This flow chart outlines the steps for implementing statistical process control (SPC). It involves: 1) Conducting a gauge repeatability and reproducibility study to ensure measurement systems are adequate. 2) Calculating process capability indices like Cp, Cpk to determine if a process is capable. 3) Collecting control chart data over multiple shifts to establish control limits. 4) Analyzing control chart data to identify processes that are in or out of control and determine appropriate corrective actions.

1. SPC Implementation Flow Chart

2. Flow chart for SPC implementation
R&R<10% for Key
and <20% for
other dim
Improve
measurement
system
No
Yes
Pp >1.83 & PPK>1.33
for key. Pp & Ppk >1.0
for other dim.
Yes
No
Discuss with the concern
process owner for
improving Pp and Ppk
Capability
Control
Calculate st dev (don’t use R bar/d2), Pp
and Ppk.
Collect 50/100 samples from different
shifts(20 per shift) so as to cover all the
common causes
Conduct gauge R&R BY operators who
does the inspection,(Ref.G R&R
Flowchart)
Study the Machine Capability As per Machine
Capability flowchart
If Cmk≥1.67
Implement corrective
actions and repeat
capability study
No
Yes

3. All samples
with in
control limit
Yes
No Remove the point by finding the assignable cause
and recalculate the new control limits with
remaining subgroups
Take fresh samples of 20 sub group of 5samples each
and put in the new limits
All samples
with in control
limit
No
Freeze the control limits and start
using them.
Freeze the control limits and start
using them.
Yes
Prepare OCAP(out of control
action plan) and give training to
operators
Prepare OCAP(out of control
action plan) and give training to
operators
Collect 20 sub group of 5 samples each(drawn from different
shifts/capability data) asses control limits and plot X bar R
chart for above 20 sub groups.
Control
Flow chart for SPC implementation

4. Gage R&R Flow Chart
Select the characteristics
Spec. variation Process variation
Collect ten parts that represents the full range
of Spec. variation. If the parts don't vary as
much as the spec, the gage error will be
overstated.
Collect ten parts that represents the full range
of process variation. If the parts don't vary as
much as the process, the gage error will be
overstated.
Mark each part with a number 1-10 in such a
way that the appraisers can not see the
numbers as they take it for the measurements.
Identify three/more appraisers who are directly involved in the inspection
( on process)
Start the study with Appraiser A measure each of the ten parts in random
order(3 times each part not Continuously ) repeat the same
With other 2 appraiser(B&C).
Spec. variation Process variation
Calculate the Gage R&R in Minitab ANOVA
method(Here Click Options, Enter your
specification limits)
Calculate the Gage R&R in Minitab ANOVA
method((Here Click Options, Enter your Process
Variation)
Is Gage R&R
within 10% of
Spec. &NDC >5
for key
Dimn..and other
Dimn within 20%
&NDC >5
Start SPC Study
Yes
step to improve results is to analyze the
breakdown of the error source. If the
largest contributor to error is Repeatability,
then the equipment must be improved Or
Within part Variation. Likewise, if
Reproducibility is the largest source of
error, appraiser training and adherence to
procedures can yield improvement.
No

5. Machine
Capability
Flow chart
Start
Set the machine to the mean in case of bilateral
tolerance and to the minimum side for unilateral
tolerance
Collect continues(in the order of manufacturing without any
intereption) 50/100 parts and measure these parts in
production sequence and note down the readings
Calculate stdev( not r bar/d2) and Cmk
Cmk = minimum value of
If Cmk≥1.67
The machine is capable
yes
Implement corrective
actions and repeat
Machine capability study
NO

6. Thank You