100 motors
per hour to examine. The inspector notes on the check sheet the
number of defective motors in each 100 selected. The inspector
samples 100 samples for a total of 30 sampling events. PN Control
Chart Slide 27 PN Control Data Chart Slide 28 Calculating the PN
Control Values 27 Slide 29 Plotting of PN Control Chart 28 Slide 30
Check For Understanding Please Develop a Control Chart for This
Valve Manufacturing line: Your Company makes gate valves which you
guarantee to flow water at 3 gallons per minute when fully open.
Any restriction or misplaced gaskets in the opening will alter this
flow rate. Your inspector at the end of the line tests one valve
each hour by measuring the flow for one minute in sample valves.
The flow rate is recorded for several days in the table in the next
slide. Is this operation in control ? Slide 31 Check For
Understanding Flow Rate in Gate Valve Inspection (gal/min) Day9
AM10 AM11 AMNoon1 PM2 PM3 PM 13.113.202.992.853.003.082.90
22.983.012.862.553.063.183.11 32.862.993.013.103.032.993.10
43.053.042.953.083.012.962.89 52.583.253.163.083.012.992.98
63.093.033.063.022.992.953.01 73.123.042.652.993.303.032.99
83.012.972.983.013.003.013.02
